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='tsn_2d_rgb_res152_seg7_kinetics400_b8_g8_cosine_cleanv3.txt', lr=0.01, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='resnet152_v1b_kinetics400', momentum=0.9, new_height=256, new_length=1, new_step=1, new_width=340, no_wd=False, num_classes=400, num_crop=1, num_epochs=100, num_gpus=8, num_segments=7, num_workers=32, partial_bn=False, prefetch_ratio=1.0, resume_epoch=0, resume_params='', resume_states='', save_dir='/home/ubuntu/yizhu/logs/mxnet/kinetics400/2dresnet/tsn_2d_rgb_res152_seg7_kinetics400_b8_g8_cosine_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 Model file not found. Downloading. ActionRecResNetV1b( (conv1): Conv2D(3 -> 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (relu): Activation(relu) (maxpool): MaxPool2D(size=(3, 3), stride=(2, 2), padding=(1, 1), ceil_mode=False, global_pool=False, pool_type=max, layout=NCHW) (layer1): HybridSequential( (0): BottleneckV1b( (conv1): Conv2D(64 -> 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (relu1): Activation(relu) (conv2): Conv2D(64 -> 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (relu2): Activation(relu) (conv3): Conv2D(64 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu3): Activation(relu) (downsample): HybridSequential( (0): Conv2D(64 -> 256, kernel_size=(1, 1), stride=(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): BottleneckV1b( (conv1): Conv2D(256 -> 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (relu1): Activation(relu) (conv2): Conv2D(64 -> 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (relu2): Activation(relu) (conv3): Conv2D(64 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu3): Activation(relu) ) (2): BottleneckV1b( (conv1): Conv2D(256 -> 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (relu1): Activation(relu) (conv2): Conv2D(64 -> 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (relu2): Activation(relu) (conv3): Conv2D(64 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu3): Activation(relu) ) ) (layer2): HybridSequential( (0): BottleneckV1b( (conv1): Conv2D(256 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) (downsample): HybridSequential( (0): Conv2D(256 -> 512, kernel_size=(1, 1), stride=(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): BottleneckV1b( (conv1): Conv2D(512 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) ) (2): BottleneckV1b( (conv1): Conv2D(512 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) ) (3): BottleneckV1b( (conv1): Conv2D(512 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) ) (4): BottleneckV1b( (conv1): Conv2D(512 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) ) (5): BottleneckV1b( (conv1): Conv2D(512 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) ) (6): BottleneckV1b( (conv1): Conv2D(512 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) ) (7): BottleneckV1b( (conv1): Conv2D(512 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu1): Activation(relu) (conv2): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (relu2): Activation(relu) (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu3): Activation(relu) ) ) (layer3): HybridSequential( (0): BottleneckV1b( (conv1): Conv2D(512 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) (downsample): HybridSequential( (0): Conv2D(512 -> 1024, kernel_size=(1, 1), stride=(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): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (2): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (3): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (4): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (5): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (6): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (7): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (8): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (9): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (10): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (11): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (12): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (13): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (14): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (15): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (16): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (17): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (18): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (19): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (20): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (21): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (22): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (23): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (24): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (25): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (26): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (27): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (28): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (29): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (30): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (31): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (32): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (33): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (34): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) (35): BottleneckV1b( (conv1): Conv2D(1024 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu1): Activation(relu) (conv2): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu2): Activation(relu) (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu3): Activation(relu) ) ) (layer4): HybridSequential( (0): BottleneckV1b( (conv1): Conv2D(1024 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu1): Activation(relu) (conv2): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu2): Activation(relu) (conv3): Conv2D(512 -> 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu3): Activation(relu) (downsample): HybridSequential( (0): Conv2D(1024 -> 2048, kernel_size=(1, 1), stride=(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): BottleneckV1b( (conv1): Conv2D(2048 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu1): Activation(relu) (conv2): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu2): Activation(relu) (conv3): Conv2D(512 -> 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu3): Activation(relu) ) (2): BottleneckV1b( (conv1): Conv2D(2048 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu1): Activation(relu) (conv2): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu2): Activation(relu) (conv3): Conv2D(512 -> 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu3): Activation(relu) ) ) (avgpool): GlobalAvgPool2D(size=(1, 1), stride=(1, 1), padding=(0, 0), ceil_mode=True, global_pool=True, pool_type=avg, layout=NCHW) (flat): Flatten (drop): Dropout(p = 0.5, axes=()) (output): Dense(2048 -> 400, linear) ) Load 240618 training samples and 19404 validation samples. 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acc-top1=46.296875 acc-top5=73.312500 Batch [0149]/[0303]: acc-top1=47.052083 acc-top5=74.010417 Batch [0199]/[0303]: acc-top1=51.015625 acc-top5=76.453125 Batch [0249]/[0303]: acc-top1=50.331250 acc-top5=75.993750 Batch [0299]/[0303]: acc-top1=49.770833 acc-top5=75.921875 [Epoch 000] training: accuracy=42.231145 loss=2.523756 [Epoch 000] speed: 92 samples/sec time cost: 2805.733717 [Epoch 000] validation: acc-top1=49.685437 acc-top5=75.892120 loss=2.353161 Epoch[001] Batch [0049]/[3760] Speed: 64.905584 samples/sec accuracy=54.125000 loss=1.899864 lr=0.009997 Epoch[001] Batch [0099]/[3760] Speed: 94.287002 samples/sec accuracy=53.625000 loss=1.921193 lr=0.009997 Epoch[001] Batch [0149]/[3760] Speed: 94.008802 samples/sec accuracy=52.750000 loss=1.953506 lr=0.009997 Epoch[001] Batch [0199]/[3760] Speed: 94.265685 samples/sec accuracy=52.609375 loss=1.961920 lr=0.009997 Epoch[001] Batch [0249]/[3760] Speed: 94.348767 samples/sec accuracy=53.006250 loss=1.946776 lr=0.009997 Epoch[001] 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accuracy=54.204861 loss=1.895333 lr=0.009991 Epoch[001] Batch [3649]/[3760] Speed: 94.448060 samples/sec accuracy=54.223887 loss=1.894792 lr=0.009990 Epoch[001] Batch [3699]/[3760] Speed: 93.658277 samples/sec accuracy=54.258024 loss=1.893670 lr=0.009990 Epoch[001] Batch [3749]/[3760] Speed: 105.907441 samples/sec accuracy=54.257083 loss=1.893690 lr=0.009990 Batch [0049]/[0303]: acc-top1=54.218750 acc-top5=77.468750 Batch [0099]/[0303]: acc-top1=51.875000 acc-top5=77.171875 Batch [0149]/[0303]: acc-top1=53.083333 acc-top5=77.885417 Batch [0199]/[0303]: acc-top1=56.312500 acc-top5=79.648438 Batch [0249]/[0303]: acc-top1=55.568750 acc-top5=79.387500 Batch [0299]/[0303]: acc-top1=54.963542 acc-top5=79.645833 [Epoch 001] training: accuracy=54.256981 loss=1.893522 [Epoch 001] speed: 93 samples/sec time cost: 2785.957448 [Epoch 001] validation: acc-top1=54.888614 acc-top5=79.620462 loss=2.210915 Epoch[002] Batch [0049]/[3759] Speed: 64.827926 samples/sec accuracy=59.031250 loss=1.688074 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acc-top1=58.203125 acc-top5=81.343750 Batch [0249]/[0303]: acc-top1=57.200000 acc-top5=80.956250 Batch [0299]/[0303]: acc-top1=56.515625 acc-top5=80.968750 [Epoch 002] training: accuracy=58.611832 loss=1.683031 [Epoch 002] speed: 93 samples/sec time cost: 2787.783891 [Epoch 002] validation: acc-top1=56.605817 acc-top5=81.017946 loss=2.125291 Epoch[003] Batch [0049]/[3760] Speed: 64.745761 samples/sec accuracy=62.500000 loss=1.517200 lr=0.009978 Epoch[003] Batch [0099]/[3760] Speed: 94.327552 samples/sec accuracy=62.703125 loss=1.501074 lr=0.009977 Epoch[003] Batch [0149]/[3760] Speed: 94.411240 samples/sec accuracy=62.625000 loss=1.503183 lr=0.009977 Epoch[003] Batch [0199]/[3760] Speed: 93.975404 samples/sec accuracy=62.335938 loss=1.513354 lr=0.009977 Epoch[003] Batch [0249]/[3760] Speed: 93.190426 samples/sec accuracy=62.243750 loss=1.505936 lr=0.009977 Epoch[003] Batch [0299]/[3760] Speed: 94.575730 samples/sec accuracy=62.010417 loss=1.516948 lr=0.009977 Epoch[003] Batch 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accuracy=61.351027 loss=1.556125 lr=0.009961 Epoch[003] Batch [3699]/[3760] Speed: 94.568107 samples/sec accuracy=61.347128 loss=1.556481 lr=0.009961 Epoch[003] Batch [3749]/[3760] Speed: 106.713544 samples/sec accuracy=61.342917 loss=1.556810 lr=0.009961 Batch [0049]/[0303]: acc-top1=60.093750 acc-top5=83.312500 Batch [0099]/[0303]: acc-top1=56.031250 acc-top5=81.250000 Batch [0149]/[0303]: acc-top1=57.052083 acc-top5=81.593750 Batch [0199]/[0303]: acc-top1=59.906250 acc-top5=83.132812 Batch [0249]/[0303]: acc-top1=59.287500 acc-top5=82.518750 Batch [0299]/[0303]: acc-top1=58.666667 acc-top5=82.406250 [Epoch 003] training: accuracy=61.333943 loss=1.557167 [Epoch 003] speed: 93 samples/sec time cost: 2790.642871 [Epoch 003] validation: acc-top1=58.580858 acc-top5=82.425743 loss=2.017428 Epoch[004] Batch [0049]/[3760] Speed: 64.852479 samples/sec accuracy=63.687500 loss=1.427663 lr=0.009960 Epoch[004] Batch [0099]/[3760] Speed: 93.734614 samples/sec accuracy=63.218750 loss=1.455735 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lr=0.009944 Epoch[004] Batch [2999]/[3760] Speed: 93.897790 samples/sec accuracy=63.375000 loss=1.458314 lr=0.009943 Epoch[004] Batch [3049]/[3760] Speed: 94.354990 samples/sec accuracy=63.360143 loss=1.458856 lr=0.009943 Epoch[004] Batch [3099]/[3760] Speed: 93.247403 samples/sec accuracy=63.377520 loss=1.458469 lr=0.009943 Epoch[004] Batch [3149]/[3760] Speed: 94.254653 samples/sec accuracy=63.380952 loss=1.458807 lr=0.009942 Epoch[004] Batch [3199]/[3760] Speed: 93.942100 samples/sec accuracy=63.380371 loss=1.459060 lr=0.009942 Epoch[004] Batch [3249]/[3760] Speed: 93.947129 samples/sec accuracy=63.406731 loss=1.458497 lr=0.009942 Epoch[004] Batch [3299]/[3760] Speed: 94.308744 samples/sec accuracy=63.426136 loss=1.457553 lr=0.009941 Epoch[004] Batch [3349]/[3760] Speed: 93.954356 samples/sec accuracy=63.428638 loss=1.457746 lr=0.009941 Epoch[004] Batch [3399]/[3760] Speed: 93.307998 samples/sec accuracy=63.424173 loss=1.457709 lr=0.009941 Epoch[004] Batch [3449]/[3760] Speed: 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[0299]/[0303]: acc-top1=60.046875 acc-top5=82.937500 [Epoch 004] training: accuracy=63.419631 loss=1.459719 [Epoch 004] speed: 93 samples/sec time cost: 2791.024172 [Epoch 004] validation: acc-top1=60.024752 acc-top5=82.936262 loss=2.057658 Epoch[005] Batch [0049]/[3759] Speed: 64.393407 samples/sec accuracy=65.875000 loss=1.348084 lr=0.009938 Epoch[005] Batch [0099]/[3759] Speed: 94.064342 samples/sec accuracy=65.312500 loss=1.354157 lr=0.009938 Epoch[005] Batch [0149]/[3759] Speed: 93.312012 samples/sec accuracy=65.052083 loss=1.365726 lr=0.009937 Epoch[005] Batch [0199]/[3759] Speed: 94.534139 samples/sec accuracy=65.390625 loss=1.354027 lr=0.009937 Epoch[005] Batch [0249]/[3759] Speed: 93.657348 samples/sec accuracy=65.625000 loss=1.350282 lr=0.009937 Epoch[005] Batch [0299]/[3759] Speed: 93.540884 samples/sec accuracy=65.953125 loss=1.337841 lr=0.009936 Epoch[005] Batch [0349]/[3759] Speed: 94.647196 samples/sec accuracy=65.883929 loss=1.339408 lr=0.009936 Epoch[005] Batch 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accuracy=64.980574 loss=1.384873 lr=0.009912 Epoch[005] Batch [3749]/[3759] Speed: 106.479948 samples/sec accuracy=64.972500 loss=1.385507 lr=0.009911 Batch [0049]/[0303]: acc-top1=61.093750 acc-top5=82.781250 Batch [0099]/[0303]: acc-top1=58.562500 acc-top5=82.125000 Batch [0149]/[0303]: acc-top1=59.906250 acc-top5=82.666667 Batch [0199]/[0303]: acc-top1=62.554687 acc-top5=84.210938 Batch [0249]/[0303]: acc-top1=61.881250 acc-top5=83.875000 Batch [0299]/[0303]: acc-top1=61.036458 acc-top5=83.776042 [Epoch 005] training: accuracy=64.976141 loss=1.385575 [Epoch 005] speed: 93 samples/sec time cost: 2792.551868 [Epoch 005] validation: acc-top1=60.983911 acc-top5=83.771658 loss=2.010255 Epoch[006] Batch [0049]/[3760] Speed: 65.077903 samples/sec accuracy=68.000000 loss=1.228475 lr=0.009911 Epoch[006] Batch [0099]/[3760] Speed: 94.065701 samples/sec accuracy=67.859375 loss=1.252749 lr=0.009911 Epoch[006] Batch [0149]/[3760] Speed: 93.425864 samples/sec accuracy=67.843750 loss=1.252150 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lr=0.009895 Epoch[006] Batch [2099]/[3760] Speed: 94.252537 samples/sec accuracy=66.636905 loss=1.311750 lr=0.009894 Epoch[006] Batch [2149]/[3760] Speed: 92.965709 samples/sec accuracy=66.603924 loss=1.312218 lr=0.009894 Epoch[006] Batch [2199]/[3760] Speed: 93.815255 samples/sec accuracy=66.594460 loss=1.312150 lr=0.009893 Epoch[006] Batch [2249]/[3760] Speed: 94.148872 samples/sec accuracy=66.588889 loss=1.311585 lr=0.009893 Epoch[006] Batch [2299]/[3760] Speed: 94.480040 samples/sec accuracy=66.585598 loss=1.312278 lr=0.009892 Epoch[006] Batch [2349]/[3760] Speed: 92.847484 samples/sec accuracy=66.548537 loss=1.313783 lr=0.009892 Epoch[006] Batch [2399]/[3760] Speed: 93.921459 samples/sec accuracy=66.541016 loss=1.314479 lr=0.009892 Epoch[006] Batch [2449]/[3760] Speed: 94.046271 samples/sec accuracy=66.509566 loss=1.314988 lr=0.009891 Epoch[006] Batch [2499]/[3760] Speed: 93.622635 samples/sec accuracy=66.493125 loss=1.315680 lr=0.009891 Epoch[006] Batch [2549]/[3760] Speed: 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lr=0.009886 Epoch[006] Batch [3049]/[3760] Speed: 94.753300 samples/sec accuracy=66.431865 loss=1.319540 lr=0.009886 Epoch[006] Batch [3099]/[3760] Speed: 93.911344 samples/sec accuracy=66.401714 loss=1.320781 lr=0.009885 Epoch[006] Batch [3149]/[3760] Speed: 93.516759 samples/sec accuracy=66.386409 loss=1.321489 lr=0.009885 Epoch[006] Batch [3199]/[3760] Speed: 93.949050 samples/sec accuracy=66.338379 loss=1.322674 lr=0.009885 Epoch[006] Batch [3249]/[3760] Speed: 93.746840 samples/sec accuracy=66.328846 loss=1.323012 lr=0.009884 Epoch[006] Batch [3299]/[3760] Speed: 94.308661 samples/sec accuracy=66.341383 loss=1.322709 lr=0.009884 Epoch[006] Batch [3349]/[3760] Speed: 94.021091 samples/sec accuracy=66.317164 loss=1.323981 lr=0.009883 Epoch[006] Batch [3399]/[3760] Speed: 93.560120 samples/sec accuracy=66.298254 loss=1.324621 lr=0.009883 Epoch[006] Batch [3449]/[3760] Speed: 94.048780 samples/sec accuracy=66.281250 loss=1.325806 lr=0.009882 Epoch[006] Batch [3499]/[3760] Speed: 93.857129 samples/sec accuracy=66.265179 loss=1.326138 lr=0.009882 Epoch[006] Batch [3549]/[3760] Speed: 94.193194 samples/sec accuracy=66.261884 loss=1.326413 lr=0.009881 Epoch[006] Batch [3599]/[3760] Speed: 94.298263 samples/sec accuracy=66.237413 loss=1.327304 lr=0.009881 Epoch[006] Batch [3649]/[3760] Speed: 93.653977 samples/sec accuracy=66.233305 loss=1.327547 lr=0.009881 Epoch[006] Batch [3699]/[3760] Speed: 94.118836 samples/sec accuracy=66.243666 loss=1.327087 lr=0.009880 Epoch[006] Batch [3749]/[3760] Speed: 106.228794 samples/sec accuracy=66.227083 loss=1.327797 lr=0.009880 Batch [0049]/[0303]: acc-top1=61.500000 acc-top5=83.906250 Batch [0099]/[0303]: acc-top1=59.468750 acc-top5=82.593750 Batch [0149]/[0303]: acc-top1=60.458333 acc-top5=83.427083 Batch [0199]/[0303]: acc-top1=63.328125 acc-top5=84.765625 Batch [0249]/[0303]: acc-top1=62.712500 acc-top5=84.475000 Batch [0299]/[0303]: acc-top1=61.578125 acc-top5=84.296875 [Epoch 006] training: accuracy=66.220080 loss=1.328139 [Epoch 006] speed: 93 samples/sec time cost: 2790.934378 [Epoch 006] validation: acc-top1=61.535685 acc-top5=84.302805 loss=2.042254 Epoch[007] Batch [0049]/[3760] Speed: 64.312219 samples/sec accuracy=69.468750 loss=1.221242 lr=0.009879 Epoch[007] Batch [0099]/[3760] Speed: 93.559205 samples/sec accuracy=69.328125 loss=1.208195 lr=0.009879 Epoch[007] Batch [0149]/[3760] Speed: 94.398473 samples/sec accuracy=69.166667 loss=1.200542 lr=0.009878 Epoch[007] Batch [0199]/[3760] Speed: 93.136591 samples/sec accuracy=69.046875 loss=1.208595 lr=0.009878 Epoch[007] Batch [0249]/[3760] Speed: 93.874847 samples/sec accuracy=69.031250 loss=1.208385 lr=0.009877 Epoch[007] Batch [0299]/[3760] Speed: 93.512770 samples/sec accuracy=68.932292 loss=1.213401 lr=0.009877 Epoch[007] Batch [0349]/[3760] Speed: 93.578065 samples/sec accuracy=68.821429 loss=1.214139 lr=0.009876 Epoch[007] Batch [0399]/[3760] Speed: 94.181368 samples/sec accuracy=68.457031 loss=1.229660 lr=0.009876 Epoch[007] 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accuracy=68.032986 loss=1.241933 lr=0.009871 Epoch[007] Batch [0949]/[3760] Speed: 93.826147 samples/sec accuracy=67.960526 loss=1.246222 lr=0.009871 Epoch[007] Batch [0999]/[3760] Speed: 93.555735 samples/sec accuracy=67.971875 loss=1.247507 lr=0.009870 Epoch[007] Batch [1049]/[3760] Speed: 93.620953 samples/sec accuracy=68.023810 loss=1.246065 lr=0.009870 Epoch[007] Batch [1099]/[3760] Speed: 93.549342 samples/sec accuracy=68.052557 loss=1.243912 lr=0.009869 Epoch[007] Batch [1149]/[3760] Speed: 93.415040 samples/sec accuracy=68.033967 loss=1.245544 lr=0.009869 Epoch[007] Batch [1199]/[3760] Speed: 94.130897 samples/sec accuracy=67.983073 loss=1.248617 lr=0.009868 Epoch[007] Batch [1249]/[3760] Speed: 93.403335 samples/sec accuracy=67.985000 loss=1.249818 lr=0.009868 Epoch[007] Batch [1299]/[3760] Speed: 93.003859 samples/sec accuracy=67.989183 loss=1.248800 lr=0.009867 Epoch[007] Batch [1349]/[3760] Speed: 94.151477 samples/sec accuracy=67.929398 loss=1.250971 lr=0.009867 Epoch[007] 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accuracy=67.916385 loss=1.253487 lr=0.009862 Epoch[007] Batch [1899]/[3760] Speed: 94.184274 samples/sec accuracy=67.902138 loss=1.253917 lr=0.009862 Epoch[007] Batch [1949]/[3760] Speed: 93.869680 samples/sec accuracy=67.892628 loss=1.254787 lr=0.009861 Epoch[007] Batch [1999]/[3760] Speed: 93.837544 samples/sec accuracy=67.896094 loss=1.255055 lr=0.009861 Epoch[007] Batch [2049]/[3760] Speed: 93.483685 samples/sec accuracy=67.886433 loss=1.255702 lr=0.009860 Epoch[007] Batch [2099]/[3760] Speed: 92.970107 samples/sec accuracy=67.843750 loss=1.256812 lr=0.009860 Epoch[007] Batch [2149]/[3760] Speed: 93.633171 samples/sec accuracy=67.844477 loss=1.256948 lr=0.009859 Epoch[007] Batch [2199]/[3760] Speed: 94.666567 samples/sec accuracy=67.846591 loss=1.257538 lr=0.009859 Epoch[007] Batch [2249]/[3760] Speed: 93.593233 samples/sec accuracy=67.825694 loss=1.258273 lr=0.009858 Epoch[007] Batch [2299]/[3760] Speed: 94.347655 samples/sec accuracy=67.825408 loss=1.257802 lr=0.009858 Epoch[007] 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accuracy=67.729911 loss=1.264744 lr=0.009853 Epoch[007] Batch [2849]/[3760] Speed: 94.184630 samples/sec accuracy=67.742873 loss=1.264967 lr=0.009852 Epoch[007] Batch [2899]/[3760] Speed: 93.395306 samples/sec accuracy=67.726832 loss=1.265290 lr=0.009852 Epoch[007] Batch [2949]/[3760] Speed: 93.319981 samples/sec accuracy=67.708157 loss=1.266269 lr=0.009851 Epoch[007] Batch [2999]/[3760] Speed: 93.879718 samples/sec accuracy=67.693750 loss=1.266558 lr=0.009851 Epoch[007] Batch [3049]/[3760] Speed: 94.152456 samples/sec accuracy=67.673156 loss=1.268043 lr=0.009850 Epoch[007] Batch [3099]/[3760] Speed: 93.981797 samples/sec accuracy=67.648185 loss=1.268517 lr=0.009850 Epoch[007] Batch [3149]/[3760] Speed: 93.422838 samples/sec accuracy=67.635913 loss=1.269131 lr=0.009849 Epoch[007] Batch [3199]/[3760] Speed: 94.180941 samples/sec accuracy=67.626953 loss=1.269231 lr=0.009849 Epoch[007] Batch [3249]/[3760] Speed: 93.308418 samples/sec accuracy=67.623558 loss=1.269616 lr=0.009848 Epoch[007] 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accuracy=67.544167 loss=1.272444 lr=0.009843 Batch [0049]/[0303]: acc-top1=61.500000 acc-top5=83.000000 Batch [0099]/[0303]: acc-top1=59.015625 acc-top5=82.546875 Batch [0149]/[0303]: acc-top1=59.895833 acc-top5=83.083333 Batch [0199]/[0303]: acc-top1=62.804688 acc-top5=84.570312 Batch [0249]/[0303]: acc-top1=62.168750 acc-top5=84.218750 Batch [0299]/[0303]: acc-top1=61.635417 acc-top5=84.177083 [Epoch 007] training: accuracy=67.535738 loss=1.272661 [Epoch 007] speed: 93 samples/sec time cost: 2793.707372 [Epoch 007] validation: acc-top1=61.654290 acc-top5=84.179043 loss=2.008449 Epoch[008] Batch [0049]/[3759] Speed: 64.494916 samples/sec accuracy=69.687500 loss=1.147776 lr=0.009842 Epoch[008] Batch [0099]/[3759] Speed: 93.841518 samples/sec accuracy=69.687500 loss=1.156579 lr=0.009842 Epoch[008] Batch [0149]/[3759] Speed: 94.072390 samples/sec accuracy=69.552083 loss=1.166413 lr=0.009841 Epoch[008] Batch [0199]/[3759] Speed: 94.237493 samples/sec accuracy=69.687500 loss=1.176209 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lr=0.009831 Epoch[008] Batch [1199]/[3759] Speed: 94.373473 samples/sec accuracy=68.824219 loss=1.210119 lr=0.009830 Epoch[008] Batch [1249]/[3759] Speed: 93.267906 samples/sec accuracy=68.787500 loss=1.210838 lr=0.009830 Epoch[008] Batch [1299]/[3759] Speed: 93.952125 samples/sec accuracy=68.784856 loss=1.210017 lr=0.009829 Epoch[008] Batch [1349]/[3759] Speed: 94.094156 samples/sec accuracy=68.793981 loss=1.209887 lr=0.009829 Epoch[008] Batch [1399]/[3759] Speed: 94.253402 samples/sec accuracy=68.787946 loss=1.210048 lr=0.009828 Epoch[008] Batch [1449]/[3759] Speed: 92.891960 samples/sec accuracy=68.812500 loss=1.208963 lr=0.009827 Epoch[008] Batch [1499]/[3759] Speed: 93.660308 samples/sec accuracy=68.773958 loss=1.209421 lr=0.009827 Epoch[008] Batch [1549]/[3759] Speed: 94.170496 samples/sec accuracy=68.750000 loss=1.209862 lr=0.009826 Epoch[008] Batch [1599]/[3759] Speed: 93.604379 samples/sec accuracy=68.754883 loss=1.209812 lr=0.009826 Epoch[008] Batch [1649]/[3759] Speed: 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lr=0.009820 Epoch[008] Batch [2149]/[3759] Speed: 93.709102 samples/sec accuracy=68.601744 loss=1.219454 lr=0.009820 Epoch[008] Batch [2199]/[3759] Speed: 94.364637 samples/sec accuracy=68.615767 loss=1.218815 lr=0.009819 Epoch[008] Batch [2249]/[3759] Speed: 93.987092 samples/sec accuracy=68.607639 loss=1.219247 lr=0.009819 Epoch[008] Batch [2299]/[3759] Speed: 93.764249 samples/sec accuracy=68.608696 loss=1.219456 lr=0.009818 Epoch[008] Batch [2349]/[3759] Speed: 94.486993 samples/sec accuracy=68.604388 loss=1.219910 lr=0.009818 Epoch[008] Batch [2399]/[3759] Speed: 94.358747 samples/sec accuracy=68.604818 loss=1.220304 lr=0.009817 Epoch[008] Batch [2449]/[3759] Speed: 93.900819 samples/sec accuracy=68.596301 loss=1.220904 lr=0.009816 Epoch[008] Batch [2499]/[3759] Speed: 92.740334 samples/sec accuracy=68.602500 loss=1.221153 lr=0.009816 Epoch[008] Batch [2549]/[3759] Speed: 94.243832 samples/sec accuracy=68.601716 loss=1.221301 lr=0.009815 Epoch[008] Batch [2599]/[3759] Speed: 94.440100 samples/sec accuracy=68.608173 loss=1.221556 lr=0.009815 Epoch[008] Batch [2649]/[3759] Speed: 93.485886 samples/sec accuracy=68.621462 loss=1.221197 lr=0.009814 Epoch[008] Batch [2699]/[3759] Speed: 94.226677 samples/sec accuracy=68.600694 loss=1.222098 lr=0.009814 Epoch[008] Batch [2749]/[3759] Speed: 93.612907 samples/sec accuracy=68.594318 loss=1.222416 lr=0.009813 Epoch[008] Batch [2799]/[3759] Speed: 93.733698 samples/sec accuracy=68.590402 loss=1.222815 lr=0.009812 Epoch[008] Batch [2849]/[3759] Speed: 94.077686 samples/sec accuracy=68.548794 loss=1.224209 lr=0.009812 Epoch[008] Batch [2899]/[3759] Speed: 93.647123 samples/sec accuracy=68.536099 loss=1.224695 lr=0.009811 Epoch[008] Batch [2949]/[3759] Speed: 93.703891 samples/sec accuracy=68.529131 loss=1.225502 lr=0.009811 Epoch[008] Batch [2999]/[3759] Speed: 94.359004 samples/sec accuracy=68.516146 loss=1.226114 lr=0.009810 Epoch[008] Batch [3049]/[3759] Speed: 93.048823 samples/sec accuracy=68.502049 loss=1.226756 lr=0.009810 Epoch[008] Batch [3099]/[3759] Speed: 94.187926 samples/sec accuracy=68.512097 loss=1.226700 lr=0.009809 Epoch[008] Batch [3149]/[3759] Speed: 94.041779 samples/sec accuracy=68.502480 loss=1.227112 lr=0.009808 Epoch[008] Batch [3199]/[3759] Speed: 93.880489 samples/sec accuracy=68.507324 loss=1.227106 lr=0.009808 Epoch[008] Batch [3249]/[3759] Speed: 93.942822 samples/sec accuracy=68.482692 loss=1.227782 lr=0.009807 Epoch[008] Batch [3299]/[3759] Speed: 93.958146 samples/sec accuracy=68.471591 loss=1.228452 lr=0.009807 Epoch[008] Batch [3349]/[3759] Speed: 94.084637 samples/sec accuracy=68.451493 loss=1.229533 lr=0.009806 Epoch[008] Batch [3399]/[3759] Speed: 93.216578 samples/sec accuracy=68.425092 loss=1.230838 lr=0.009806 Epoch[008] Batch [3449]/[3759] Speed: 93.763126 samples/sec accuracy=68.428442 loss=1.230594 lr=0.009805 Epoch[008] Batch [3499]/[3759] Speed: 93.992588 samples/sec accuracy=68.418304 loss=1.230679 lr=0.009804 Epoch[008] Batch [3549]/[3759] Speed: 93.776128 samples/sec accuracy=68.402289 loss=1.231447 lr=0.009804 Epoch[008] Batch [3599]/[3759] Speed: 93.773954 samples/sec accuracy=68.384115 loss=1.232281 lr=0.009803 Epoch[008] Batch [3649]/[3759] Speed: 93.043316 samples/sec accuracy=68.373716 loss=1.233044 lr=0.009803 Epoch[008] Batch [3699]/[3759] Speed: 94.322056 samples/sec accuracy=68.353041 loss=1.233676 lr=0.009802 Epoch[008] Batch [3749]/[3759] Speed: 106.556675 samples/sec accuracy=68.352917 loss=1.233918 lr=0.009802 Batch [0049]/[0303]: acc-top1=61.375000 acc-top5=83.906250 Batch [0099]/[0303]: acc-top1=59.093750 acc-top5=83.234375 Batch [0149]/[0303]: acc-top1=60.489583 acc-top5=83.666667 Batch [0199]/[0303]: acc-top1=63.250000 acc-top5=84.953125 Batch [0249]/[0303]: acc-top1=62.856250 acc-top5=84.612500 Batch [0299]/[0303]: acc-top1=62.291667 acc-top5=84.583333 [Epoch 008] training: accuracy=68.351373 loss=1.234192 [Epoch 008] speed: 93 samples/sec time cost: 2792.507376 [Epoch 008] validation: acc-top1=62.247318 acc-top5=84.565800 loss=1.928163 Epoch[009] Batch [0049]/[3760] Speed: 64.193093 samples/sec accuracy=70.687500 loss=1.128768 lr=0.009801 Epoch[009] Batch [0099]/[3760] Speed: 93.765486 samples/sec accuracy=71.046875 loss=1.121947 lr=0.009800 Epoch[009] Batch [0149]/[3760] Speed: 93.143075 samples/sec accuracy=70.895833 loss=1.124850 lr=0.009800 Epoch[009] Batch [0199]/[3760] Speed: 93.672670 samples/sec accuracy=71.117188 loss=1.127635 lr=0.009799 Epoch[009] Batch [0249]/[3760] Speed: 94.398272 samples/sec accuracy=70.787500 loss=1.133072 lr=0.009798 Epoch[009] Batch [0299]/[3760] Speed: 94.060810 samples/sec accuracy=70.760417 loss=1.136855 lr=0.009798 Epoch[009] Batch [0349]/[3760] Speed: 93.895906 samples/sec accuracy=70.665179 loss=1.142825 lr=0.009797 Epoch[009] Batch [0399]/[3760] Speed: 94.225097 samples/sec accuracy=70.535156 loss=1.146516 lr=0.009797 Epoch[009] Batch [0449]/[3760] Speed: 93.300645 samples/sec accuracy=70.236111 loss=1.151032 lr=0.009796 Epoch[009] Batch 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accuracy=69.815789 loss=1.160276 lr=0.009790 Epoch[009] Batch [0999]/[3760] Speed: 93.281734 samples/sec accuracy=69.793750 loss=1.161564 lr=0.009790 Epoch[009] Batch [1049]/[3760] Speed: 94.508793 samples/sec accuracy=69.796131 loss=1.161569 lr=0.009789 Epoch[009] Batch [1099]/[3760] Speed: 93.284119 samples/sec accuracy=69.782670 loss=1.163023 lr=0.009788 Epoch[009] Batch [1149]/[3760] Speed: 94.121208 samples/sec accuracy=69.789402 loss=1.163379 lr=0.009788 Epoch[009] Batch [1199]/[3760] Speed: 93.892225 samples/sec accuracy=69.768229 loss=1.163978 lr=0.009787 Epoch[009] Batch [1249]/[3760] Speed: 93.405066 samples/sec accuracy=69.750000 loss=1.163261 lr=0.009787 Epoch[009] Batch [1299]/[3760] Speed: 93.404726 samples/sec accuracy=69.769231 loss=1.163465 lr=0.009786 Epoch[009] Batch [1349]/[3760] Speed: 93.395640 samples/sec accuracy=69.790509 loss=1.162683 lr=0.009785 Epoch[009] Batch [1399]/[3760] Speed: 93.811531 samples/sec accuracy=69.801339 loss=1.161741 lr=0.009785 Epoch[009] 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accuracy=69.513158 loss=1.180641 lr=0.009767 Epoch[009] Batch [2899]/[3760] Speed: 94.169127 samples/sec accuracy=69.507004 loss=1.181002 lr=0.009766 Epoch[009] Batch [2949]/[3760] Speed: 93.702631 samples/sec accuracy=69.485699 loss=1.181911 lr=0.009766 Epoch[009] Batch [2999]/[3760] Speed: 93.805081 samples/sec accuracy=69.483854 loss=1.181929 lr=0.009765 Epoch[009] Batch [3049]/[3760] Speed: 93.879160 samples/sec accuracy=69.477971 loss=1.182215 lr=0.009764 Epoch[009] Batch [3099]/[3760] Speed: 93.992767 samples/sec accuracy=69.477319 loss=1.182701 lr=0.009764 Epoch[009] Batch [3149]/[3760] Speed: 93.356628 samples/sec accuracy=69.458829 loss=1.183932 lr=0.009763 Epoch[009] Batch [3199]/[3760] Speed: 93.843605 samples/sec accuracy=69.461426 loss=1.184199 lr=0.009762 Epoch[009] Batch [3249]/[3760] Speed: 93.413417 samples/sec accuracy=69.448558 loss=1.184941 lr=0.009762 Epoch[009] Batch [3299]/[3760] Speed: 94.352598 samples/sec accuracy=69.455492 loss=1.184964 lr=0.009761 Epoch[009] 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[0099]/[0303]: acc-top1=59.484375 acc-top5=83.468750 Batch [0149]/[0303]: acc-top1=61.447917 acc-top5=83.666667 Batch [0199]/[0303]: acc-top1=64.031250 acc-top5=85.132812 Batch [0249]/[0303]: acc-top1=63.431250 acc-top5=84.756250 Batch [0299]/[0303]: acc-top1=63.098958 acc-top5=84.838542 [Epoch 009] training: accuracy=69.429854 loss=1.188744 [Epoch 009] speed: 93 samples/sec time cost: 2792.454662 [Epoch 009] validation: acc-top1=63.041460 acc-top5=84.777228 loss=1.964366 Epoch[010] Batch [0049]/[3760] Speed: 64.489991 samples/sec accuracy=70.531250 loss=1.143846 lr=0.009755 Epoch[010] Batch [0099]/[3760] Speed: 92.882709 samples/sec accuracy=70.609375 loss=1.129869 lr=0.009754 Epoch[010] Batch [0149]/[3760] Speed: 93.843270 samples/sec accuracy=70.364583 loss=1.134199 lr=0.009753 Epoch[010] Batch [0199]/[3760] Speed: 94.152515 samples/sec accuracy=70.554688 loss=1.127314 lr=0.009753 Epoch[010] Batch [0249]/[3760] Speed: 93.429378 samples/sec accuracy=70.906250 loss=1.117342 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lr=0.009727 Epoch[010] Batch [2199]/[3760] Speed: 93.624138 samples/sec accuracy=70.379261 loss=1.138280 lr=0.009726 Epoch[010] Batch [2249]/[3760] Speed: 93.649140 samples/sec accuracy=70.365278 loss=1.139001 lr=0.009725 Epoch[010] Batch [2299]/[3760] Speed: 93.067041 samples/sec accuracy=70.355299 loss=1.139275 lr=0.009725 Epoch[010] Batch [2349]/[3760] Speed: 93.760981 samples/sec accuracy=70.344415 loss=1.140203 lr=0.009724 Epoch[010] Batch [2399]/[3760] Speed: 94.558409 samples/sec accuracy=70.326823 loss=1.141112 lr=0.009723 Epoch[010] Batch [2449]/[3760] Speed: 94.217759 samples/sec accuracy=70.319515 loss=1.141500 lr=0.009723 Epoch[010] Batch [2499]/[3760] Speed: 94.166274 samples/sec accuracy=70.317500 loss=1.142325 lr=0.009722 Epoch[010] Batch [2549]/[3760] Speed: 93.705754 samples/sec accuracy=70.290441 loss=1.142913 lr=0.009721 Epoch[010] Batch [2599]/[3760] Speed: 93.537723 samples/sec accuracy=70.272837 loss=1.143924 lr=0.009721 Epoch[010] Batch [2649]/[3760] Speed: 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lr=0.009714 Epoch[010] Batch [3149]/[3760] Speed: 94.143737 samples/sec accuracy=70.095734 loss=1.152338 lr=0.009713 Epoch[010] Batch [3199]/[3760] Speed: 93.329081 samples/sec accuracy=70.077637 loss=1.152889 lr=0.009712 Epoch[010] Batch [3249]/[3760] Speed: 93.921735 samples/sec accuracy=70.070673 loss=1.153499 lr=0.009711 Epoch[010] Batch [3299]/[3760] Speed: 93.446543 samples/sec accuracy=70.073864 loss=1.153388 lr=0.009711 Epoch[010] Batch [3349]/[3760] Speed: 94.098829 samples/sec accuracy=70.062966 loss=1.153986 lr=0.009710 Epoch[010] Batch [3399]/[3760] Speed: 94.113479 samples/sec accuracy=70.034926 loss=1.155100 lr=0.009709 Epoch[010] Batch [3449]/[3760] Speed: 93.520465 samples/sec accuracy=70.032609 loss=1.155240 lr=0.009709 Epoch[010] Batch [3499]/[3760] Speed: 94.050975 samples/sec accuracy=70.036161 loss=1.155368 lr=0.009708 Epoch[010] Batch [3549]/[3760] Speed: 94.769515 samples/sec accuracy=70.015845 loss=1.155884 lr=0.009707 Epoch[010] Batch [3599]/[3760] Speed: 93.313283 samples/sec accuracy=70.006076 loss=1.156433 lr=0.009707 Epoch[010] Batch [3649]/[3760] Speed: 93.866974 samples/sec accuracy=70.000428 loss=1.156502 lr=0.009706 Epoch[010] Batch [3699]/[3760] Speed: 93.685234 samples/sec accuracy=69.975929 loss=1.157830 lr=0.009705 Epoch[010] Batch [3749]/[3760] Speed: 106.448900 samples/sec accuracy=69.967500 loss=1.158484 lr=0.009704 Batch [0049]/[0303]: acc-top1=60.312500 acc-top5=83.062500 Batch [0099]/[0303]: acc-top1=58.421875 acc-top5=82.968750 Batch [0149]/[0303]: acc-top1=60.052083 acc-top5=83.531250 Batch [0199]/[0303]: acc-top1=63.242188 acc-top5=85.000000 Batch [0249]/[0303]: acc-top1=62.631250 acc-top5=84.618750 Batch [0299]/[0303]: acc-top1=61.927083 acc-top5=84.713542 [Epoch 010] training: accuracy=69.965509 loss=1.158539 [Epoch 010] speed: 93 samples/sec time cost: 2793.892531 [Epoch 010] validation: acc-top1=61.865718 acc-top5=84.684406 loss=2.084426 Epoch[011] Batch [0049]/[3759] Speed: 65.037137 samples/sec accuracy=74.031250 loss=1.010577 lr=0.009704 Epoch[011] Batch [0099]/[3759] Speed: 93.275416 samples/sec accuracy=72.796875 loss=1.051133 lr=0.009703 Epoch[011] Batch [0149]/[3759] Speed: 93.744952 samples/sec accuracy=72.395833 loss=1.051237 lr=0.009702 Epoch[011] Batch [0199]/[3759] Speed: 93.634420 samples/sec accuracy=71.859375 loss=1.065661 lr=0.009701 Epoch[011] Batch [0249]/[3759] Speed: 94.128492 samples/sec accuracy=71.893750 loss=1.063115 lr=0.009701 Epoch[011] Batch [0299]/[3759] Speed: 93.219959 samples/sec accuracy=72.010417 loss=1.061546 lr=0.009700 Epoch[011] Batch [0349]/[3759] Speed: 93.941703 samples/sec accuracy=71.946429 loss=1.066605 lr=0.009699 Epoch[011] Batch [0399]/[3759] Speed: 93.541020 samples/sec accuracy=71.910156 loss=1.071017 lr=0.009699 Epoch[011] Batch [0449]/[3759] Speed: 95.194203 samples/sec accuracy=71.927083 loss=1.070441 lr=0.009698 Epoch[011] Batch [0499]/[3759] Speed: 94.241438 samples/sec accuracy=71.950000 loss=1.068551 lr=0.009697 Epoch[011] 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acc-top5=83.281250 Batch [0199]/[0303]: acc-top1=63.140625 acc-top5=84.507812 Batch [0249]/[0303]: acc-top1=62.362500 acc-top5=84.131250 Batch [0299]/[0303]: acc-top1=61.718750 acc-top5=84.026042 [Epoch 011] training: accuracy=70.820032 loss=1.124994 [Epoch 011] speed: 93 samples/sec time cost: 2792.184529 [Epoch 011] validation: acc-top1=61.705858 acc-top5=84.024340 loss=2.069311 Epoch[012] Batch [0049]/[3760] Speed: 64.456070 samples/sec accuracy=72.062500 loss=1.075234 lr=0.009648 Epoch[012] Batch [0099]/[3760] Speed: 94.060197 samples/sec accuracy=72.687500 loss=1.057928 lr=0.009647 Epoch[012] Batch [0149]/[3760] Speed: 94.173819 samples/sec accuracy=72.645833 loss=1.046302 lr=0.009646 Epoch[012] Batch [0199]/[3760] Speed: 94.842865 samples/sec accuracy=72.343750 loss=1.045941 lr=0.009646 Epoch[012] Batch [0249]/[3760] Speed: 93.550420 samples/sec accuracy=72.512500 loss=1.040196 lr=0.009645 Epoch[012] Batch [0299]/[3760] Speed: 93.221438 samples/sec accuracy=72.286458 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accuracy=71.838778 loss=1.078960 lr=0.009614 Epoch[012] Batch [2249]/[3760] Speed: 93.780807 samples/sec accuracy=71.808333 loss=1.080264 lr=0.009613 Epoch[012] Batch [2299]/[3760] Speed: 93.659627 samples/sec accuracy=71.770380 loss=1.081958 lr=0.009613 Epoch[012] Batch [2349]/[3760] Speed: 93.825080 samples/sec accuracy=71.770612 loss=1.082353 lr=0.009612 Epoch[012] Batch [2399]/[3760] Speed: 93.650080 samples/sec accuracy=71.735026 loss=1.083123 lr=0.009611 Epoch[012] Batch [2449]/[3760] Speed: 93.039755 samples/sec accuracy=71.737245 loss=1.083089 lr=0.009610 Epoch[012] Batch [2499]/[3760] Speed: 93.927471 samples/sec accuracy=71.690625 loss=1.084745 lr=0.009609 Epoch[012] Batch [2549]/[3760] Speed: 94.144739 samples/sec accuracy=71.665441 loss=1.085078 lr=0.009608 Epoch[012] Batch [2599]/[3760] Speed: 93.455020 samples/sec accuracy=71.629207 loss=1.085793 lr=0.009608 Epoch[012] Batch [2649]/[3760] Speed: 94.153051 samples/sec accuracy=71.639741 loss=1.085714 lr=0.009607 Epoch[012] 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accuracy=71.524306 loss=1.092688 lr=0.009599 Epoch[012] Batch [3199]/[3760] Speed: 94.010421 samples/sec accuracy=71.525391 loss=1.092901 lr=0.009598 Epoch[012] Batch [3249]/[3760] Speed: 92.752730 samples/sec accuracy=71.499519 loss=1.093504 lr=0.009597 Epoch[012] Batch [3299]/[3760] Speed: 93.259016 samples/sec accuracy=71.484848 loss=1.093992 lr=0.009596 Epoch[012] Batch [3349]/[3760] Speed: 93.701677 samples/sec accuracy=71.479011 loss=1.094201 lr=0.009595 Epoch[012] Batch [3399]/[3760] Speed: 93.815986 samples/sec accuracy=71.476562 loss=1.094265 lr=0.009595 Epoch[012] Batch [3449]/[3760] Speed: 94.158090 samples/sec accuracy=71.473279 loss=1.094211 lr=0.009594 Epoch[012] Batch [3499]/[3760] Speed: 94.005473 samples/sec accuracy=71.441071 loss=1.095436 lr=0.009593 Epoch[012] Batch [3549]/[3760] Speed: 93.612187 samples/sec accuracy=71.441021 loss=1.095779 lr=0.009592 Epoch[012] Batch [3599]/[3760] Speed: 94.412592 samples/sec accuracy=71.420139 loss=1.097254 lr=0.009591 Epoch[012] 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lr=0.009530 Epoch[013] Batch [3449]/[3760] Speed: 93.935881 samples/sec accuracy=72.116395 loss=1.068614 lr=0.009529 Epoch[013] Batch [3499]/[3760] Speed: 93.665659 samples/sec accuracy=72.086161 loss=1.069559 lr=0.009529 Epoch[013] Batch [3549]/[3760] Speed: 93.631992 samples/sec accuracy=72.071743 loss=1.070161 lr=0.009528 Epoch[013] Batch [3599]/[3760] Speed: 93.772096 samples/sec accuracy=72.072049 loss=1.070577 lr=0.009527 Epoch[013] Batch [3649]/[3760] Speed: 94.642754 samples/sec accuracy=72.059932 loss=1.071041 lr=0.009526 Epoch[013] Batch [3699]/[3760] Speed: 93.400984 samples/sec accuracy=72.046453 loss=1.072071 lr=0.009525 Epoch[013] Batch [3749]/[3760] Speed: 106.092561 samples/sec accuracy=72.047917 loss=1.072503 lr=0.009524 Batch [0049]/[0303]: acc-top1=63.031250 acc-top5=84.156250 Batch [0099]/[0303]: acc-top1=59.812500 acc-top5=83.265625 Batch [0149]/[0303]: acc-top1=60.916667 acc-top5=83.875000 Batch [0199]/[0303]: acc-top1=63.851562 acc-top5=85.171875 Batch [0249]/[0303]: acc-top1=63.643750 acc-top5=84.900000 Batch [0299]/[0303]: acc-top1=62.963542 acc-top5=84.786458 [Epoch 013] training: accuracy=72.049950 loss=1.072316 [Epoch 013] speed: 93 samples/sec time cost: 2791.201826 [Epoch 013] validation: acc-top1=62.938325 acc-top5=84.787541 loss=2.093456 Epoch[014] Batch [0049]/[3759] Speed: 64.680591 samples/sec accuracy=74.125000 loss=0.983718 lr=0.009523 Epoch[014] Batch [0099]/[3759] Speed: 93.974139 samples/sec accuracy=73.921875 loss=0.976210 lr=0.009522 Epoch[014] Batch [0149]/[3759] Speed: 94.036080 samples/sec accuracy=73.666667 loss=0.981992 lr=0.009521 Epoch[014] Batch [0199]/[3759] Speed: 93.839212 samples/sec accuracy=73.640625 loss=0.990691 lr=0.009520 Epoch[014] Batch [0249]/[3759] Speed: 93.664795 samples/sec accuracy=73.712500 loss=0.990838 lr=0.009520 Epoch[014] Batch [0299]/[3759] Speed: 93.407206 samples/sec accuracy=73.734375 loss=0.995142 lr=0.009519 Epoch[014] Batch [0349]/[3759] Speed: 93.612283 samples/sec 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lr=0.009388 Epoch[015] Batch [3499]/[3760] Speed: 94.860868 samples/sec accuracy=73.029911 loss=1.027846 lr=0.009387 Epoch[015] Batch [3549]/[3760] Speed: 93.172927 samples/sec accuracy=73.036532 loss=1.027765 lr=0.009386 Epoch[015] Batch [3599]/[3760] Speed: 93.904320 samples/sec accuracy=73.018229 loss=1.028458 lr=0.009385 Epoch[015] Batch [3649]/[3760] Speed: 93.373234 samples/sec accuracy=72.998716 loss=1.029188 lr=0.009384 Epoch[015] Batch [3699]/[3760] Speed: 93.491448 samples/sec accuracy=73.008446 loss=1.029325 lr=0.009383 Epoch[015] Batch [3749]/[3760] Speed: 106.353357 samples/sec accuracy=73.007917 loss=1.029430 lr=0.009382 Batch [0049]/[0303]: acc-top1=62.500000 acc-top5=84.343750 Batch [0099]/[0303]: acc-top1=61.671875 acc-top5=84.281250 Batch [0149]/[0303]: acc-top1=62.593750 acc-top5=84.479167 Batch [0199]/[0303]: acc-top1=64.992188 acc-top5=85.734375 Batch [0249]/[0303]: acc-top1=64.200000 acc-top5=85.300000 Batch [0299]/[0303]: acc-top1=63.375000 acc-top5=85.380208 [Epoch 015] training: accuracy=73.006566 loss=1.029662 [Epoch 015] speed: 93 samples/sec time cost: 2793.611815 [Epoch 015] validation: acc-top1=63.330239 acc-top5=85.349629 loss=2.089359 Epoch[016] Batch [0049]/[3760] Speed: 64.530180 samples/sec accuracy=75.343750 loss=0.939999 lr=0.009380 Epoch[016] Batch [0099]/[3760] Speed: 93.717972 samples/sec accuracy=75.765625 loss=0.933298 lr=0.009379 Epoch[016] Batch [0149]/[3760] Speed: 94.347042 samples/sec accuracy=75.812500 loss=0.933273 lr=0.009378 Epoch[016] Batch [0199]/[3760] Speed: 93.034086 samples/sec accuracy=75.562500 loss=0.935465 lr=0.009377 Epoch[016] Batch [0249]/[3760] Speed: 93.597077 samples/sec accuracy=75.593750 loss=0.930746 lr=0.009376 Epoch[016] Batch [0299]/[3760] Speed: 93.637799 samples/sec accuracy=75.583333 loss=0.935542 lr=0.009375 Epoch[016] Batch [0349]/[3760] Speed: 93.987007 samples/sec accuracy=75.553571 loss=0.939906 lr=0.009374 Epoch[016] Batch [0399]/[3760] Speed: 93.942910 samples/sec accuracy=75.410156 loss=0.943731 lr=0.009373 Epoch[016] Batch [0449]/[3760] Speed: 93.895276 samples/sec accuracy=75.204861 loss=0.949805 lr=0.009372 Epoch[016] Batch [0499]/[3760] Speed: 93.799274 samples/sec accuracy=74.959375 loss=0.955359 lr=0.009371 Epoch[016] Batch [0549]/[3760] Speed: 93.669030 samples/sec accuracy=74.931818 loss=0.956457 lr=0.009370 Epoch[016] Batch [0599]/[3760] Speed: 93.648330 samples/sec accuracy=74.880208 loss=0.958853 lr=0.009369 Epoch[016] Batch [0649]/[3760] Speed: 93.767512 samples/sec accuracy=74.831731 loss=0.962284 lr=0.009368 Epoch[016] Batch [0699]/[3760] Speed: 94.427952 samples/sec accuracy=74.872768 loss=0.960319 lr=0.009367 Epoch[016] Batch [0749]/[3760] Speed: 93.169515 samples/sec accuracy=74.712500 loss=0.962815 lr=0.009366 Epoch[016] Batch [0799]/[3760] Speed: 94.670741 samples/sec accuracy=74.761719 loss=0.961613 lr=0.009365 Epoch[016] Batch [0849]/[3760] Speed: 93.074288 samples/sec accuracy=74.693015 loss=0.962423 lr=0.009364 Epoch[016] 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accuracy=74.337963 loss=0.977719 lr=0.009354 Epoch[016] Batch [1399]/[3760] Speed: 94.535838 samples/sec accuracy=74.361607 loss=0.977314 lr=0.009353 Epoch[016] Batch [1449]/[3760] Speed: 93.189579 samples/sec accuracy=74.348060 loss=0.978244 lr=0.009352 Epoch[016] Batch [1499]/[3760] Speed: 94.092676 samples/sec accuracy=74.263542 loss=0.982097 lr=0.009351 Epoch[016] Batch [1549]/[3760] Speed: 93.560557 samples/sec accuracy=74.223790 loss=0.983568 lr=0.009350 Epoch[016] Batch [1599]/[3760] Speed: 94.233323 samples/sec accuracy=74.195312 loss=0.984127 lr=0.009349 Epoch[016] Batch [1649]/[3760] Speed: 94.072751 samples/sec accuracy=74.198864 loss=0.983214 lr=0.009348 Epoch[016] Batch [1699]/[3760] Speed: 93.478459 samples/sec accuracy=74.180147 loss=0.983280 lr=0.009347 Epoch[016] Batch [1749]/[3760] Speed: 93.761070 samples/sec accuracy=74.164286 loss=0.984428 lr=0.009346 Epoch[016] Batch [1799]/[3760] Speed: 92.833979 samples/sec accuracy=74.114583 loss=0.986528 lr=0.009345 Epoch[016] 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accuracy=73.991848 loss=0.991827 lr=0.009334 Epoch[016] Batch [2349]/[3760] Speed: 93.804383 samples/sec accuracy=73.989362 loss=0.991394 lr=0.009333 Epoch[016] Batch [2399]/[3760] Speed: 94.480017 samples/sec accuracy=73.963542 loss=0.993000 lr=0.009332 Epoch[016] Batch [2449]/[3760] Speed: 93.885917 samples/sec accuracy=73.936862 loss=0.994196 lr=0.009331 Epoch[016] Batch [2499]/[3760] Speed: 93.621001 samples/sec accuracy=73.895000 loss=0.995345 lr=0.009330 Epoch[016] Batch [2549]/[3760] Speed: 94.042038 samples/sec accuracy=73.855392 loss=0.996752 lr=0.009329 Epoch[016] Batch [2599]/[3760] Speed: 93.562794 samples/sec accuracy=73.838942 loss=0.997704 lr=0.009328 Epoch[016] Batch [2649]/[3760] Speed: 94.183475 samples/sec accuracy=73.837264 loss=0.997657 lr=0.009327 Epoch[016] Batch [2699]/[3760] Speed: 94.000221 samples/sec accuracy=73.822917 loss=0.998157 lr=0.009326 Epoch[016] Batch [2749]/[3760] Speed: 93.547204 samples/sec accuracy=73.804545 loss=0.998966 lr=0.009325 Epoch[016] 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accuracy=73.643269 loss=1.004639 lr=0.009314 Epoch[016] Batch [3299]/[3760] Speed: 93.258475 samples/sec accuracy=73.631155 loss=1.005360 lr=0.009313 Epoch[016] Batch [3349]/[3760] Speed: 93.480570 samples/sec accuracy=73.623601 loss=1.005877 lr=0.009312 Epoch[016] Batch [3399]/[3760] Speed: 93.902562 samples/sec accuracy=73.607537 loss=1.006313 lr=0.009311 Epoch[016] Batch [3449]/[3760] Speed: 94.865635 samples/sec accuracy=73.592391 loss=1.006829 lr=0.009310 Epoch[016] Batch [3499]/[3760] Speed: 93.722558 samples/sec accuracy=73.579464 loss=1.007373 lr=0.009309 Epoch[016] Batch [3549]/[3760] Speed: 94.187239 samples/sec accuracy=73.583187 loss=1.007480 lr=0.009308 Epoch[016] Batch [3599]/[3760] Speed: 93.841751 samples/sec accuracy=73.576389 loss=1.008093 lr=0.009307 Epoch[016] Batch [3649]/[3760] Speed: 93.864419 samples/sec accuracy=73.569777 loss=1.008151 lr=0.009306 Epoch[016] Batch [3699]/[3760] Speed: 94.237860 samples/sec accuracy=73.552787 loss=1.008379 lr=0.009305 Epoch[016] Batch [3749]/[3760] Speed: 105.476410 samples/sec accuracy=73.533333 loss=1.009241 lr=0.009304 Batch [0049]/[0303]: acc-top1=63.156250 acc-top5=83.562500 Batch [0099]/[0303]: acc-top1=60.546875 acc-top5=83.640625 Batch [0149]/[0303]: acc-top1=61.656250 acc-top5=84.354167 Batch [0199]/[0303]: acc-top1=64.406250 acc-top5=85.492188 Batch [0249]/[0303]: acc-top1=63.825000 acc-top5=85.031250 Batch [0299]/[0303]: acc-top1=63.552083 acc-top5=85.177083 [Epoch 016] training: accuracy=73.533910 loss=1.009350 [Epoch 016] speed: 93 samples/sec time cost: 2792.902087 [Epoch 016] validation: acc-top1=63.639645 acc-top5=85.174299 loss=2.084832 Epoch[017] Batch [0049]/[3759] Speed: 64.510427 samples/sec accuracy=74.562500 loss=0.963154 lr=0.009302 Epoch[017] Batch [0099]/[3759] Speed: 94.349624 samples/sec accuracy=75.828125 loss=0.915632 lr=0.009301 Epoch[017] Batch [0149]/[3759] Speed: 93.923365 samples/sec accuracy=75.572917 loss=0.925885 lr=0.009300 Epoch[017] Batch [0199]/[3759] Speed: 93.437032 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lr=0.009248 Epoch[017] Batch [2599]/[3759] Speed: 93.347121 samples/sec accuracy=74.115385 loss=0.981332 lr=0.009247 Epoch[017] Batch [2649]/[3759] Speed: 93.929280 samples/sec accuracy=74.093160 loss=0.981744 lr=0.009246 Epoch[017] Batch [2699]/[3759] Speed: 94.629612 samples/sec accuracy=74.068287 loss=0.982567 lr=0.009245 Epoch[017] Batch [2749]/[3759] Speed: 92.977250 samples/sec accuracy=74.048295 loss=0.983444 lr=0.009244 Epoch[017] Batch [2799]/[3759] Speed: 94.200827 samples/sec accuracy=74.035714 loss=0.984282 lr=0.009243 Epoch[017] Batch [2849]/[3759] Speed: 93.135652 samples/sec accuracy=74.023026 loss=0.984779 lr=0.009242 Epoch[017] Batch [2899]/[3759] Speed: 93.773026 samples/sec accuracy=74.001078 loss=0.985390 lr=0.009241 Epoch[017] Batch [2949]/[3759] Speed: 94.019872 samples/sec accuracy=73.988347 loss=0.986006 lr=0.009239 Epoch[017] Batch [2999]/[3759] Speed: 94.071400 samples/sec accuracy=73.987500 loss=0.986114 lr=0.009238 Epoch[017] Batch [3049]/[3759] Speed: 93.753788 samples/sec accuracy=74.012807 loss=0.985881 lr=0.009237 Epoch[017] Batch [3099]/[3759] Speed: 94.237103 samples/sec accuracy=73.990423 loss=0.986671 lr=0.009236 Epoch[017] Batch [3149]/[3759] Speed: 93.707029 samples/sec accuracy=73.964782 loss=0.987420 lr=0.009235 Epoch[017] Batch [3199]/[3759] Speed: 94.748784 samples/sec accuracy=73.951172 loss=0.987773 lr=0.009234 Epoch[017] Batch [3249]/[3759] Speed: 94.828164 samples/sec accuracy=73.937981 loss=0.988662 lr=0.009233 Epoch[017] Batch [3299]/[3759] Speed: 93.606906 samples/sec accuracy=73.952178 loss=0.988491 lr=0.009232 Epoch[017] Batch [3349]/[3759] Speed: 93.948798 samples/sec accuracy=73.941231 loss=0.988991 lr=0.009231 Epoch[017] Batch [3399]/[3759] Speed: 93.120083 samples/sec accuracy=73.931985 loss=0.989397 lr=0.009229 Epoch[017] Batch [3449]/[3759] Speed: 94.651073 samples/sec accuracy=73.918025 loss=0.989589 lr=0.009228 Epoch[017] Batch [3499]/[3759] Speed: 94.451036 samples/sec accuracy=73.897768 loss=0.990171 lr=0.009227 Epoch[017] Batch [3549]/[3759] Speed: 93.988493 samples/sec accuracy=73.895246 loss=0.990184 lr=0.009226 Epoch[017] Batch [3599]/[3759] Speed: 93.504003 samples/sec accuracy=73.875434 loss=0.990774 lr=0.009225 Epoch[017] Batch [3649]/[3759] Speed: 94.144236 samples/sec accuracy=73.869863 loss=0.990854 lr=0.009224 Epoch[017] Batch [3699]/[3759] Speed: 93.887719 samples/sec accuracy=73.836571 loss=0.992058 lr=0.009223 Epoch[017] Batch [3749]/[3759] Speed: 106.252477 samples/sec accuracy=73.806667 loss=0.993240 lr=0.009222 Batch [0049]/[0303]: acc-top1=63.437500 acc-top5=83.750000 Batch [0099]/[0303]: acc-top1=60.421875 acc-top5=83.125000 Batch [0149]/[0303]: acc-top1=61.531250 acc-top5=83.708333 Batch [0199]/[0303]: acc-top1=64.570312 acc-top5=85.218750 Batch [0249]/[0303]: acc-top1=63.887500 acc-top5=84.825000 Batch [0299]/[0303]: acc-top1=63.005208 acc-top5=84.619792 [Epoch 017] training: accuracy=73.803704 loss=0.993313 [Epoch 017] speed: 93 samples/sec time cost: 2790.505432 [Epoch 017] validation: acc-top1=63.020833 acc-top5=84.622525 loss=2.073760 Epoch[018] Batch [0049]/[3760] Speed: 64.681748 samples/sec accuracy=75.156250 loss=0.923653 lr=0.009220 Epoch[018] Batch [0099]/[3760] Speed: 93.899835 samples/sec accuracy=75.390625 loss=0.920929 lr=0.009219 Epoch[018] Batch [0149]/[3760] Speed: 93.386059 samples/sec accuracy=75.312500 loss=0.918772 lr=0.009218 Epoch[018] Batch [0199]/[3760] Speed: 93.979223 samples/sec accuracy=75.359375 loss=0.911670 lr=0.009217 Epoch[018] Batch [0249]/[3760] Speed: 93.649870 samples/sec accuracy=75.150000 loss=0.920410 lr=0.009216 Epoch[018] Batch [0299]/[3760] Speed: 94.713701 samples/sec accuracy=75.098958 loss=0.927359 lr=0.009215 Epoch[018] Batch [0349]/[3760] Speed: 93.039278 samples/sec accuracy=75.276786 loss=0.922290 lr=0.009214 Epoch[018] Batch [0399]/[3760] Speed: 93.283002 samples/sec accuracy=75.414062 loss=0.915748 lr=0.009212 Epoch[018] Batch [0449]/[3760] Speed: 94.086752 samples/sec accuracy=75.309028 loss=0.920043 lr=0.009211 Epoch[018] Batch [0499]/[3760] Speed: 94.259269 samples/sec accuracy=75.353125 loss=0.915754 lr=0.009210 Epoch[018] Batch [0549]/[3760] Speed: 93.598423 samples/sec accuracy=75.298295 loss=0.919275 lr=0.009209 Epoch[018] Batch [0599]/[3760] Speed: 94.731686 samples/sec accuracy=75.302083 loss=0.918447 lr=0.009208 Epoch[018] Batch [0649]/[3760] Speed: 94.164556 samples/sec accuracy=75.341346 loss=0.917659 lr=0.009207 Epoch[018] Batch [0699]/[3760] Speed: 93.934385 samples/sec accuracy=75.343750 loss=0.919448 lr=0.009206 Epoch[018] Batch [0749]/[3760] Speed: 94.103885 samples/sec accuracy=75.364583 loss=0.920582 lr=0.009205 Epoch[018] Batch [0799]/[3760] Speed: 93.951089 samples/sec accuracy=75.408203 loss=0.919767 lr=0.009203 Epoch[018] Batch [0849]/[3760] Speed: 93.639227 samples/sec accuracy=75.341912 loss=0.921824 lr=0.009202 Epoch[018] Batch [0899]/[3760] Speed: 93.972257 samples/sec accuracy=75.359375 loss=0.922901 lr=0.009201 Epoch[018] 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accuracy=75.116071 loss=0.934731 lr=0.009190 Epoch[018] Batch [1449]/[3760] Speed: 93.400880 samples/sec accuracy=75.108836 loss=0.934678 lr=0.009189 Epoch[018] Batch [1499]/[3760] Speed: 94.431499 samples/sec accuracy=75.068750 loss=0.937094 lr=0.009187 Epoch[018] Batch [1549]/[3760] Speed: 93.958404 samples/sec accuracy=75.034274 loss=0.938213 lr=0.009186 Epoch[018] Batch [1599]/[3760] Speed: 93.006959 samples/sec accuracy=74.983398 loss=0.941219 lr=0.009185 Epoch[018] Batch [1649]/[3760] Speed: 93.766951 samples/sec accuracy=74.959280 loss=0.942622 lr=0.009184 Epoch[018] Batch [1699]/[3760] Speed: 94.250144 samples/sec accuracy=74.927390 loss=0.943880 lr=0.009183 Epoch[018] Batch [1749]/[3760] Speed: 92.751292 samples/sec accuracy=74.933929 loss=0.943757 lr=0.009182 Epoch[018] Batch [1799]/[3760] Speed: 94.484758 samples/sec accuracy=74.922743 loss=0.944664 lr=0.009181 Epoch[018] Batch [1849]/[3760] Speed: 93.331284 samples/sec accuracy=74.919764 loss=0.944513 lr=0.009179 Epoch[018] 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accuracy=74.739362 loss=0.956809 lr=0.009168 Epoch[018] Batch [2399]/[3760] Speed: 93.775972 samples/sec accuracy=74.713542 loss=0.957528 lr=0.009167 Epoch[018] Batch [2449]/[3760] Speed: 93.926321 samples/sec accuracy=74.688138 loss=0.958000 lr=0.009166 Epoch[018] Batch [2499]/[3760] Speed: 94.156282 samples/sec accuracy=74.658125 loss=0.959180 lr=0.009164 Epoch[018] Batch [2549]/[3760] Speed: 92.832114 samples/sec accuracy=74.606005 loss=0.961282 lr=0.009163 Epoch[018] Batch [2599]/[3760] Speed: 94.859861 samples/sec accuracy=74.604567 loss=0.961586 lr=0.009162 Epoch[018] Batch [2649]/[3760] Speed: 93.497186 samples/sec accuracy=74.586085 loss=0.962696 lr=0.009161 Epoch[018] Batch [2699]/[3760] Speed: 93.532725 samples/sec accuracy=74.564236 loss=0.963616 lr=0.009160 Epoch[018] Batch [2749]/[3760] Speed: 94.081980 samples/sec accuracy=74.545455 loss=0.964113 lr=0.009159 Epoch[018] Batch [2799]/[3760] Speed: 93.427695 samples/sec accuracy=74.524554 loss=0.964631 lr=0.009158 Epoch[018] 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accuracy=74.399148 loss=0.970343 lr=0.009146 Epoch[018] Batch [3349]/[3760] Speed: 93.610467 samples/sec accuracy=74.406250 loss=0.970541 lr=0.009145 Epoch[018] Batch [3399]/[3760] Speed: 93.694136 samples/sec accuracy=74.390165 loss=0.971713 lr=0.009144 Epoch[018] Batch [3449]/[3760] Speed: 94.685243 samples/sec accuracy=74.365489 loss=0.972718 lr=0.009142 Epoch[018] Batch [3499]/[3760] Speed: 93.129749 samples/sec accuracy=74.357589 loss=0.972588 lr=0.009141 Epoch[018] Batch [3549]/[3760] Speed: 94.112530 samples/sec accuracy=74.349032 loss=0.972705 lr=0.009140 Epoch[018] Batch [3599]/[3760] Speed: 94.263712 samples/sec accuracy=74.323785 loss=0.973326 lr=0.009139 Epoch[018] Batch [3649]/[3760] Speed: 93.581062 samples/sec accuracy=74.294521 loss=0.973996 lr=0.009138 Epoch[018] Batch [3699]/[3760] Speed: 93.845613 samples/sec accuracy=74.268581 loss=0.975102 lr=0.009137 Epoch[018] Batch [3749]/[3760] Speed: 105.953251 samples/sec accuracy=74.267500 loss=0.975398 lr=0.009135 Batch [0049]/[0303]: acc-top1=62.031250 acc-top5=83.656250 Batch [0099]/[0303]: acc-top1=60.609375 acc-top5=83.671875 Batch [0149]/[0303]: acc-top1=62.208333 acc-top5=84.489583 Batch [0199]/[0303]: acc-top1=65.117188 acc-top5=85.976562 Batch [0249]/[0303]: acc-top1=64.643750 acc-top5=85.706250 Batch [0299]/[0303]: acc-top1=64.000000 acc-top5=85.598958 [Epoch 018] training: accuracy=74.266955 loss=0.975378 [Epoch 018] speed: 93 samples/sec time cost: 2792.039030 [Epoch 018] validation: acc-top1=64.016089 acc-top5=85.576526 loss=2.014751 Epoch[019] Batch [0049]/[3760] Speed: 64.377697 samples/sec accuracy=77.062500 loss=0.903798 lr=0.009134 Epoch[019] Batch [0099]/[3760] Speed: 94.570117 samples/sec accuracy=76.828125 loss=0.896764 lr=0.009133 Epoch[019] Batch [0149]/[3760] Speed: 93.851434 samples/sec accuracy=76.583333 loss=0.895176 lr=0.009132 Epoch[019] Batch [0199]/[3760] Speed: 93.596964 samples/sec accuracy=76.359375 loss=0.903824 lr=0.009130 Epoch[019] Batch [0249]/[3760] Speed: 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lr=0.009050 Epoch[019] Batch [3599]/[3760] Speed: 93.046827 samples/sec accuracy=74.731337 loss=0.955167 lr=0.009049 Epoch[019] Batch [3649]/[3760] Speed: 93.966453 samples/sec accuracy=74.703767 loss=0.956107 lr=0.009047 Epoch[019] Batch [3699]/[3760] Speed: 94.038729 samples/sec accuracy=74.684966 loss=0.956957 lr=0.009046 Epoch[019] Batch [3749]/[3760] Speed: 105.616262 samples/sec accuracy=74.685833 loss=0.956985 lr=0.009045 Batch [0049]/[0303]: acc-top1=63.281250 acc-top5=84.906250 Batch [0099]/[0303]: acc-top1=61.500000 acc-top5=84.187500 Batch [0149]/[0303]: acc-top1=62.364583 acc-top5=85.041667 Batch [0199]/[0303]: acc-top1=65.132812 acc-top5=86.234375 Batch [0249]/[0303]: acc-top1=64.681250 acc-top5=85.837500 Batch [0299]/[0303]: acc-top1=64.072917 acc-top5=85.708333 [Epoch 019] training: accuracy=74.682929 loss=0.957186 [Epoch 019] speed: 93 samples/sec time cost: 2793.039587 [Epoch 019] validation: acc-top1=64.077970 acc-top5=85.715759 loss=2.004170 Epoch[020] Batch 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accuracy=76.368750 loss=0.893902 lr=0.009032 Epoch[020] Batch [0549]/[3759] Speed: 94.035335 samples/sec accuracy=76.386364 loss=0.891973 lr=0.009031 Epoch[020] Batch [0599]/[3759] Speed: 94.177467 samples/sec accuracy=76.296875 loss=0.895940 lr=0.009030 Epoch[020] Batch [0649]/[3759] Speed: 94.025120 samples/sec accuracy=76.283654 loss=0.895485 lr=0.009029 Epoch[020] Batch [0699]/[3759] Speed: 94.374565 samples/sec accuracy=76.292411 loss=0.895269 lr=0.009027 Epoch[020] Batch [0749]/[3759] Speed: 93.429495 samples/sec accuracy=76.258333 loss=0.894469 lr=0.009026 Epoch[020] Batch [0799]/[3759] Speed: 93.910799 samples/sec accuracy=76.134766 loss=0.898178 lr=0.009025 Epoch[020] Batch [0849]/[3759] Speed: 93.995934 samples/sec accuracy=76.068015 loss=0.899979 lr=0.009024 Epoch[020] Batch [0899]/[3759] Speed: 93.682992 samples/sec accuracy=76.046875 loss=0.901099 lr=0.009023 Epoch[020] Batch [0949]/[3759] Speed: 93.842707 samples/sec accuracy=76.009868 loss=0.901030 lr=0.009021 Epoch[020] 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accuracy=75.138060 loss=0.936556 lr=0.008961 Epoch[020] Batch [3399]/[3759] Speed: 93.817277 samples/sec accuracy=75.126838 loss=0.937188 lr=0.008960 Epoch[020] Batch [3449]/[3759] Speed: 93.052280 samples/sec accuracy=75.108696 loss=0.937668 lr=0.008958 Epoch[020] Batch [3499]/[3759] Speed: 93.258979 samples/sec accuracy=75.110268 loss=0.937827 lr=0.008957 Epoch[020] Batch [3549]/[3759] Speed: 94.447290 samples/sec accuracy=75.090229 loss=0.938952 lr=0.008956 Epoch[020] Batch [3599]/[3759] Speed: 93.788329 samples/sec accuracy=75.060330 loss=0.940328 lr=0.008955 Epoch[020] Batch [3649]/[3759] Speed: 94.058605 samples/sec accuracy=75.045805 loss=0.940851 lr=0.008953 Epoch[020] Batch [3699]/[3759] Speed: 92.839608 samples/sec accuracy=75.041385 loss=0.940871 lr=0.008952 Epoch[020] Batch [3749]/[3759] Speed: 106.750333 samples/sec accuracy=75.009583 loss=0.942052 lr=0.008951 Batch [0049]/[0303]: acc-top1=63.156250 acc-top5=84.500000 Batch [0099]/[0303]: acc-top1=60.453125 acc-top5=83.796875 Batch [0149]/[0303]: acc-top1=61.781250 acc-top5=84.156250 Batch [0199]/[0303]: acc-top1=64.687500 acc-top5=85.476562 Batch [0249]/[0303]: acc-top1=64.143750 acc-top5=84.993750 Batch [0299]/[0303]: acc-top1=63.614583 acc-top5=85.119792 [Epoch 020] training: accuracy=75.008313 loss=0.942251 [Epoch 020] speed: 93 samples/sec time cost: 2793.210272 [Epoch 020] validation: acc-top1=63.598391 acc-top5=85.138201 loss=2.159460 Epoch[021] Batch [0049]/[3760] Speed: 64.290671 samples/sec accuracy=76.812500 loss=0.876384 lr=0.008949 Epoch[021] Batch [0099]/[3760] Speed: 93.275256 samples/sec accuracy=76.687500 loss=0.875404 lr=0.008948 Epoch[021] Batch [0149]/[3760] Speed: 94.580216 samples/sec accuracy=76.552083 loss=0.875646 lr=0.008947 Epoch[021] Batch [0199]/[3760] Speed: 94.147443 samples/sec accuracy=76.789062 loss=0.871616 lr=0.008945 Epoch[021] Batch [0249]/[3760] Speed: 93.531464 samples/sec accuracy=76.818750 loss=0.867256 lr=0.008944 Epoch[021] Batch [0299]/[3760] 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accuracy=75.968750 loss=0.900245 lr=0.008906 Epoch[021] Batch [1749]/[3760] Speed: 94.057455 samples/sec accuracy=75.950893 loss=0.901084 lr=0.008905 Epoch[021] Batch [1799]/[3760] Speed: 93.648766 samples/sec accuracy=75.930556 loss=0.901331 lr=0.008904 Epoch[021] Batch [1849]/[3760] Speed: 93.805166 samples/sec accuracy=75.911318 loss=0.901546 lr=0.008903 Epoch[021] Batch [1899]/[3760] Speed: 93.926147 samples/sec accuracy=75.861842 loss=0.903179 lr=0.008901 Epoch[021] Batch [1949]/[3760] Speed: 93.251705 samples/sec accuracy=75.868590 loss=0.903918 lr=0.008900 Epoch[021] Batch [1999]/[3760] Speed: 94.380669 samples/sec accuracy=75.855469 loss=0.904033 lr=0.008899 Epoch[021] Batch [2049]/[3760] Speed: 93.905993 samples/sec accuracy=75.832317 loss=0.905414 lr=0.008897 Epoch[021] Batch [2099]/[3760] Speed: 94.125346 samples/sec accuracy=75.819940 loss=0.906116 lr=0.008896 Epoch[021] Batch [2149]/[3760] Speed: 93.022817 samples/sec accuracy=75.800145 loss=0.907628 lr=0.008895 Epoch[021] 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accuracy=75.660377 loss=0.915304 lr=0.008882 Epoch[021] Batch [2699]/[3760] Speed: 93.765650 samples/sec accuracy=75.634838 loss=0.915939 lr=0.008880 Epoch[021] Batch [2749]/[3760] Speed: 94.081282 samples/sec accuracy=75.607386 loss=0.917162 lr=0.008879 Epoch[021] Batch [2799]/[3760] Speed: 93.695616 samples/sec accuracy=75.549107 loss=0.918543 lr=0.008878 Epoch[021] Batch [2849]/[3760] Speed: 93.321942 samples/sec accuracy=75.516996 loss=0.919841 lr=0.008876 Epoch[021] Batch [2899]/[3760] Speed: 94.280310 samples/sec accuracy=75.509159 loss=0.920556 lr=0.008875 Epoch[021] Batch [2949]/[3760] Speed: 94.470016 samples/sec accuracy=75.500000 loss=0.920771 lr=0.008874 Epoch[021] Batch [2999]/[3760] Speed: 93.423616 samples/sec accuracy=75.493750 loss=0.920751 lr=0.008872 Epoch[021] Batch [3049]/[3760] Speed: 94.123818 samples/sec accuracy=75.483607 loss=0.921011 lr=0.008871 Epoch[021] Batch [3099]/[3760] Speed: 93.442655 samples/sec accuracy=75.458165 loss=0.921852 lr=0.008870 Epoch[021] Batch [3149]/[3760] Speed: 93.884878 samples/sec accuracy=75.446429 loss=0.922626 lr=0.008868 Epoch[021] Batch [3199]/[3760] Speed: 93.796867 samples/sec accuracy=75.412109 loss=0.923391 lr=0.008867 Epoch[021] Batch [3249]/[3760] Speed: 93.345031 samples/sec accuracy=75.393269 loss=0.924595 lr=0.008866 Epoch[021] Batch [3299]/[3760] Speed: 94.358065 samples/sec accuracy=75.386837 loss=0.925030 lr=0.008864 Epoch[021] Batch [3349]/[3760] Speed: 93.762570 samples/sec accuracy=75.384795 loss=0.925507 lr=0.008863 Epoch[021] Batch [3399]/[3760] Speed: 94.465778 samples/sec accuracy=75.353860 loss=0.926772 lr=0.008862 Epoch[021] Batch [3449]/[3760] Speed: 94.160662 samples/sec accuracy=75.341938 loss=0.927133 lr=0.008860 Epoch[021] Batch [3499]/[3760] Speed: 93.894042 samples/sec accuracy=75.337500 loss=0.927281 lr=0.008859 Epoch[021] Batch [3549]/[3760] Speed: 93.922800 samples/sec accuracy=75.321743 loss=0.927959 lr=0.008858 Epoch[021] Batch [3599]/[3760] Speed: 93.843935 samples/sec accuracy=75.326389 loss=0.928205 lr=0.008856 Epoch[021] Batch [3649]/[3760] Speed: 93.794367 samples/sec accuracy=75.307791 loss=0.929145 lr=0.008855 Epoch[021] Batch [3699]/[3760] Speed: 94.306123 samples/sec accuracy=75.303632 loss=0.929333 lr=0.008854 Epoch[021] Batch [3749]/[3760] Speed: 105.941226 samples/sec accuracy=75.277083 loss=0.930255 lr=0.008852 Batch [0049]/[0303]: acc-top1=63.531250 acc-top5=84.656250 Batch [0099]/[0303]: acc-top1=61.500000 acc-top5=83.890625 Batch [0149]/[0303]: acc-top1=62.927083 acc-top5=84.927083 Batch [0199]/[0303]: acc-top1=65.500000 acc-top5=86.343750 Batch [0249]/[0303]: acc-top1=64.975000 acc-top5=86.137500 Batch [0299]/[0303]: acc-top1=64.286458 acc-top5=86.057292 [Epoch 021] training: accuracy=75.276346 loss=0.930324 [Epoch 021] speed: 93 samples/sec time cost: 2792.975427 [Epoch 021] validation: acc-top1=64.284241 acc-top5=86.035479 loss=2.044635 Epoch[022] Batch [0049]/[3760] Speed: 64.342808 samples/sec accuracy=77.000000 loss=0.872396 lr=0.008851 Epoch[022] Batch [0099]/[3760] Speed: 94.525914 samples/sec accuracy=76.828125 loss=0.869041 lr=0.008850 Epoch[022] Batch [0149]/[3760] Speed: 94.797310 samples/sec accuracy=77.093750 loss=0.851913 lr=0.008848 Epoch[022] Batch [0199]/[3760] Speed: 93.815846 samples/sec accuracy=77.304688 loss=0.841221 lr=0.008847 Epoch[022] Batch [0249]/[3760] Speed: 93.950894 samples/sec accuracy=77.193750 loss=0.843008 lr=0.008846 Epoch[022] Batch [0299]/[3760] Speed: 93.578518 samples/sec accuracy=77.255208 loss=0.841796 lr=0.008844 Epoch[022] Batch [0349]/[3760] Speed: 93.714895 samples/sec accuracy=77.290179 loss=0.841219 lr=0.008843 Epoch[022] Batch [0399]/[3760] Speed: 93.971355 samples/sec accuracy=77.230469 loss=0.842850 lr=0.008842 Epoch[022] Batch [0449]/[3760] Speed: 93.394925 samples/sec accuracy=77.336806 loss=0.841159 lr=0.008840 Epoch[022] Batch [0499]/[3760] Speed: 93.781879 samples/sec accuracy=77.312500 loss=0.842353 lr=0.008839 Epoch[022] Batch [0549]/[3760] Speed: 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acc-top1=64.804688 acc-top5=85.984375 Batch [0249]/[0303]: acc-top1=64.225000 acc-top5=85.681250 Batch [0299]/[0303]: acc-top1=63.666667 acc-top5=85.557292 [Epoch 022] training: accuracy=75.808261 loss=0.909703 [Epoch 022] speed: 93 samples/sec time cost: 2791.908804 [Epoch 022] validation: acc-top1=63.665429 acc-top5=85.504332 loss=2.119898 Epoch[023] Batch [0049]/[3759] Speed: 63.940504 samples/sec accuracy=76.781250 loss=0.877232 lr=0.008749 Epoch[023] Batch [0099]/[3759] Speed: 94.375496 samples/sec accuracy=77.281250 loss=0.859880 lr=0.008747 Epoch[023] Batch [0149]/[3759] Speed: 94.635306 samples/sec accuracy=77.406250 loss=0.847774 lr=0.008746 Epoch[023] Batch [0199]/[3759] Speed: 93.482238 samples/sec accuracy=77.953125 loss=0.828695 lr=0.008745 Epoch[023] Batch [0249]/[3759] Speed: 94.456839 samples/sec accuracy=77.868750 loss=0.826620 lr=0.008743 Epoch[023] Batch [0299]/[3759] Speed: 93.386365 samples/sec accuracy=77.828125 loss=0.826478 lr=0.008742 Epoch[023] Batch 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accuracy=77.259766 loss=0.851163 lr=0.008728 Epoch[023] Batch [0849]/[3759] Speed: 93.511970 samples/sec accuracy=77.226103 loss=0.854325 lr=0.008727 Epoch[023] Batch [0899]/[3759] Speed: 93.904003 samples/sec accuracy=77.189236 loss=0.856003 lr=0.008725 Epoch[023] Batch [0949]/[3759] Speed: 93.875970 samples/sec accuracy=77.151316 loss=0.857849 lr=0.008724 Epoch[023] Batch [0999]/[3759] Speed: 93.908911 samples/sec accuracy=77.120312 loss=0.858837 lr=0.008722 Epoch[023] Batch [1049]/[3759] Speed: 93.941743 samples/sec accuracy=77.122024 loss=0.857769 lr=0.008721 Epoch[023] Batch [1099]/[3759] Speed: 94.145056 samples/sec accuracy=77.075284 loss=0.859659 lr=0.008720 Epoch[023] Batch [1149]/[3759] Speed: 93.483104 samples/sec accuracy=77.006793 loss=0.861183 lr=0.008718 Epoch[023] Batch [1199]/[3759] Speed: 94.269216 samples/sec accuracy=76.967448 loss=0.861610 lr=0.008717 Epoch[023] Batch [1249]/[3759] Speed: 93.564750 samples/sec accuracy=76.950000 loss=0.862201 lr=0.008715 Epoch[023] 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accuracy=76.708036 loss=0.871394 lr=0.008701 Epoch[023] Batch [1799]/[3759] Speed: 94.006785 samples/sec accuracy=76.683160 loss=0.872515 lr=0.008700 Epoch[023] Batch [1849]/[3759] Speed: 93.479854 samples/sec accuracy=76.659628 loss=0.873898 lr=0.008699 Epoch[023] Batch [1899]/[3759] Speed: 93.361405 samples/sec accuracy=76.672697 loss=0.872931 lr=0.008697 Epoch[023] Batch [1949]/[3759] Speed: 93.583442 samples/sec accuracy=76.704327 loss=0.872755 lr=0.008696 Epoch[023] Batch [1999]/[3759] Speed: 93.193164 samples/sec accuracy=76.639062 loss=0.874466 lr=0.008694 Epoch[023] Batch [2049]/[3759] Speed: 93.712593 samples/sec accuracy=76.622713 loss=0.874437 lr=0.008693 Epoch[023] Batch [2099]/[3759] Speed: 94.481411 samples/sec accuracy=76.604167 loss=0.875125 lr=0.008692 Epoch[023] Batch [2149]/[3759] Speed: 93.911075 samples/sec accuracy=76.539244 loss=0.876764 lr=0.008690 Epoch[023] Batch [2199]/[3759] Speed: 93.998818 samples/sec accuracy=76.518466 loss=0.877198 lr=0.008689 Epoch[023] 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accuracy=76.335648 loss=0.886681 lr=0.008675 Epoch[023] Batch [2749]/[3759] Speed: 93.012855 samples/sec accuracy=76.318750 loss=0.887211 lr=0.008673 Epoch[023] Batch [2799]/[3759] Speed: 93.884554 samples/sec accuracy=76.296875 loss=0.888333 lr=0.008672 Epoch[023] Batch [2849]/[3759] Speed: 93.370808 samples/sec accuracy=76.268640 loss=0.889233 lr=0.008670 Epoch[023] Batch [2899]/[3759] Speed: 93.875078 samples/sec accuracy=76.276401 loss=0.889218 lr=0.008669 Epoch[023] Batch [2949]/[3759] Speed: 93.960206 samples/sec accuracy=76.267479 loss=0.889591 lr=0.008667 Epoch[023] Batch [2999]/[3759] Speed: 94.489745 samples/sec accuracy=76.265104 loss=0.889644 lr=0.008666 Epoch[023] Batch [3049]/[3759] Speed: 93.800825 samples/sec accuracy=76.247951 loss=0.890323 lr=0.008665 Epoch[023] Batch [3099]/[3759] Speed: 93.036028 samples/sec accuracy=76.236895 loss=0.891005 lr=0.008663 Epoch[023] Batch [3149]/[3759] Speed: 93.969549 samples/sec accuracy=76.207837 loss=0.892146 lr=0.008662 Epoch[023] Batch [3199]/[3759] Speed: 93.658606 samples/sec accuracy=76.186035 loss=0.893291 lr=0.008660 Epoch[023] Batch [3249]/[3759] Speed: 93.290104 samples/sec accuracy=76.173077 loss=0.894009 lr=0.008659 Epoch[023] Batch [3299]/[3759] Speed: 93.865584 samples/sec accuracy=76.143466 loss=0.894717 lr=0.008658 Epoch[023] Batch [3349]/[3759] Speed: 94.174853 samples/sec accuracy=76.105877 loss=0.896064 lr=0.008656 Epoch[023] Batch [3399]/[3759] Speed: 94.106505 samples/sec accuracy=76.077665 loss=0.897049 lr=0.008655 Epoch[023] Batch [3449]/[3759] Speed: 93.794632 samples/sec accuracy=76.066123 loss=0.897461 lr=0.008653 Epoch[023] Batch [3499]/[3759] Speed: 93.411977 samples/sec accuracy=76.028571 loss=0.898856 lr=0.008652 Epoch[023] Batch [3549]/[3759] Speed: 94.452175 samples/sec accuracy=76.014965 loss=0.899225 lr=0.008650 Epoch[023] Batch [3599]/[3759] Speed: 93.465673 samples/sec accuracy=75.999132 loss=0.899775 lr=0.008649 Epoch[023] Batch [3649]/[3759] Speed: 93.994871 samples/sec accuracy=75.981592 loss=0.900753 lr=0.008648 Epoch[023] Batch [3699]/[3759] Speed: 93.974818 samples/sec accuracy=75.984375 loss=0.901044 lr=0.008646 Epoch[023] Batch [3749]/[3759] Speed: 105.614086 samples/sec accuracy=75.978333 loss=0.901346 lr=0.008645 Batch [0049]/[0303]: acc-top1=62.718750 acc-top5=85.250000 Batch [0099]/[0303]: acc-top1=61.203125 acc-top5=84.140625 Batch [0149]/[0303]: acc-top1=62.322917 acc-top5=84.729167 Batch [0199]/[0303]: acc-top1=65.125000 acc-top5=85.929688 Batch [0249]/[0303]: acc-top1=64.662500 acc-top5=85.662500 Batch [0299]/[0303]: acc-top1=63.864583 acc-top5=85.541667 [Epoch 023] training: accuracy=75.983473 loss=0.901208 [Epoch 023] speed: 93 samples/sec time cost: 2794.332795 [Epoch 023] validation: acc-top1=63.768564 acc-top5=85.483705 loss=2.090579 Epoch[024] Batch [0049]/[3760] Speed: 64.253444 samples/sec accuracy=77.937500 loss=0.802387 lr=0.008643 Epoch[024] Batch [0099]/[3760] Speed: 93.683330 samples/sec accuracy=77.500000 loss=0.829182 lr=0.008642 Epoch[024] Batch [0149]/[3760] Speed: 93.835025 samples/sec accuracy=78.208333 loss=0.807598 lr=0.008640 Epoch[024] Batch [0199]/[3760] Speed: 93.989772 samples/sec accuracy=78.257812 loss=0.807105 lr=0.008639 Epoch[024] Batch [0249]/[3760] Speed: 93.601363 samples/sec accuracy=78.037500 loss=0.816959 lr=0.008637 Epoch[024] Batch [0299]/[3760] Speed: 94.542579 samples/sec accuracy=78.166667 loss=0.817542 lr=0.008636 Epoch[024] Batch [0349]/[3760] Speed: 93.996731 samples/sec accuracy=78.053571 loss=0.818191 lr=0.008634 Epoch[024] Batch [0399]/[3760] Speed: 93.856321 samples/sec accuracy=78.023438 loss=0.820270 lr=0.008633 Epoch[024] Batch [0449]/[3760] Speed: 93.766275 samples/sec accuracy=77.843750 loss=0.821641 lr=0.008632 Epoch[024] Batch [0499]/[3760] Speed: 92.127719 samples/sec accuracy=77.828125 loss=0.822224 lr=0.008630 Epoch[024] Batch [0549]/[3760] Speed: 93.594687 samples/sec accuracy=77.928977 loss=0.822370 lr=0.008629 Epoch[024] Batch [0599]/[3760] Speed: 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lr=0.008587 Epoch[024] Batch [2049]/[3760] Speed: 94.279558 samples/sec accuracy=77.237043 loss=0.853581 lr=0.008585 Epoch[024] Batch [2099]/[3760] Speed: 93.604766 samples/sec accuracy=77.239583 loss=0.853321 lr=0.008584 Epoch[024] Batch [2149]/[3760] Speed: 93.586758 samples/sec accuracy=77.195494 loss=0.855190 lr=0.008582 Epoch[024] Batch [2199]/[3760] Speed: 92.867491 samples/sec accuracy=77.177557 loss=0.856396 lr=0.008581 Epoch[024] Batch [2249]/[3760] Speed: 94.235097 samples/sec accuracy=77.124306 loss=0.858363 lr=0.008579 Epoch[024] Batch [2299]/[3760] Speed: 94.257012 samples/sec accuracy=77.093750 loss=0.859429 lr=0.008578 Epoch[024] Batch [2349]/[3760] Speed: 92.833439 samples/sec accuracy=77.063165 loss=0.860350 lr=0.008576 Epoch[024] Batch [2399]/[3760] Speed: 94.127778 samples/sec accuracy=77.033203 loss=0.861340 lr=0.008575 Epoch[024] Batch [2449]/[3760] Speed: 94.357226 samples/sec accuracy=76.982143 loss=0.863223 lr=0.008574 Epoch[024] Batch [2499]/[3760] Speed: 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lr=0.008559 Epoch[024] Batch [2999]/[3760] Speed: 93.977846 samples/sec accuracy=76.741146 loss=0.873488 lr=0.008557 Epoch[024] Batch [3049]/[3760] Speed: 93.734755 samples/sec accuracy=76.737193 loss=0.873766 lr=0.008556 Epoch[024] Batch [3099]/[3760] Speed: 93.825238 samples/sec accuracy=76.712702 loss=0.874428 lr=0.008555 Epoch[024] Batch [3149]/[3760] Speed: 93.805112 samples/sec accuracy=76.702381 loss=0.875027 lr=0.008553 Epoch[024] Batch [3199]/[3760] Speed: 94.585086 samples/sec accuracy=76.680176 loss=0.875785 lr=0.008552 Epoch[024] Batch [3249]/[3760] Speed: 94.045117 samples/sec accuracy=76.665385 loss=0.876239 lr=0.008550 Epoch[024] Batch [3299]/[3760] Speed: 93.961739 samples/sec accuracy=76.650095 loss=0.876849 lr=0.008549 Epoch[024] Batch [3349]/[3760] Speed: 93.622248 samples/sec accuracy=76.652985 loss=0.877057 lr=0.008547 Epoch[024] Batch [3399]/[3760] Speed: 93.635279 samples/sec accuracy=76.625919 loss=0.877728 lr=0.008546 Epoch[024] Batch [3449]/[3760] Speed: 93.963431 samples/sec accuracy=76.604167 loss=0.878737 lr=0.008544 Epoch[024] Batch [3499]/[3760] Speed: 93.078659 samples/sec accuracy=76.568750 loss=0.879749 lr=0.008543 Epoch[024] Batch [3549]/[3760] Speed: 93.293546 samples/sec accuracy=76.553257 loss=0.880326 lr=0.008541 Epoch[024] Batch [3599]/[3760] Speed: 94.468843 samples/sec accuracy=76.533420 loss=0.881545 lr=0.008540 Epoch[024] Batch [3649]/[3760] Speed: 94.137544 samples/sec accuracy=76.500000 loss=0.882588 lr=0.008538 Epoch[024] Batch [3699]/[3760] Speed: 93.698222 samples/sec accuracy=76.481419 loss=0.883258 lr=0.008537 Epoch[024] Batch [3749]/[3760] Speed: 105.819065 samples/sec accuracy=76.458333 loss=0.884034 lr=0.008535 Batch [0049]/[0303]: acc-top1=63.312500 acc-top5=84.312500 Batch [0099]/[0303]: acc-top1=61.562500 acc-top5=84.203125 Batch [0149]/[0303]: acc-top1=62.531250 acc-top5=84.656250 Batch [0199]/[0303]: acc-top1=65.367188 acc-top5=86.078125 Batch [0249]/[0303]: acc-top1=65.350000 acc-top5=86.006250 Batch [0299]/[0303]: acc-top1=64.609375 acc-top5=85.958333 [Epoch 024] training: accuracy=76.460688 loss=0.884070 [Epoch 024] speed: 93 samples/sec time cost: 2794.099471 [Epoch 024] validation: acc-top1=64.655528 acc-top5=85.973597 loss=2.034902 Epoch[025] Batch [0049]/[3760] Speed: 65.021108 samples/sec accuracy=78.156250 loss=0.806672 lr=0.008534 Epoch[025] Batch [0099]/[3760] Speed: 94.355673 samples/sec accuracy=78.359375 loss=0.808037 lr=0.008532 Epoch[025] Batch [0149]/[3760] Speed: 93.410280 samples/sec accuracy=78.614583 loss=0.812666 lr=0.008531 Epoch[025] Batch [0199]/[3760] Speed: 94.246642 samples/sec accuracy=78.796875 loss=0.807806 lr=0.008529 Epoch[025] Batch [0249]/[3760] Speed: 94.478485 samples/sec accuracy=78.818750 loss=0.808295 lr=0.008528 Epoch[025] Batch [0299]/[3760] Speed: 94.059676 samples/sec accuracy=78.625000 loss=0.810794 lr=0.008526 Epoch[025] Batch [0349]/[3760] Speed: 94.248431 samples/sec accuracy=78.459821 loss=0.817536 lr=0.008525 Epoch[025] Batch 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accuracy=78.011029 loss=0.827095 lr=0.008510 Epoch[025] Batch [0899]/[3760] Speed: 93.250976 samples/sec accuracy=77.911458 loss=0.829108 lr=0.008508 Epoch[025] Batch [0949]/[3760] Speed: 93.792114 samples/sec accuracy=77.876645 loss=0.830887 lr=0.008507 Epoch[025] Batch [0999]/[3760] Speed: 93.565730 samples/sec accuracy=77.725000 loss=0.835111 lr=0.008505 Epoch[025] Batch [1049]/[3760] Speed: 94.148409 samples/sec accuracy=77.736607 loss=0.834109 lr=0.008504 Epoch[025] Batch [1099]/[3760] Speed: 94.105293 samples/sec accuracy=77.684659 loss=0.834720 lr=0.008502 Epoch[025] Batch [1149]/[3760] Speed: 94.517224 samples/sec accuracy=77.566576 loss=0.838731 lr=0.008501 Epoch[025] Batch [1199]/[3760] Speed: 93.601720 samples/sec accuracy=77.532552 loss=0.839345 lr=0.008499 Epoch[025] Batch [1249]/[3760] Speed: 94.415276 samples/sec accuracy=77.525000 loss=0.839875 lr=0.008498 Epoch[025] Batch [1299]/[3760] Speed: 93.796453 samples/sec accuracy=77.484375 loss=0.840842 lr=0.008496 Epoch[025] 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accuracy=77.259549 loss=0.850216 lr=0.008481 Epoch[025] Batch [1849]/[3760] Speed: 94.845997 samples/sec accuracy=77.236486 loss=0.851646 lr=0.008480 Epoch[025] Batch [1899]/[3760] Speed: 94.140485 samples/sec accuracy=77.191612 loss=0.853580 lr=0.008478 Epoch[025] Batch [1949]/[3760] Speed: 93.421047 samples/sec accuracy=77.162660 loss=0.854847 lr=0.008477 Epoch[025] Batch [1999]/[3760] Speed: 93.164710 samples/sec accuracy=77.122656 loss=0.855992 lr=0.008475 Epoch[025] Batch [2049]/[3760] Speed: 93.467184 samples/sec accuracy=77.115091 loss=0.856629 lr=0.008474 Epoch[025] Batch [2099]/[3760] Speed: 93.550656 samples/sec accuracy=77.142857 loss=0.855963 lr=0.008472 Epoch[025] Batch [2149]/[3760] Speed: 93.641433 samples/sec accuracy=77.120640 loss=0.856680 lr=0.008471 Epoch[025] Batch [2199]/[3760] Speed: 94.318830 samples/sec accuracy=77.066051 loss=0.858258 lr=0.008469 Epoch[025] Batch [2249]/[3760] Speed: 94.184799 samples/sec accuracy=77.056250 loss=0.859231 lr=0.008468 Epoch[025] Batch [2299]/[3760] Speed: 93.939169 samples/sec accuracy=77.052310 loss=0.859961 lr=0.008466 Epoch[025] Batch [2349]/[3760] Speed: 93.287786 samples/sec accuracy=77.018617 loss=0.861230 lr=0.008465 Epoch[025] Batch [2399]/[3760] Speed: 94.407980 samples/sec accuracy=76.999349 loss=0.862449 lr=0.008463 Epoch[025] Batch [2449]/[3760] Speed: 92.744817 samples/sec accuracy=77.000000 loss=0.862817 lr=0.008462 Epoch[025] Batch [2499]/[3760] Speed: 93.704677 samples/sec accuracy=76.990000 loss=0.863360 lr=0.008460 Epoch[025] Batch [2549]/[3760] Speed: 93.447131 samples/sec accuracy=76.979167 loss=0.864143 lr=0.008459 Epoch[025] Batch [2599]/[3760] Speed: 94.254078 samples/sec accuracy=76.989183 loss=0.863530 lr=0.008457 Epoch[025] Batch [2649]/[3760] Speed: 93.121199 samples/sec accuracy=76.966392 loss=0.864024 lr=0.008456 Epoch[025] Batch [2699]/[3760] Speed: 93.941800 samples/sec accuracy=76.972801 loss=0.863694 lr=0.008454 Epoch[025] Batch [2749]/[3760] Speed: 94.369248 samples/sec accuracy=76.951136 loss=0.864020 lr=0.008453 Epoch[025] Batch [2799]/[3760] Speed: 94.191047 samples/sec accuracy=76.919085 loss=0.865061 lr=0.008451 Epoch[025] Batch [2849]/[3760] Speed: 94.307083 samples/sec accuracy=76.913377 loss=0.865737 lr=0.008450 Epoch[025] Batch [2899]/[3760] Speed: 93.346852 samples/sec accuracy=76.918103 loss=0.866157 lr=0.008448 Epoch[025] Batch [2949]/[3760] Speed: 94.020741 samples/sec accuracy=76.895127 loss=0.866812 lr=0.008447 Epoch[025] Batch [2999]/[3760] Speed: 93.910516 samples/sec accuracy=76.878646 loss=0.867195 lr=0.008445 Epoch[025] Batch [3049]/[3760] Speed: 94.215605 samples/sec accuracy=76.849898 loss=0.868307 lr=0.008444 Epoch[025] Batch [3099]/[3760] Speed: 93.750059 samples/sec accuracy=76.831149 loss=0.869001 lr=0.008442 Epoch[025] Batch [3149]/[3760] Speed: 93.926540 samples/sec accuracy=76.821429 loss=0.869029 lr=0.008441 Epoch[025] Batch [3199]/[3760] Speed: 93.439944 samples/sec accuracy=76.793945 loss=0.869929 lr=0.008439 Epoch[025] Batch [3249]/[3760] Speed: 93.483337 samples/sec accuracy=76.793269 loss=0.870288 lr=0.008438 Epoch[025] Batch [3299]/[3760] Speed: 94.471618 samples/sec accuracy=76.773674 loss=0.870879 lr=0.008436 Epoch[025] Batch [3349]/[3760] Speed: 93.953061 samples/sec accuracy=76.766791 loss=0.871278 lr=0.008435 Epoch[025] Batch [3399]/[3760] Speed: 93.604625 samples/sec accuracy=76.753676 loss=0.871594 lr=0.008433 Epoch[025] Batch [3449]/[3760] Speed: 93.720511 samples/sec accuracy=76.742301 loss=0.871926 lr=0.008432 Epoch[025] Batch [3499]/[3760] Speed: 94.424003 samples/sec accuracy=76.736607 loss=0.872219 lr=0.008430 Epoch[025] Batch [3549]/[3760] Speed: 93.308813 samples/sec accuracy=76.728433 loss=0.872845 lr=0.008429 Epoch[025] Batch [3599]/[3760] Speed: 93.577114 samples/sec accuracy=76.713542 loss=0.873031 lr=0.008427 Epoch[025] Batch [3649]/[3760] Speed: 93.483674 samples/sec accuracy=76.707192 loss=0.873175 lr=0.008426 Epoch[025] Batch [3699]/[3760] Speed: 94.293276 samples/sec accuracy=76.710304 loss=0.873438 lr=0.008424 Epoch[025] Batch [3749]/[3760] Speed: 105.231882 samples/sec accuracy=76.694167 loss=0.873717 lr=0.008423 Batch [0049]/[0303]: acc-top1=63.906250 acc-top5=84.906250 Batch [0099]/[0303]: acc-top1=61.000000 acc-top5=83.968750 Batch [0149]/[0303]: acc-top1=62.281250 acc-top5=84.520833 Batch [0199]/[0303]: acc-top1=65.335938 acc-top5=86.023438 Batch [0249]/[0303]: acc-top1=64.775000 acc-top5=85.793750 Batch [0299]/[0303]: acc-top1=64.031250 acc-top5=85.776042 [Epoch 025] training: accuracy=76.687583 loss=0.873744 [Epoch 025] speed: 93 samples/sec time cost: 2792.134865 [Epoch 025] validation: acc-top1=64.026403 acc-top5=85.777640 loss=2.105386 Epoch[026] Batch [0049]/[3759] Speed: 64.062554 samples/sec accuracy=78.531250 loss=0.822477 lr=0.008421 Epoch[026] Batch [0099]/[3759] Speed: 94.075105 samples/sec accuracy=78.062500 loss=0.824774 lr=0.008419 Epoch[026] Batch [0149]/[3759] Speed: 94.169594 samples/sec accuracy=78.062500 loss=0.821489 lr=0.008418 Epoch[026] Batch [0199]/[3759] Speed: 93.828614 samples/sec accuracy=78.367188 loss=0.809214 lr=0.008416 Epoch[026] Batch [0249]/[3759] Speed: 93.324137 samples/sec accuracy=78.437500 loss=0.805866 lr=0.008415 Epoch[026] Batch [0299]/[3759] Speed: 93.574503 samples/sec accuracy=78.567708 loss=0.798197 lr=0.008413 Epoch[026] Batch [0349]/[3759] Speed: 94.119706 samples/sec accuracy=78.566964 loss=0.793217 lr=0.008412 Epoch[026] Batch [0399]/[3759] Speed: 93.345717 samples/sec accuracy=78.472656 loss=0.801375 lr=0.008410 Epoch[026] Batch [0449]/[3759] Speed: 92.918196 samples/sec accuracy=78.378472 loss=0.804215 lr=0.008408 Epoch[026] Batch [0499]/[3759] Speed: 93.734826 samples/sec accuracy=78.425000 loss=0.802834 lr=0.008407 Epoch[026] Batch [0549]/[3759] Speed: 94.099875 samples/sec accuracy=78.250000 loss=0.808358 lr=0.008405 Epoch[026] Batch [0599]/[3759] Speed: 93.001778 samples/sec accuracy=78.171875 loss=0.810776 lr=0.008404 Epoch[026] Batch [0649]/[3759] Speed: 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lr=0.008330 Epoch[026] Batch [3049]/[3759] Speed: 93.712690 samples/sec accuracy=77.018443 loss=0.857624 lr=0.008328 Epoch[026] Batch [3099]/[3759] Speed: 94.016366 samples/sec accuracy=77.014113 loss=0.857972 lr=0.008327 Epoch[026] Batch [3149]/[3759] Speed: 94.145396 samples/sec accuracy=77.000000 loss=0.858583 lr=0.008325 Epoch[026] Batch [3199]/[3759] Speed: 93.009901 samples/sec accuracy=76.986816 loss=0.859207 lr=0.008324 Epoch[026] Batch [3249]/[3759] Speed: 94.462947 samples/sec accuracy=76.984615 loss=0.859479 lr=0.008322 Epoch[026] Batch [3299]/[3759] Speed: 93.540427 samples/sec accuracy=76.974432 loss=0.859934 lr=0.008320 Epoch[026] Batch [3349]/[3759] Speed: 93.129815 samples/sec accuracy=76.966884 loss=0.860135 lr=0.008319 Epoch[026] Batch [3399]/[3759] Speed: 93.703483 samples/sec accuracy=76.978860 loss=0.859630 lr=0.008317 Epoch[026] Batch [3449]/[3759] Speed: 94.320711 samples/sec accuracy=76.956975 loss=0.860512 lr=0.008316 Epoch[026] Batch [3499]/[3759] Speed: 94.244140 samples/sec accuracy=76.924554 loss=0.861812 lr=0.008314 Epoch[026] Batch [3549]/[3759] Speed: 93.933471 samples/sec accuracy=76.907130 loss=0.862135 lr=0.008313 Epoch[026] Batch [3599]/[3759] Speed: 94.326894 samples/sec accuracy=76.885851 loss=0.863046 lr=0.008311 Epoch[026] Batch [3649]/[3759] Speed: 93.689037 samples/sec accuracy=76.875428 loss=0.863223 lr=0.008309 Epoch[026] Batch [3699]/[3759] Speed: 93.820170 samples/sec accuracy=76.877111 loss=0.863689 lr=0.008308 Epoch[026] Batch [3749]/[3759] Speed: 106.902167 samples/sec accuracy=76.851667 loss=0.864545 lr=0.008306 Batch [0049]/[0303]: acc-top1=64.312500 acc-top5=84.937500 Batch [0099]/[0303]: acc-top1=62.093750 acc-top5=84.687500 Batch [0149]/[0303]: acc-top1=63.864583 acc-top5=85.000000 Batch [0199]/[0303]: acc-top1=66.304688 acc-top5=86.164062 Batch [0249]/[0303]: acc-top1=65.318750 acc-top5=85.612500 Batch [0299]/[0303]: acc-top1=64.250000 acc-top5=85.348958 [Epoch 026] training: accuracy=76.843908 loss=0.864853 [Epoch 026] speed: 93 samples/sec time cost: 2792.717129 [Epoch 026] validation: acc-top1=64.304868 acc-top5=85.354785 loss=2.149792 Epoch[027] Batch [0049]/[3760] Speed: 64.775605 samples/sec accuracy=78.218750 loss=0.789618 lr=0.008304 Epoch[027] Batch [0099]/[3760] Speed: 93.851809 samples/sec accuracy=78.468750 loss=0.789532 lr=0.008303 Epoch[027] Batch [0149]/[3760] Speed: 93.770093 samples/sec accuracy=78.677083 loss=0.788392 lr=0.008301 Epoch[027] Batch [0199]/[3760] Speed: 93.951693 samples/sec accuracy=78.781250 loss=0.786648 lr=0.008300 Epoch[027] Batch [0249]/[3760] Speed: 93.164806 samples/sec accuracy=78.600000 loss=0.793014 lr=0.008298 Epoch[027] Batch [0299]/[3760] Speed: 93.676207 samples/sec accuracy=78.395833 loss=0.796321 lr=0.008297 Epoch[027] Batch [0349]/[3760] Speed: 94.035437 samples/sec accuracy=78.517857 loss=0.793882 lr=0.008295 Epoch[027] Batch [0399]/[3760] Speed: 94.770915 samples/sec accuracy=78.417969 loss=0.795177 lr=0.008293 Epoch[027] 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accuracy=78.267361 loss=0.803988 lr=0.008278 Epoch[027] Batch [0949]/[3760] Speed: 93.198048 samples/sec accuracy=78.281250 loss=0.804746 lr=0.008276 Epoch[027] Batch [0999]/[3760] Speed: 94.460587 samples/sec accuracy=78.245312 loss=0.807354 lr=0.008275 Epoch[027] Batch [1049]/[3760] Speed: 93.222262 samples/sec accuracy=78.196429 loss=0.809810 lr=0.008273 Epoch[027] Batch [1099]/[3760] Speed: 94.169143 samples/sec accuracy=78.169034 loss=0.810843 lr=0.008271 Epoch[027] Batch [1149]/[3760] Speed: 94.086513 samples/sec accuracy=78.116848 loss=0.812883 lr=0.008270 Epoch[027] Batch [1199]/[3760] Speed: 93.652513 samples/sec accuracy=78.140625 loss=0.812439 lr=0.008268 Epoch[027] Batch [1249]/[3760] Speed: 93.578906 samples/sec accuracy=78.148750 loss=0.812578 lr=0.008267 Epoch[027] Batch [1299]/[3760] Speed: 93.590854 samples/sec accuracy=78.149038 loss=0.813112 lr=0.008265 Epoch[027] Batch [1349]/[3760] Speed: 93.501268 samples/sec accuracy=78.123843 loss=0.814631 lr=0.008263 Epoch[027] 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accuracy=78.041385 loss=0.820137 lr=0.008248 Epoch[027] Batch [1899]/[3760] Speed: 94.181488 samples/sec accuracy=78.001645 loss=0.821644 lr=0.008246 Epoch[027] Batch [1949]/[3760] Speed: 93.468747 samples/sec accuracy=78.000801 loss=0.821294 lr=0.008244 Epoch[027] Batch [1999]/[3760] Speed: 94.568010 samples/sec accuracy=77.954687 loss=0.822261 lr=0.008243 Epoch[027] Batch [2049]/[3760] Speed: 93.589755 samples/sec accuracy=77.916921 loss=0.823706 lr=0.008241 Epoch[027] Batch [2099]/[3760] Speed: 93.649807 samples/sec accuracy=77.906250 loss=0.824129 lr=0.008240 Epoch[027] Batch [2149]/[3760] Speed: 93.689474 samples/sec accuracy=77.912064 loss=0.824183 lr=0.008238 Epoch[027] Batch [2199]/[3760] Speed: 94.153669 samples/sec accuracy=77.876420 loss=0.825384 lr=0.008236 Epoch[027] Batch [2249]/[3760] Speed: 94.109036 samples/sec accuracy=77.853472 loss=0.826734 lr=0.008235 Epoch[027] Batch [2299]/[3760] Speed: 93.972317 samples/sec accuracy=77.832880 loss=0.827990 lr=0.008233 Epoch[027] 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accuracy=77.666853 loss=0.833407 lr=0.008217 Epoch[027] Batch [2849]/[3760] Speed: 93.213438 samples/sec accuracy=77.649671 loss=0.834474 lr=0.008216 Epoch[027] Batch [2899]/[3760] Speed: 93.476416 samples/sec accuracy=77.626078 loss=0.835220 lr=0.008214 Epoch[027] Batch [2949]/[3760] Speed: 93.708837 samples/sec accuracy=77.611229 loss=0.835801 lr=0.008213 Epoch[027] Batch [2999]/[3760] Speed: 93.445003 samples/sec accuracy=77.588542 loss=0.836517 lr=0.008211 Epoch[027] Batch [3049]/[3760] Speed: 93.399205 samples/sec accuracy=77.546107 loss=0.838075 lr=0.008209 Epoch[027] Batch [3099]/[3760] Speed: 93.747185 samples/sec accuracy=77.520161 loss=0.838977 lr=0.008208 Epoch[027] Batch [3149]/[3760] Speed: 93.190621 samples/sec accuracy=77.524306 loss=0.839090 lr=0.008206 Epoch[027] Batch [3199]/[3760] Speed: 93.383622 samples/sec accuracy=77.531250 loss=0.838724 lr=0.008205 Epoch[027] Batch [3249]/[3760] Speed: 93.978510 samples/sec accuracy=77.511058 loss=0.839478 lr=0.008203 Epoch[027] Batch [3299]/[3760] Speed: 94.141015 samples/sec accuracy=77.494792 loss=0.840230 lr=0.008201 Epoch[027] Batch [3349]/[3760] Speed: 94.514494 samples/sec accuracy=77.475746 loss=0.841247 lr=0.008200 Epoch[027] Batch [3399]/[3760] Speed: 93.605095 samples/sec accuracy=77.459559 loss=0.841951 lr=0.008198 Epoch[027] Batch [3449]/[3760] Speed: 93.777266 samples/sec accuracy=77.434330 loss=0.842966 lr=0.008197 Epoch[027] Batch [3499]/[3760] Speed: 94.142495 samples/sec accuracy=77.413393 loss=0.843788 lr=0.008195 Epoch[027] Batch [3549]/[3760] Speed: 93.829931 samples/sec accuracy=77.409331 loss=0.844310 lr=0.008193 Epoch[027] Batch [3599]/[3760] Speed: 93.691176 samples/sec accuracy=77.401476 loss=0.844638 lr=0.008192 Epoch[027] Batch [3649]/[3760] Speed: 94.232997 samples/sec accuracy=77.364298 loss=0.846232 lr=0.008190 Epoch[027] Batch [3699]/[3760] Speed: 93.511298 samples/sec accuracy=77.347551 loss=0.846794 lr=0.008188 Epoch[027] Batch [3749]/[3760] Speed: 105.788608 samples/sec accuracy=77.341250 loss=0.847514 lr=0.008187 Batch [0049]/[0303]: acc-top1=64.156250 acc-top5=84.875000 Batch [0099]/[0303]: acc-top1=61.562500 acc-top5=84.093750 Batch [0149]/[0303]: acc-top1=63.041667 acc-top5=84.572917 Batch [0199]/[0303]: acc-top1=65.812500 acc-top5=85.789062 Batch [0249]/[0303]: acc-top1=65.075000 acc-top5=85.400000 Batch [0299]/[0303]: acc-top1=64.156250 acc-top5=85.312500 [Epoch 027] training: accuracy=77.337517 loss=0.847719 [Epoch 027] speed: 93 samples/sec time cost: 2794.510419 [Epoch 027] validation: acc-top1=64.103754 acc-top5=85.292904 loss=2.042422 Epoch[028] Batch [0049]/[3760] Speed: 64.959559 samples/sec accuracy=79.406250 loss=0.768456 lr=0.008185 Epoch[028] Batch [0099]/[3760] Speed: 94.318321 samples/sec accuracy=79.281250 loss=0.778335 lr=0.008183 Epoch[028] Batch [0149]/[3760] Speed: 94.283062 samples/sec accuracy=79.354167 loss=0.782486 lr=0.008182 Epoch[028] Batch [0199]/[3760] Speed: 93.368138 samples/sec accuracy=79.281250 loss=0.787980 lr=0.008180 Epoch[028] Batch [0249]/[3760] Speed: 93.653739 samples/sec accuracy=79.287500 loss=0.786981 lr=0.008178 Epoch[028] Batch [0299]/[3760] Speed: 93.389732 samples/sec accuracy=79.291667 loss=0.785036 lr=0.008177 Epoch[028] Batch [0349]/[3760] Speed: 93.626301 samples/sec accuracy=79.200893 loss=0.783821 lr=0.008175 Epoch[028] Batch [0399]/[3760] Speed: 94.308572 samples/sec accuracy=79.171875 loss=0.785689 lr=0.008174 Epoch[028] Batch [0449]/[3760] Speed: 93.917767 samples/sec accuracy=79.194444 loss=0.782183 lr=0.008172 Epoch[028] Batch [0499]/[3760] Speed: 93.274041 samples/sec accuracy=79.206250 loss=0.780533 lr=0.008170 Epoch[028] Batch [0549]/[3760] Speed: 94.409925 samples/sec accuracy=79.090909 loss=0.784362 lr=0.008169 Epoch[028] Batch [0599]/[3760] Speed: 93.834947 samples/sec accuracy=79.083333 loss=0.783828 lr=0.008167 Epoch[028] Batch [0649]/[3760] Speed: 94.009101 samples/sec accuracy=79.091346 loss=0.783544 lr=0.008166 Epoch[028] Batch [0699]/[3760] Speed: 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acc-top5=85.720916 loss=2.132620 Epoch[029] Batch [0049]/[3759] Speed: 65.002141 samples/sec accuracy=78.031250 loss=0.779994 lr=0.008062 Epoch[029] Batch [0099]/[3759] Speed: 93.841375 samples/sec accuracy=79.218750 loss=0.767661 lr=0.008061 Epoch[029] Batch [0149]/[3759] Speed: 94.794402 samples/sec accuracy=79.270833 loss=0.766094 lr=0.008059 Epoch[029] Batch [0199]/[3759] Speed: 94.417430 samples/sec accuracy=79.234375 loss=0.771162 lr=0.008057 Epoch[029] Batch [0249]/[3759] Speed: 94.091724 samples/sec accuracy=79.231250 loss=0.768545 lr=0.008056 Epoch[029] Batch [0299]/[3759] Speed: 93.557655 samples/sec accuracy=79.046875 loss=0.770818 lr=0.008054 Epoch[029] Batch [0349]/[3759] Speed: 92.509686 samples/sec accuracy=78.950893 loss=0.775936 lr=0.008052 Epoch[029] Batch [0399]/[3759] Speed: 94.329509 samples/sec accuracy=78.937500 loss=0.775775 lr=0.008051 Epoch[029] Batch [0449]/[3759] Speed: 93.851687 samples/sec accuracy=79.086806 loss=0.774456 lr=0.008049 Epoch[029] Batch 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accuracy=78.194627 loss=0.812101 lr=0.007969 Epoch[029] Batch [2899]/[3759] Speed: 93.148388 samples/sec accuracy=78.176724 loss=0.813076 lr=0.007967 Epoch[029] Batch [2949]/[3759] Speed: 94.017336 samples/sec accuracy=78.136653 loss=0.814282 lr=0.007966 Epoch[029] Batch [2999]/[3759] Speed: 92.995010 samples/sec accuracy=78.130729 loss=0.814759 lr=0.007964 Epoch[029] Batch [3049]/[3759] Speed: 94.430501 samples/sec accuracy=78.143955 loss=0.814721 lr=0.007962 Epoch[029] Batch [3099]/[3759] Speed: 93.598191 samples/sec accuracy=78.126008 loss=0.815663 lr=0.007961 Epoch[029] Batch [3149]/[3759] Speed: 93.398381 samples/sec accuracy=78.114087 loss=0.815688 lr=0.007959 Epoch[029] Batch [3199]/[3759] Speed: 94.031852 samples/sec accuracy=78.112793 loss=0.816240 lr=0.007957 Epoch[029] Batch [3249]/[3759] Speed: 94.044532 samples/sec accuracy=78.104808 loss=0.816635 lr=0.007955 Epoch[029] Batch [3299]/[3759] Speed: 93.888525 samples/sec accuracy=78.087595 loss=0.817312 lr=0.007954 Epoch[029] 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[0099]/[0303]: acc-top1=62.000000 acc-top5=84.609375 Batch [0149]/[0303]: acc-top1=62.968750 acc-top5=85.260417 Batch [0199]/[0303]: acc-top1=65.468750 acc-top5=86.304688 Batch [0249]/[0303]: acc-top1=64.900000 acc-top5=85.806250 Batch [0299]/[0303]: acc-top1=64.453125 acc-top5=85.911458 [Epoch 029] training: accuracy=77.916750 loss=0.823931 [Epoch 029] speed: 93 samples/sec time cost: 2791.810848 [Epoch 029] validation: acc-top1=64.423474 acc-top5=85.865305 loss=2.131259 Epoch[030] Batch [0049]/[3760] Speed: 65.484987 samples/sec accuracy=80.281250 loss=0.739524 lr=0.007937 Epoch[030] Batch [0099]/[3760] Speed: 93.523491 samples/sec accuracy=80.046875 loss=0.747079 lr=0.007935 Epoch[030] Batch [0149]/[3760] Speed: 93.762861 samples/sec accuracy=79.739583 loss=0.756076 lr=0.007933 Epoch[030] Batch [0199]/[3760] Speed: 93.732768 samples/sec accuracy=79.632812 loss=0.751670 lr=0.007932 Epoch[030] Batch [0249]/[3760] Speed: 94.178894 samples/sec accuracy=79.668750 loss=0.756393 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accuracy=79.906250 loss=0.754405 lr=0.007808 Epoch[031] Batch [0099]/[3760] Speed: 93.476391 samples/sec accuracy=79.343750 loss=0.766877 lr=0.007806 Epoch[031] Batch [0149]/[3760] Speed: 93.226274 samples/sec accuracy=79.531250 loss=0.761341 lr=0.007805 Epoch[031] Batch [0199]/[3760] Speed: 93.581230 samples/sec accuracy=79.320312 loss=0.764896 lr=0.007803 Epoch[031] Batch [0249]/[3760] Speed: 93.152397 samples/sec accuracy=79.387500 loss=0.762604 lr=0.007801 Epoch[031] Batch [0299]/[3760] Speed: 93.824939 samples/sec accuracy=79.369792 loss=0.760860 lr=0.007799 Epoch[031] Batch [0349]/[3760] Speed: 94.098787 samples/sec accuracy=79.491071 loss=0.757108 lr=0.007798 Epoch[031] Batch [0399]/[3760] Speed: 94.087613 samples/sec accuracy=79.527344 loss=0.756072 lr=0.007796 Epoch[031] Batch [0449]/[3760] Speed: 94.408811 samples/sec accuracy=79.329861 loss=0.760812 lr=0.007794 Epoch[031] Batch [0499]/[3760] Speed: 93.994359 samples/sec accuracy=79.462500 loss=0.756515 lr=0.007792 Epoch[031] 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accuracy=78.868534 loss=0.785105 lr=0.007709 Epoch[031] Batch [2949]/[3760] Speed: 93.673265 samples/sec accuracy=78.845339 loss=0.785726 lr=0.007707 Epoch[031] Batch [2999]/[3760] Speed: 93.610479 samples/sec accuracy=78.829688 loss=0.786169 lr=0.007705 Epoch[031] Batch [3049]/[3760] Speed: 94.125309 samples/sec accuracy=78.814549 loss=0.786955 lr=0.007703 Epoch[031] Batch [3099]/[3760] Speed: 93.673183 samples/sec accuracy=78.783266 loss=0.787803 lr=0.007702 Epoch[031] Batch [3149]/[3760] Speed: 93.802707 samples/sec accuracy=78.742063 loss=0.788946 lr=0.007700 Epoch[031] Batch [3199]/[3760] Speed: 92.837173 samples/sec accuracy=78.714355 loss=0.789737 lr=0.007698 Epoch[031] Batch [3249]/[3760] Speed: 94.212625 samples/sec accuracy=78.691346 loss=0.790460 lr=0.007696 Epoch[031] Batch [3299]/[3760] Speed: 94.539596 samples/sec accuracy=78.671402 loss=0.790811 lr=0.007695 Epoch[031] Batch [3349]/[3760] Speed: 93.625725 samples/sec accuracy=78.649254 loss=0.791380 lr=0.007693 Epoch[031] 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acc-top5=85.020833 Batch [0199]/[0303]: acc-top1=65.726562 acc-top5=86.234375 Batch [0249]/[0303]: acc-top1=65.287500 acc-top5=85.800000 Batch [0299]/[0303]: acc-top1=64.463542 acc-top5=85.583333 [Epoch 031] training: accuracy=78.538065 loss=0.795995 [Epoch 031] speed: 93 samples/sec time cost: 2791.620425 [Epoch 031] validation: acc-top1=64.449257 acc-top5=85.571370 loss=2.101930 Epoch[032] Batch [0049]/[3759] Speed: 65.032365 samples/sec accuracy=79.375000 loss=0.751400 lr=0.007677 Epoch[032] Batch [0099]/[3759] Speed: 93.377790 samples/sec accuracy=79.796875 loss=0.728794 lr=0.007675 Epoch[032] Batch [0149]/[3759] Speed: 93.375714 samples/sec accuracy=80.041667 loss=0.725711 lr=0.007673 Epoch[032] Batch [0199]/[3759] Speed: 94.054889 samples/sec accuracy=80.335938 loss=0.715069 lr=0.007671 Epoch[032] Batch [0249]/[3759] Speed: 93.970702 samples/sec accuracy=80.362500 loss=0.714556 lr=0.007670 Epoch[032] Batch [0299]/[3759] Speed: 94.042759 samples/sec accuracy=80.229167 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accuracy=78.899802 loss=0.781068 lr=0.007566 Epoch[032] Batch [3199]/[3759] Speed: 93.381856 samples/sec accuracy=78.889160 loss=0.781690 lr=0.007565 Epoch[032] Batch [3249]/[3759] Speed: 93.363734 samples/sec accuracy=78.868269 loss=0.782817 lr=0.007563 Epoch[032] Batch [3299]/[3759] Speed: 94.061906 samples/sec accuracy=78.857955 loss=0.783089 lr=0.007561 Epoch[032] Batch [3349]/[3759] Speed: 93.688582 samples/sec accuracy=78.858209 loss=0.783276 lr=0.007559 Epoch[032] Batch [3399]/[3759] Speed: 93.666561 samples/sec accuracy=78.864890 loss=0.783284 lr=0.007557 Epoch[032] Batch [3449]/[3759] Speed: 94.193429 samples/sec accuracy=78.836957 loss=0.784209 lr=0.007556 Epoch[032] Batch [3499]/[3759] Speed: 93.818909 samples/sec accuracy=78.829018 loss=0.784619 lr=0.007554 Epoch[032] Batch [3549]/[3759] Speed: 93.518700 samples/sec accuracy=78.810299 loss=0.785236 lr=0.007552 Epoch[032] Batch [3599]/[3759] Speed: 93.465853 samples/sec accuracy=78.776042 loss=0.786342 lr=0.007550 Epoch[032] Batch [3649]/[3759] Speed: 93.018228 samples/sec accuracy=78.770120 loss=0.786918 lr=0.007548 Epoch[032] Batch [3699]/[3759] Speed: 94.456524 samples/sec accuracy=78.759291 loss=0.787333 lr=0.007547 Epoch[032] Batch [3749]/[3759] Speed: 106.775984 samples/sec accuracy=78.732917 loss=0.787935 lr=0.007545 Batch [0049]/[0303]: acc-top1=63.843750 acc-top5=84.406250 Batch [0099]/[0303]: acc-top1=62.265625 acc-top5=84.031250 Batch [0149]/[0303]: acc-top1=63.343750 acc-top5=84.864583 Batch [0199]/[0303]: acc-top1=65.671875 acc-top5=86.148438 Batch [0249]/[0303]: acc-top1=65.031250 acc-top5=85.731250 Batch [0299]/[0303]: acc-top1=64.572917 acc-top5=85.750000 [Epoch 032] training: accuracy=78.728551 loss=0.788030 [Epoch 032] speed: 93 samples/sec time cost: 2791.527144 [Epoch 032] validation: acc-top1=64.573020 acc-top5=85.731229 loss=2.114828 Epoch[033] Batch [0049]/[3760] Speed: 64.482236 samples/sec accuracy=79.718750 loss=0.720575 lr=0.007543 Epoch[033] Batch [0099]/[3760] Speed: 93.732423 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lr=0.007421 Epoch[033] Batch [3449]/[3760] Speed: 94.309026 samples/sec accuracy=79.176630 loss=0.773734 lr=0.007419 Epoch[033] Batch [3499]/[3760] Speed: 93.926598 samples/sec accuracy=79.151786 loss=0.774303 lr=0.007417 Epoch[033] Batch [3549]/[3760] Speed: 93.757862 samples/sec accuracy=79.126320 loss=0.775210 lr=0.007416 Epoch[033] Batch [3599]/[3760] Speed: 93.608952 samples/sec accuracy=79.105903 loss=0.775876 lr=0.007414 Epoch[033] Batch [3649]/[3760] Speed: 93.671340 samples/sec accuracy=79.097603 loss=0.776378 lr=0.007412 Epoch[033] Batch [3699]/[3760] Speed: 93.206744 samples/sec accuracy=79.073057 loss=0.777518 lr=0.007410 Epoch[033] Batch [3749]/[3760] Speed: 105.384179 samples/sec accuracy=79.060000 loss=0.778251 lr=0.007408 Batch [0049]/[0303]: acc-top1=65.062500 acc-top5=84.000000 Batch [0099]/[0303]: acc-top1=62.218750 acc-top5=83.875000 Batch [0149]/[0303]: acc-top1=63.072917 acc-top5=84.583333 Batch [0199]/[0303]: acc-top1=65.734375 acc-top5=85.906250 Batch [0249]/[0303]: acc-top1=65.368750 acc-top5=85.581250 Batch [0299]/[0303]: acc-top1=64.718750 acc-top5=85.572917 [Epoch 033] training: accuracy=79.061669 loss=0.778419 [Epoch 033] speed: 93 samples/sec time cost: 2791.473039 [Epoch 033] validation: acc-top1=64.722566 acc-top5=85.571370 loss=2.185577 Epoch[034] Batch [0049]/[3759] Speed: 64.147148 samples/sec accuracy=81.906250 loss=0.673624 lr=0.007406 Epoch[034] Batch [0099]/[3759] Speed: 92.788002 samples/sec accuracy=82.062500 loss=0.683686 lr=0.007404 Epoch[034] Batch [0149]/[3759] Speed: 93.661859 samples/sec accuracy=82.229167 loss=0.684485 lr=0.007402 Epoch[034] Batch [0199]/[3759] Speed: 94.475220 samples/sec accuracy=81.640625 loss=0.697493 lr=0.007401 Epoch[034] Batch [0249]/[3759] Speed: 93.340312 samples/sec accuracy=81.400000 loss=0.696783 lr=0.007399 Epoch[034] Batch [0299]/[3759] Speed: 93.749784 samples/sec accuracy=81.197917 loss=0.703721 lr=0.007397 Epoch[034] Batch [0349]/[3759] Speed: 93.215725 samples/sec accuracy=81.129464 loss=0.703916 lr=0.007395 Epoch[034] Batch [0399]/[3759] Speed: 93.411692 samples/sec accuracy=81.035156 loss=0.705166 lr=0.007393 Epoch[034] Batch [0449]/[3759] Speed: 93.826669 samples/sec accuracy=81.055556 loss=0.707071 lr=0.007391 Epoch[034] Batch [0499]/[3759] Speed: 93.487437 samples/sec accuracy=80.965625 loss=0.710412 lr=0.007390 Epoch[034] Batch [0549]/[3759] Speed: 94.837388 samples/sec accuracy=80.784091 loss=0.712841 lr=0.007388 Epoch[034] Batch [0599]/[3759] Speed: 93.768428 samples/sec accuracy=80.791667 loss=0.713320 lr=0.007386 Epoch[034] Batch [0649]/[3759] Speed: 93.520009 samples/sec accuracy=80.824519 loss=0.712383 lr=0.007384 Epoch[034] Batch [0699]/[3759] Speed: 94.570180 samples/sec accuracy=80.649554 loss=0.717566 lr=0.007382 Epoch[034] Batch [0749]/[3759] Speed: 93.462528 samples/sec accuracy=80.550000 loss=0.720246 lr=0.007380 Epoch[034] Batch [0799]/[3759] Speed: 93.135659 samples/sec accuracy=80.521484 loss=0.720772 lr=0.007379 Epoch[034] 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accuracy=80.038462 loss=0.735357 lr=0.007360 Epoch[034] Batch [1349]/[3759] Speed: 94.202513 samples/sec accuracy=80.006944 loss=0.735564 lr=0.007358 Epoch[034] Batch [1399]/[3759] Speed: 94.124502 samples/sec accuracy=79.952009 loss=0.736132 lr=0.007357 Epoch[034] Batch [1449]/[3759] Speed: 93.883992 samples/sec accuracy=79.943966 loss=0.736684 lr=0.007355 Epoch[034] Batch [1499]/[3759] Speed: 93.085183 samples/sec accuracy=79.945833 loss=0.736746 lr=0.007353 Epoch[034] Batch [1549]/[3759] Speed: 93.619743 samples/sec accuracy=79.926411 loss=0.737187 lr=0.007351 Epoch[034] Batch [1599]/[3759] Speed: 94.312878 samples/sec accuracy=79.928711 loss=0.737281 lr=0.007349 Epoch[034] Batch [1649]/[3759] Speed: 93.926976 samples/sec accuracy=79.893939 loss=0.738947 lr=0.007347 Epoch[034] Batch [1699]/[3759] Speed: 93.996506 samples/sec accuracy=79.900735 loss=0.738860 lr=0.007345 Epoch[034] Batch [1749]/[3759] Speed: 93.503700 samples/sec accuracy=79.899107 loss=0.739076 lr=0.007344 Epoch[034] Batch [1799]/[3759] Speed: 94.183514 samples/sec accuracy=79.913194 loss=0.738905 lr=0.007342 Epoch[034] Batch [1849]/[3759] Speed: 94.024696 samples/sec accuracy=79.901182 loss=0.738935 lr=0.007340 Epoch[034] Batch [1899]/[3759] Speed: 93.871310 samples/sec accuracy=79.881579 loss=0.739670 lr=0.007338 Epoch[034] Batch [1949]/[3759] Speed: 94.007170 samples/sec accuracy=79.850160 loss=0.740281 lr=0.007336 Epoch[034] Batch [1999]/[3759] Speed: 93.838019 samples/sec accuracy=79.846875 loss=0.740111 lr=0.007334 Epoch[034] Batch [2049]/[3759] Speed: 93.708793 samples/sec accuracy=79.809451 loss=0.741514 lr=0.007333 Epoch[034] Batch [2099]/[3759] Speed: 93.685091 samples/sec accuracy=79.765625 loss=0.743256 lr=0.007331 Epoch[034] Batch [2149]/[3759] Speed: 93.119167 samples/sec accuracy=79.756541 loss=0.744236 lr=0.007329 Epoch[034] Batch [2199]/[3759] Speed: 94.085251 samples/sec accuracy=79.727273 loss=0.745007 lr=0.007327 Epoch[034] Batch [2249]/[3759] Speed: 94.236392 samples/sec accuracy=79.713889 loss=0.746211 lr=0.007325 Epoch[034] Batch [2299]/[3759] Speed: 93.586020 samples/sec accuracy=79.688859 loss=0.747611 lr=0.007323 Epoch[034] Batch [2349]/[3759] Speed: 94.505462 samples/sec accuracy=79.668218 loss=0.748649 lr=0.007321 Epoch[034] Batch [2399]/[3759] Speed: 93.995786 samples/sec accuracy=79.633464 loss=0.749700 lr=0.007320 Epoch[034] Batch [2449]/[3759] Speed: 93.502686 samples/sec accuracy=79.607143 loss=0.751037 lr=0.007318 Epoch[034] Batch [2499]/[3759] Speed: 93.825490 samples/sec accuracy=79.584375 loss=0.752000 lr=0.007316 Epoch[034] Batch [2549]/[3759] Speed: 93.452313 samples/sec accuracy=79.586397 loss=0.752166 lr=0.007314 Epoch[034] Batch [2599]/[3759] Speed: 94.068396 samples/sec accuracy=79.569111 loss=0.753392 lr=0.007312 Epoch[034] Batch [2649]/[3759] Speed: 93.617189 samples/sec accuracy=79.570165 loss=0.753596 lr=0.007310 Epoch[034] Batch [2699]/[3759] Speed: 94.619858 samples/sec accuracy=79.537616 loss=0.754520 lr=0.007308 Epoch[034] Batch [2749]/[3759] Speed: 94.182009 samples/sec accuracy=79.510227 loss=0.755145 lr=0.007307 Epoch[034] Batch [2799]/[3759] Speed: 93.931632 samples/sec accuracy=79.516741 loss=0.755360 lr=0.007305 Epoch[034] Batch [2849]/[3759] Speed: 94.043641 samples/sec accuracy=79.508224 loss=0.755667 lr=0.007303 Epoch[034] Batch [2899]/[3759] Speed: 93.890206 samples/sec accuracy=79.472522 loss=0.756700 lr=0.007301 Epoch[034] Batch [2949]/[3759] Speed: 93.679166 samples/sec accuracy=79.474047 loss=0.756991 lr=0.007299 Epoch[034] Batch [2999]/[3759] Speed: 93.931654 samples/sec accuracy=79.469792 loss=0.757020 lr=0.007297 Epoch[034] Batch [3049]/[3759] Speed: 94.546233 samples/sec accuracy=79.474385 loss=0.756858 lr=0.007295 Epoch[034] Batch [3099]/[3759] Speed: 94.196506 samples/sec accuracy=79.474798 loss=0.757102 lr=0.007294 Epoch[034] Batch [3149]/[3759] Speed: 93.933605 samples/sec accuracy=79.456845 loss=0.757769 lr=0.007292 Epoch[034] Batch [3199]/[3759] Speed: 93.082436 samples/sec accuracy=79.446289 loss=0.758184 lr=0.007290 Epoch[034] Batch [3249]/[3759] Speed: 93.894101 samples/sec accuracy=79.438462 loss=0.758667 lr=0.007288 Epoch[034] Batch [3299]/[3759] Speed: 93.729575 samples/sec accuracy=79.431345 loss=0.759051 lr=0.007286 Epoch[034] Batch [3349]/[3759] Speed: 93.648546 samples/sec accuracy=79.408582 loss=0.759819 lr=0.007284 Epoch[034] Batch [3399]/[3759] Speed: 94.071972 samples/sec accuracy=79.373621 loss=0.760994 lr=0.007282 Epoch[034] Batch [3449]/[3759] Speed: 93.849673 samples/sec accuracy=79.359601 loss=0.761519 lr=0.007281 Epoch[034] Batch [3499]/[3759] Speed: 93.492815 samples/sec accuracy=79.337500 loss=0.762451 lr=0.007279 Epoch[034] Batch [3549]/[3759] Speed: 93.839124 samples/sec accuracy=79.327025 loss=0.762880 lr=0.007277 Epoch[034] Batch [3599]/[3759] Speed: 93.090083 samples/sec accuracy=79.337674 loss=0.762749 lr=0.007275 Epoch[034] Batch [3649]/[3759] Speed: 93.130950 samples/sec accuracy=79.325342 loss=0.763203 lr=0.007273 Epoch[034] Batch [3699]/[3759] Speed: 93.194460 samples/sec accuracy=79.304899 loss=0.764085 lr=0.007271 Epoch[034] Batch [3749]/[3759] Speed: 107.507803 samples/sec accuracy=79.292500 loss=0.764707 lr=0.007269 Batch [0049]/[0303]: acc-top1=62.812500 acc-top5=84.406250 Batch [0099]/[0303]: acc-top1=60.265625 acc-top5=83.328125 Batch [0149]/[0303]: acc-top1=62.010417 acc-top5=84.187500 Batch [0199]/[0303]: acc-top1=65.054688 acc-top5=85.453125 Batch [0249]/[0303]: acc-top1=64.762500 acc-top5=85.337500 Batch [0299]/[0303]: acc-top1=64.255208 acc-top5=85.307292 [Epoch 034] training: accuracy=79.290120 loss=0.764679 [Epoch 034] speed: 93 samples/sec time cost: 2793.321697 [Epoch 034] validation: acc-top1=64.227517 acc-top5=85.287748 loss=2.212637 Epoch[035] Batch [0049]/[3760] Speed: 65.636027 samples/sec accuracy=80.562500 loss=0.684376 lr=0.007267 Epoch[035] Batch [0099]/[3760] Speed: 94.052790 samples/sec accuracy=81.031250 loss=0.683350 lr=0.007265 Epoch[035] Batch [0149]/[3760] Speed: 93.309016 samples/sec accuracy=81.052083 loss=0.691668 lr=0.007264 Epoch[035] Batch [0199]/[3760] Speed: 94.515459 samples/sec accuracy=80.796875 loss=0.704489 lr=0.007262 Epoch[035] Batch [0249]/[3760] Speed: 93.613732 samples/sec accuracy=80.943750 loss=0.703810 lr=0.007260 Epoch[035] Batch [0299]/[3760] Speed: 93.805809 samples/sec accuracy=80.953125 loss=0.701513 lr=0.007258 Epoch[035] Batch [0349]/[3760] Speed: 93.917420 samples/sec accuracy=81.008929 loss=0.699226 lr=0.007256 Epoch[035] Batch [0399]/[3760] Speed: 94.725905 samples/sec accuracy=81.042969 loss=0.699051 lr=0.007254 Epoch[035] Batch [0449]/[3760] Speed: 94.229344 samples/sec accuracy=81.097222 loss=0.696408 lr=0.007252 Epoch[035] Batch [0499]/[3760] Speed: 93.444488 samples/sec accuracy=81.028125 loss=0.695851 lr=0.007250 Epoch[035] Batch [0549]/[3760] Speed: 93.824966 samples/sec accuracy=81.034091 loss=0.695988 lr=0.007249 Epoch[035] Batch [0599]/[3760] Speed: 94.123332 samples/sec accuracy=81.041667 loss=0.697743 lr=0.007247 Epoch[035] Batch [0649]/[3760] Speed: 93.152345 samples/sec accuracy=80.985577 loss=0.699511 lr=0.007245 Epoch[035] Batch [0699]/[3760] Speed: 93.969787 samples/sec accuracy=81.015625 loss=0.699128 lr=0.007243 Epoch[035] Batch [0749]/[3760] Speed: 94.496995 samples/sec accuracy=80.993750 loss=0.700540 lr=0.007241 Epoch[035] Batch [0799]/[3760] Speed: 93.617824 samples/sec accuracy=81.033203 loss=0.699279 lr=0.007239 Epoch[035] Batch [0849]/[3760] Speed: 93.184175 samples/sec accuracy=81.040441 loss=0.700003 lr=0.007237 Epoch[035] Batch [0899]/[3760] Speed: 93.647432 samples/sec accuracy=80.996528 loss=0.700213 lr=0.007236 Epoch[035] Batch [0949]/[3760] Speed: 94.141486 samples/sec accuracy=80.914474 loss=0.702328 lr=0.007234 Epoch[035] Batch [0999]/[3760] Speed: 93.283598 samples/sec accuracy=80.862500 loss=0.704138 lr=0.007232 Epoch[035] Batch [1049]/[3760] Speed: 94.592422 samples/sec accuracy=80.846726 loss=0.706008 lr=0.007230 Epoch[035] Batch [1099]/[3760] Speed: 94.073183 samples/sec accuracy=80.774148 loss=0.710007 lr=0.007228 Epoch[035] Batch [1149]/[3760] Speed: 93.487947 samples/sec accuracy=80.730978 loss=0.711140 lr=0.007226 Epoch[035] Batch [1199]/[3760] Speed: 93.468893 samples/sec accuracy=80.679688 loss=0.712978 lr=0.007224 Epoch[035] Batch [1249]/[3760] Speed: 93.237674 samples/sec accuracy=80.645000 loss=0.714289 lr=0.007222 Epoch[035] Batch [1299]/[3760] Speed: 93.034261 samples/sec accuracy=80.606971 loss=0.716162 lr=0.007221 Epoch[035] Batch [1349]/[3760] Speed: 94.811006 samples/sec accuracy=80.564815 loss=0.717467 lr=0.007219 Epoch[035] Batch [1399]/[3760] Speed: 93.609823 samples/sec accuracy=80.540179 loss=0.717958 lr=0.007217 Epoch[035] Batch [1449]/[3760] Speed: 92.995650 samples/sec accuracy=80.522629 loss=0.718235 lr=0.007215 Epoch[035] Batch [1499]/[3760] Speed: 94.453831 samples/sec accuracy=80.483333 loss=0.719249 lr=0.007213 Epoch[035] Batch [1549]/[3760] Speed: 93.639419 samples/sec accuracy=80.465726 loss=0.720072 lr=0.007211 Epoch[035] Batch [1599]/[3760] Speed: 93.275395 samples/sec accuracy=80.469727 loss=0.720828 lr=0.007209 Epoch[035] Batch [1649]/[3760] Speed: 94.050337 samples/sec accuracy=80.453598 loss=0.721314 lr=0.007207 Epoch[035] Batch [1699]/[3760] Speed: 93.929221 samples/sec accuracy=80.431985 loss=0.723035 lr=0.007206 Epoch[035] Batch [1749]/[3760] Speed: 93.936912 samples/sec accuracy=80.404464 loss=0.723848 lr=0.007204 Epoch[035] Batch [1799]/[3760] Speed: 93.100347 samples/sec accuracy=80.387153 loss=0.724706 lr=0.007202 Epoch[035] Batch [1849]/[3760] Speed: 93.451363 samples/sec accuracy=80.360642 loss=0.725839 lr=0.007200 Epoch[035] Batch [1899]/[3760] Speed: 92.376024 samples/sec accuracy=80.331414 loss=0.726747 lr=0.007198 Epoch[035] Batch [1949]/[3760] Speed: 94.794626 samples/sec accuracy=80.318109 loss=0.727232 lr=0.007196 Epoch[035] Batch [1999]/[3760] Speed: 93.933786 samples/sec accuracy=80.310937 loss=0.727527 lr=0.007194 Epoch[035] Batch [2049]/[3760] Speed: 93.675372 samples/sec accuracy=80.282012 loss=0.728285 lr=0.007192 Epoch[035] Batch [2099]/[3760] Speed: 92.888784 samples/sec accuracy=80.275298 loss=0.728805 lr=0.007191 Epoch[035] Batch [2149]/[3760] Speed: 93.431087 samples/sec accuracy=80.235465 loss=0.729182 lr=0.007189 Epoch[035] Batch [2199]/[3760] Speed: 93.513568 samples/sec accuracy=80.215199 loss=0.729888 lr=0.007187 Epoch[035] Batch [2249]/[3760] Speed: 94.068982 samples/sec accuracy=80.175000 loss=0.731257 lr=0.007185 Epoch[035] Batch [2299]/[3760] Speed: 93.862656 samples/sec accuracy=80.134511 loss=0.732363 lr=0.007183 Epoch[035] Batch [2349]/[3760] Speed: 94.509537 samples/sec accuracy=80.113697 loss=0.733073 lr=0.007181 Epoch[035] Batch [2399]/[3760] Speed: 94.067083 samples/sec accuracy=80.087240 loss=0.734189 lr=0.007179 Epoch[035] Batch [2449]/[3760] Speed: 94.776584 samples/sec accuracy=80.073342 loss=0.734815 lr=0.007177 Epoch[035] Batch [2499]/[3760] Speed: 93.239931 samples/sec accuracy=80.031250 loss=0.736545 lr=0.007176 Epoch[035] Batch [2549]/[3760] Speed: 93.217226 samples/sec accuracy=79.995098 loss=0.737880 lr=0.007174 Epoch[035] Batch [2599]/[3760] Speed: 94.099651 samples/sec accuracy=79.992788 loss=0.738083 lr=0.007172 Epoch[035] Batch [2649]/[3760] Speed: 93.974191 samples/sec accuracy=79.974057 loss=0.738746 lr=0.007170 Epoch[035] Batch [2699]/[3760] Speed: 93.999305 samples/sec accuracy=79.986690 loss=0.738462 lr=0.007168 Epoch[035] Batch [2749]/[3760] Speed: 93.350762 samples/sec accuracy=80.002273 loss=0.738381 lr=0.007166 Epoch[035] Batch [2799]/[3760] Speed: 93.675329 samples/sec accuracy=79.995536 loss=0.738840 lr=0.007164 Epoch[035] Batch [2849]/[3760] Speed: 94.565410 samples/sec accuracy=79.957237 loss=0.739947 lr=0.007162 Epoch[035] Batch [2899]/[3760] Speed: 94.069918 samples/sec accuracy=79.960668 loss=0.740075 lr=0.007160 Epoch[035] Batch [2949]/[3760] Speed: 93.059328 samples/sec accuracy=79.957627 loss=0.740594 lr=0.007159 Epoch[035] Batch [2999]/[3760] Speed: 93.766398 samples/sec accuracy=79.952604 loss=0.741134 lr=0.007157 Epoch[035] Batch [3049]/[3760] Speed: 93.808679 samples/sec accuracy=79.923668 loss=0.742076 lr=0.007155 Epoch[035] Batch [3099]/[3760] Speed: 93.903805 samples/sec accuracy=79.882056 loss=0.743469 lr=0.007153 Epoch[035] Batch [3149]/[3760] Speed: 95.304472 samples/sec accuracy=79.871528 loss=0.743840 lr=0.007151 Epoch[035] Batch [3199]/[3760] Speed: 93.977392 samples/sec accuracy=79.867188 loss=0.744018 lr=0.007149 Epoch[035] Batch [3249]/[3760] Speed: 93.866517 samples/sec accuracy=79.875000 loss=0.744346 lr=0.007147 Epoch[035] Batch [3299]/[3760] Speed: 93.750962 samples/sec accuracy=79.880208 loss=0.744275 lr=0.007145 Epoch[035] Batch [3349]/[3760] Speed: 93.178530 samples/sec accuracy=79.868937 loss=0.744619 lr=0.007144 Epoch[035] Batch [3399]/[3760] Speed: 93.479945 samples/sec accuracy=79.839154 loss=0.745270 lr=0.007142 Epoch[035] Batch [3449]/[3760] Speed: 93.977372 samples/sec accuracy=79.801630 loss=0.746789 lr=0.007140 Epoch[035] Batch [3499]/[3760] Speed: 93.855565 samples/sec accuracy=79.779911 loss=0.747452 lr=0.007138 Epoch[035] Batch [3549]/[3760] Speed: 94.056065 samples/sec accuracy=79.765845 loss=0.748251 lr=0.007136 Epoch[035] Batch [3599]/[3760] Speed: 93.684415 samples/sec accuracy=79.761285 loss=0.748455 lr=0.007134 Epoch[035] Batch [3649]/[3760] Speed: 93.615190 samples/sec accuracy=79.747432 loss=0.748690 lr=0.007132 Epoch[035] Batch [3699]/[3760] Speed: 92.671193 samples/sec accuracy=79.737331 loss=0.749124 lr=0.007130 Epoch[035] Batch [3749]/[3760] Speed: 107.063937 samples/sec accuracy=79.721667 loss=0.749620 lr=0.007128 Batch [0049]/[0303]: acc-top1=65.000000 acc-top5=85.312500 Batch [0099]/[0303]: acc-top1=62.718750 acc-top5=84.390625 Batch [0149]/[0303]: acc-top1=63.375000 acc-top5=84.500000 Batch [0199]/[0303]: acc-top1=65.882812 acc-top5=85.937500 Batch [0249]/[0303]: acc-top1=65.225000 acc-top5=85.581250 Batch [0299]/[0303]: acc-top1=64.854167 acc-top5=85.531250 [Epoch 035] training: accuracy=79.724900 loss=0.749564 [Epoch 035] speed: 93 samples/sec time cost: 2792.740194 [Epoch 035] validation: acc-top1=64.846328 acc-top5=85.519802 loss=2.155185 Epoch[036] Batch [0049]/[3760] Speed: 64.887078 samples/sec accuracy=80.906250 loss=0.707926 lr=0.007126 Epoch[036] Batch [0099]/[3760] Speed: 93.913261 samples/sec accuracy=81.609375 loss=0.682496 lr=0.007124 Epoch[036] Batch [0149]/[3760] Speed: 94.467923 samples/sec accuracy=81.645833 loss=0.685446 lr=0.007122 Epoch[036] Batch [0199]/[3760] Speed: 93.196916 samples/sec accuracy=81.625000 loss=0.680706 lr=0.007120 Epoch[036] Batch [0249]/[3760] Speed: 93.811499 samples/sec accuracy=81.400000 loss=0.685876 lr=0.007119 Epoch[036] Batch [0299]/[3760] Speed: 93.012288 samples/sec accuracy=81.390625 loss=0.682676 lr=0.007117 Epoch[036] Batch [0349]/[3760] Speed: 93.220919 samples/sec accuracy=81.486607 loss=0.680700 lr=0.007115 Epoch[036] Batch [0399]/[3760] Speed: 95.101881 samples/sec accuracy=81.429688 loss=0.682196 lr=0.007113 Epoch[036] Batch [0449]/[3760] Speed: 93.351644 samples/sec accuracy=81.375000 loss=0.682992 lr=0.007111 Epoch[036] Batch [0499]/[3760] Speed: 93.752317 samples/sec accuracy=81.375000 loss=0.684505 lr=0.007109 Epoch[036] Batch [0549]/[3760] Speed: 93.640426 samples/sec accuracy=81.357955 loss=0.685725 lr=0.007107 Epoch[036] Batch [0599]/[3760] Speed: 93.662518 samples/sec accuracy=81.276042 loss=0.688831 lr=0.007105 Epoch[036] Batch [0649]/[3760] Speed: 93.637218 samples/sec accuracy=81.228365 loss=0.689949 lr=0.007103 Epoch[036] Batch [0699]/[3760] Speed: 94.415546 samples/sec accuracy=81.145089 loss=0.693856 lr=0.007102 Epoch[036] Batch [0749]/[3760] Speed: 94.306995 samples/sec accuracy=81.127083 loss=0.695558 lr=0.007100 Epoch[036] Batch [0799]/[3760] Speed: 94.455639 samples/sec accuracy=81.058594 loss=0.696625 lr=0.007098 Epoch[036] Batch [0849]/[3760] Speed: 94.680470 samples/sec accuracy=81.137868 loss=0.695193 lr=0.007096 Epoch[036] 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accuracy=80.956019 loss=0.700829 lr=0.007077 Epoch[036] Batch [1399]/[3760] Speed: 93.835502 samples/sec accuracy=80.948661 loss=0.701586 lr=0.007075 Epoch[036] Batch [1449]/[3760] Speed: 93.460638 samples/sec accuracy=80.933190 loss=0.703531 lr=0.007073 Epoch[036] Batch [1499]/[3760] Speed: 93.550779 samples/sec accuracy=80.951042 loss=0.703498 lr=0.007071 Epoch[036] Batch [1549]/[3760] Speed: 93.188286 samples/sec accuracy=80.978831 loss=0.702774 lr=0.007069 Epoch[036] Batch [1599]/[3760] Speed: 95.138203 samples/sec accuracy=80.909180 loss=0.705086 lr=0.007067 Epoch[036] Batch [1649]/[3760] Speed: 93.567236 samples/sec accuracy=80.858902 loss=0.707629 lr=0.007065 Epoch[036] Batch [1699]/[3760] Speed: 93.715031 samples/sec accuracy=80.831801 loss=0.708234 lr=0.007064 Epoch[036] Batch [1749]/[3760] Speed: 93.858302 samples/sec accuracy=80.798214 loss=0.709031 lr=0.007062 Epoch[036] Batch [1799]/[3760] Speed: 93.395715 samples/sec accuracy=80.796007 loss=0.708834 lr=0.007060 Epoch[036] Batch [1849]/[3760] Speed: 93.125424 samples/sec accuracy=80.817568 loss=0.708619 lr=0.007058 Epoch[036] Batch [1899]/[3760] Speed: 94.924687 samples/sec accuracy=80.819901 loss=0.709334 lr=0.007056 Epoch[036] Batch [1949]/[3760] Speed: 93.893487 samples/sec accuracy=80.787660 loss=0.710522 lr=0.007054 Epoch[036] Batch [1999]/[3760] Speed: 93.759288 samples/sec accuracy=80.793750 loss=0.710705 lr=0.007052 Epoch[036] Batch [2049]/[3760] Speed: 93.597777 samples/sec accuracy=80.764482 loss=0.711894 lr=0.007050 Epoch[036] Batch [2099]/[3760] Speed: 93.500188 samples/sec accuracy=80.747024 loss=0.713054 lr=0.007048 Epoch[036] Batch [2149]/[3760] Speed: 93.393118 samples/sec accuracy=80.762355 loss=0.713473 lr=0.007046 Epoch[036] Batch [2199]/[3760] Speed: 94.333984 samples/sec accuracy=80.739347 loss=0.713819 lr=0.007044 Epoch[036] Batch [2249]/[3760] Speed: 92.975927 samples/sec accuracy=80.701389 loss=0.715385 lr=0.007043 Epoch[036] Batch [2299]/[3760] Speed: 94.650173 samples/sec accuracy=80.669837 loss=0.716318 lr=0.007041 Epoch[036] Batch [2349]/[3760] Speed: 94.251264 samples/sec accuracy=80.629654 loss=0.717476 lr=0.007039 Epoch[036] Batch [2399]/[3760] Speed: 94.118878 samples/sec accuracy=80.619792 loss=0.718134 lr=0.007037 Epoch[036] Batch [2449]/[3760] Speed: 93.155354 samples/sec accuracy=80.608418 loss=0.718400 lr=0.007035 Epoch[036] Batch [2499]/[3760] Speed: 95.332653 samples/sec accuracy=80.570625 loss=0.719698 lr=0.007033 Epoch[036] Batch [2549]/[3760] Speed: 93.169909 samples/sec accuracy=80.555147 loss=0.720159 lr=0.007031 Epoch[036] Batch [2599]/[3760] Speed: 93.692556 samples/sec accuracy=80.506611 loss=0.721135 lr=0.007029 Epoch[036] Batch [2649]/[3760] Speed: 94.328816 samples/sec accuracy=80.498231 loss=0.721612 lr=0.007027 Epoch[036] Batch [2699]/[3760] Speed: 93.740505 samples/sec accuracy=80.460648 loss=0.722692 lr=0.007025 Epoch[036] Batch [2749]/[3760] Speed: 93.866157 samples/sec accuracy=80.434091 loss=0.723377 lr=0.007023 Epoch[036] Batch [2799]/[3760] Speed: 95.048276 samples/sec accuracy=80.428013 loss=0.723842 lr=0.007022 Epoch[036] Batch [2849]/[3760] Speed: 92.805669 samples/sec accuracy=80.396930 loss=0.724606 lr=0.007020 Epoch[036] Batch [2899]/[3760] Speed: 93.066531 samples/sec accuracy=80.381466 loss=0.725225 lr=0.007018 Epoch[036] Batch [2949]/[3760] Speed: 93.342657 samples/sec accuracy=80.372881 loss=0.725756 lr=0.007016 Epoch[036] Batch [2999]/[3760] Speed: 93.230169 samples/sec accuracy=80.344792 loss=0.726913 lr=0.007014 Epoch[036] Batch [3049]/[3760] Speed: 94.004312 samples/sec accuracy=80.332480 loss=0.727550 lr=0.007012 Epoch[036] Batch [3099]/[3760] Speed: 93.850620 samples/sec accuracy=80.287298 loss=0.728998 lr=0.007010 Epoch[036] Batch [3149]/[3760] Speed: 93.575667 samples/sec accuracy=80.257440 loss=0.729953 lr=0.007008 Epoch[036] Batch [3199]/[3760] Speed: 93.834847 samples/sec accuracy=80.267578 loss=0.729848 lr=0.007006 Epoch[036] Batch [3249]/[3760] Speed: 93.182349 samples/sec accuracy=80.250962 loss=0.730441 lr=0.007004 Epoch[036] Batch [3299]/[3760] Speed: 94.782233 samples/sec accuracy=80.250947 loss=0.730832 lr=0.007002 Epoch[036] Batch [3349]/[3760] Speed: 93.881951 samples/sec accuracy=80.252332 loss=0.731004 lr=0.007001 Epoch[036] Batch [3399]/[3760] Speed: 93.933826 samples/sec accuracy=80.220129 loss=0.732231 lr=0.006999 Epoch[036] Batch [3449]/[3760] Speed: 93.263937 samples/sec accuracy=80.197917 loss=0.733230 lr=0.006997 Epoch[036] Batch [3499]/[3760] Speed: 93.618797 samples/sec accuracy=80.162500 loss=0.734254 lr=0.006995 Epoch[036] Batch [3549]/[3760] Speed: 95.126240 samples/sec accuracy=80.150528 loss=0.734718 lr=0.006993 Epoch[036] Batch [3599]/[3760] Speed: 94.237996 samples/sec accuracy=80.123264 loss=0.736036 lr=0.006991 Epoch[036] Batch [3649]/[3760] Speed: 93.613769 samples/sec accuracy=80.094606 loss=0.736640 lr=0.006989 Epoch[036] Batch [3699]/[3760] Speed: 93.505968 samples/sec accuracy=80.077280 loss=0.736968 lr=0.006987 Epoch[036] Batch [3749]/[3760] Speed: 105.039516 samples/sec accuracy=80.087500 loss=0.736798 lr=0.006985 Batch [0049]/[0303]: acc-top1=63.562500 acc-top5=85.468750 Batch [0099]/[0303]: acc-top1=61.890625 acc-top5=85.328125 Batch [0149]/[0303]: acc-top1=62.927083 acc-top5=85.364583 Batch [0199]/[0303]: acc-top1=65.773438 acc-top5=86.562500 Batch [0249]/[0303]: acc-top1=65.325000 acc-top5=86.093750 Batch [0299]/[0303]: acc-top1=64.942708 acc-top5=86.067708 [Epoch 036] training: accuracy=80.082281 loss=0.736960 [Epoch 036] speed: 93 samples/sec time cost: 2792.906552 [Epoch 036] validation: acc-top1=64.918523 acc-top5=86.014851 loss=2.141304 Epoch[037] Batch [0049]/[3759] Speed: 64.721218 samples/sec accuracy=82.125000 loss=0.650374 lr=0.006983 Epoch[037] Batch [0099]/[3759] Speed: 93.432449 samples/sec accuracy=82.093750 loss=0.652316 lr=0.006981 Epoch[037] Batch [0149]/[3759] Speed: 94.127275 samples/sec accuracy=82.364583 loss=0.650550 lr=0.006979 Epoch[037] Batch [0199]/[3759] Speed: 94.516638 samples/sec accuracy=82.460938 loss=0.646316 lr=0.006977 Epoch[037] Batch [0249]/[3759] Speed: 94.166411 samples/sec accuracy=82.218750 loss=0.653825 lr=0.006975 Epoch[037] Batch [0299]/[3759] Speed: 93.445878 samples/sec accuracy=82.208333 loss=0.654797 lr=0.006973 Epoch[037] Batch [0349]/[3759] Speed: 92.756844 samples/sec accuracy=82.263393 loss=0.653718 lr=0.006971 Epoch[037] Batch [0399]/[3759] Speed: 94.320923 samples/sec accuracy=81.824219 loss=0.668217 lr=0.006969 Epoch[037] Batch [0449]/[3759] Speed: 93.953550 samples/sec accuracy=81.819444 loss=0.669653 lr=0.006968 Epoch[037] Batch [0499]/[3759] Speed: 93.991401 samples/sec accuracy=81.756250 loss=0.670190 lr=0.006966 Epoch[037] Batch [0549]/[3759] Speed: 93.588534 samples/sec accuracy=81.622159 loss=0.675091 lr=0.006964 Epoch[037] Batch [0599]/[3759] Speed: 93.758809 samples/sec accuracy=81.500000 loss=0.678638 lr=0.006962 Epoch[037] Batch [0649]/[3759] Speed: 94.430891 samples/sec accuracy=81.497596 loss=0.679194 lr=0.006960 Epoch[037] Batch [0699]/[3759] Speed: 93.706007 samples/sec accuracy=81.513393 loss=0.678691 lr=0.006958 Epoch[037] Batch [0749]/[3759] Speed: 93.384052 samples/sec accuracy=81.433333 loss=0.681294 lr=0.006956 Epoch[037] Batch [0799]/[3759] Speed: 94.129502 samples/sec accuracy=81.443359 loss=0.681171 lr=0.006954 Epoch[037] Batch [0849]/[3759] Speed: 93.385044 samples/sec accuracy=81.463235 loss=0.679622 lr=0.006952 Epoch[037] Batch [0899]/[3759] Speed: 93.126439 samples/sec accuracy=81.440972 loss=0.681039 lr=0.006950 Epoch[037] Batch [0949]/[3759] Speed: 94.559801 samples/sec accuracy=81.445724 loss=0.681296 lr=0.006948 Epoch[037] Batch [0999]/[3759] Speed: 93.111833 samples/sec accuracy=81.414062 loss=0.680724 lr=0.006946 Epoch[037] Batch [1049]/[3759] Speed: 93.038613 samples/sec accuracy=81.410714 loss=0.681477 lr=0.006944 Epoch[037] Batch [1099]/[3759] Speed: 93.746625 samples/sec accuracy=81.363636 loss=0.683325 lr=0.006943 Epoch[037] Batch [1149]/[3759] Speed: 93.206842 samples/sec accuracy=81.369565 loss=0.683480 lr=0.006941 Epoch[037] Batch [1199]/[3759] Speed: 94.204126 samples/sec accuracy=81.341146 loss=0.685099 lr=0.006939 Epoch[037] Batch [1249]/[3759] Speed: 93.405523 samples/sec accuracy=81.287500 loss=0.686727 lr=0.006937 Epoch[037] Batch [1299]/[3759] Speed: 94.479992 samples/sec accuracy=81.332933 loss=0.686695 lr=0.006935 Epoch[037] Batch [1349]/[3759] Speed: 92.862613 samples/sec accuracy=81.259259 loss=0.689137 lr=0.006933 Epoch[037] Batch [1399]/[3759] Speed: 92.975521 samples/sec accuracy=81.270089 loss=0.688521 lr=0.006931 Epoch[037] Batch [1449]/[3759] Speed: 93.805097 samples/sec accuracy=81.275862 loss=0.689279 lr=0.006929 Epoch[037] Batch [1499]/[3759] Speed: 94.058753 samples/sec accuracy=81.248958 loss=0.690308 lr=0.006927 Epoch[037] Batch [1549]/[3759] Speed: 93.726640 samples/sec accuracy=81.223790 loss=0.691625 lr=0.006925 Epoch[037] Batch [1599]/[3759] Speed: 94.291610 samples/sec accuracy=81.195312 loss=0.692689 lr=0.006923 Epoch[037] Batch [1649]/[3759] Speed: 93.628638 samples/sec accuracy=81.171402 loss=0.692711 lr=0.006921 Epoch[037] Batch [1699]/[3759] Speed: 93.026468 samples/sec accuracy=81.123162 loss=0.694368 lr=0.006919 Epoch[037] Batch [1749]/[3759] Speed: 94.377161 samples/sec accuracy=81.101786 loss=0.695363 lr=0.006917 Epoch[037] Batch [1799]/[3759] Speed: 93.854836 samples/sec accuracy=81.078125 loss=0.696067 lr=0.006916 Epoch[037] Batch [1849]/[3759] Speed: 93.174622 samples/sec accuracy=81.054054 loss=0.696587 lr=0.006914 Epoch[037] Batch [1899]/[3759] Speed: 93.021995 samples/sec accuracy=81.026316 loss=0.697752 lr=0.006912 Epoch[037] Batch [1949]/[3759] Speed: 92.678079 samples/sec accuracy=80.997596 loss=0.699047 lr=0.006910 Epoch[037] Batch [1999]/[3759] Speed: 94.317379 samples/sec accuracy=80.986719 loss=0.699491 lr=0.006908 Epoch[037] Batch [2049]/[3759] Speed: 94.012493 samples/sec accuracy=80.942073 loss=0.701636 lr=0.006906 Epoch[037] Batch [2099]/[3759] Speed: 93.189235 samples/sec accuracy=80.911458 loss=0.703089 lr=0.006904 Epoch[037] Batch [2149]/[3759] Speed: 92.920026 samples/sec accuracy=80.876453 loss=0.704075 lr=0.006902 Epoch[037] Batch [2199]/[3759] Speed: 93.209495 samples/sec accuracy=80.834517 loss=0.705641 lr=0.006900 Epoch[037] Batch [2249]/[3759] Speed: 94.912365 samples/sec accuracy=80.802083 loss=0.706333 lr=0.006898 Epoch[037] Batch [2299]/[3759] Speed: 93.602032 samples/sec accuracy=80.786685 loss=0.706870 lr=0.006896 Epoch[037] Batch [2349]/[3759] Speed: 93.550318 samples/sec accuracy=80.784574 loss=0.707107 lr=0.006894 Epoch[037] Batch [2399]/[3759] Speed: 93.390256 samples/sec accuracy=80.791016 loss=0.707188 lr=0.006892 Epoch[037] Batch [2449]/[3759] Speed: 92.777331 samples/sec accuracy=80.804847 loss=0.707205 lr=0.006890 Epoch[037] Batch [2499]/[3759] Speed: 94.035096 samples/sec accuracy=80.759375 loss=0.708285 lr=0.006888 Epoch[037] Batch [2549]/[3759] Speed: 93.726896 samples/sec accuracy=80.724265 loss=0.708905 lr=0.006887 Epoch[037] Batch [2599]/[3759] Speed: 93.055666 samples/sec accuracy=80.715745 loss=0.709247 lr=0.006885 Epoch[037] Batch [2649]/[3759] Speed: 93.392337 samples/sec accuracy=80.719340 loss=0.709535 lr=0.006883 Epoch[037] Batch [2699]/[3759] Speed: 94.284815 samples/sec accuracy=80.703125 loss=0.710305 lr=0.006881 Epoch[037] Batch [2749]/[3759] Speed: 95.570857 samples/sec accuracy=80.669318 loss=0.711741 lr=0.006879 Epoch[037] Batch [2799]/[3759] Speed: 93.498856 samples/sec accuracy=80.661830 loss=0.712016 lr=0.006877 Epoch[037] Batch [2849]/[3759] Speed: 93.093305 samples/sec accuracy=80.625000 loss=0.712984 lr=0.006875 Epoch[037] Batch [2899]/[3759] Speed: 94.045618 samples/sec accuracy=80.613685 loss=0.713732 lr=0.006873 Epoch[037] Batch [2949]/[3759] Speed: 93.530073 samples/sec accuracy=80.615466 loss=0.713652 lr=0.006871 Epoch[037] Batch [2999]/[3759] Speed: 94.380020 samples/sec accuracy=80.585417 loss=0.714027 lr=0.006869 Epoch[037] Batch [3049]/[3759] Speed: 93.722586 samples/sec accuracy=80.558402 loss=0.715104 lr=0.006867 Epoch[037] Batch [3099]/[3759] Speed: 94.098380 samples/sec accuracy=80.554940 loss=0.715527 lr=0.006865 Epoch[037] Batch [3149]/[3759] Speed: 94.496615 samples/sec accuracy=80.534226 loss=0.716326 lr=0.006863 Epoch[037] Batch [3199]/[3759] Speed: 93.085472 samples/sec accuracy=80.532227 loss=0.716852 lr=0.006861 Epoch[037] Batch [3249]/[3759] Speed: 94.046121 samples/sec accuracy=80.513462 loss=0.717397 lr=0.006859 Epoch[037] Batch [3299]/[3759] Speed: 92.944442 samples/sec accuracy=80.495739 loss=0.717965 lr=0.006857 Epoch[037] Batch [3349]/[3759] Speed: 93.746731 samples/sec accuracy=80.476213 loss=0.718770 lr=0.006856 Epoch[037] Batch [3399]/[3759] Speed: 93.671196 samples/sec accuracy=80.452665 loss=0.719758 lr=0.006854 Epoch[037] Batch [3449]/[3759] Speed: 93.443167 samples/sec accuracy=80.440217 loss=0.720775 lr=0.006852 Epoch[037] Batch [3499]/[3759] Speed: 94.843946 samples/sec accuracy=80.404464 loss=0.721777 lr=0.006850 Epoch[037] Batch [3549]/[3759] Speed: 94.127008 samples/sec accuracy=80.394366 loss=0.722470 lr=0.006848 Epoch[037] Batch [3599]/[3759] Speed: 94.306832 samples/sec accuracy=80.385851 loss=0.722822 lr=0.006846 Epoch[037] Batch [3649]/[3759] Speed: 93.472937 samples/sec accuracy=80.367723 loss=0.724113 lr=0.006844 Epoch[037] Batch [3699]/[3759] Speed: 93.403183 samples/sec accuracy=80.345439 loss=0.725011 lr=0.006842 Epoch[037] Batch [3749]/[3759] Speed: 107.900844 samples/sec accuracy=80.340833 loss=0.725288 lr=0.006840 Batch [0049]/[0303]: acc-top1=63.218750 acc-top5=83.937500 Batch [0099]/[0303]: acc-top1=61.953125 acc-top5=84.296875 Batch [0149]/[0303]: acc-top1=63.010417 acc-top5=84.791667 Batch [0199]/[0303]: acc-top1=66.007812 acc-top5=86.218750 Batch [0249]/[0303]: acc-top1=65.475000 acc-top5=85.700000 Batch [0299]/[0303]: acc-top1=64.453125 acc-top5=85.661458 [Epoch 037] training: accuracy=80.337191 loss=0.725521 [Epoch 037] speed: 93 samples/sec time cost: 2795.353023 [Epoch 037] validation: acc-top1=64.454414 acc-top5=85.653878 loss=2.255671 Epoch[038] Batch [0049]/[3760] Speed: 65.230495 samples/sec accuracy=82.843750 loss=0.647469 lr=0.006838 Epoch[038] Batch [0099]/[3760] Speed: 93.943134 samples/sec accuracy=82.875000 loss=0.642825 lr=0.006836 Epoch[038] Batch [0149]/[3760] Speed: 92.873058 samples/sec accuracy=82.666667 loss=0.649550 lr=0.006834 Epoch[038] Batch [0199]/[3760] Speed: 94.252910 samples/sec accuracy=82.632812 loss=0.644421 lr=0.006832 Epoch[038] Batch [0249]/[3760] Speed: 92.985366 samples/sec accuracy=82.412500 loss=0.652015 lr=0.006830 Epoch[038] Batch [0299]/[3760] Speed: 94.672284 samples/sec accuracy=82.411458 loss=0.653768 lr=0.006828 Epoch[038] Batch [0349]/[3760] Speed: 93.606358 samples/sec accuracy=82.178571 loss=0.661467 lr=0.006826 Epoch[038] Batch [0399]/[3760] Speed: 93.718294 samples/sec accuracy=82.074219 loss=0.664858 lr=0.006824 Epoch[038] Batch [0449]/[3760] Speed: 93.558102 samples/sec accuracy=82.083333 loss=0.666866 lr=0.006822 Epoch[038] Batch [0499]/[3760] Speed: 93.418482 samples/sec accuracy=82.059375 loss=0.667768 lr=0.006820 Epoch[038] Batch [0549]/[3760] Speed: 93.843423 samples/sec accuracy=82.019886 loss=0.667764 lr=0.006818 Epoch[038] Batch [0599]/[3760] Speed: 93.079212 samples/sec accuracy=81.880208 loss=0.670939 lr=0.006816 Epoch[038] Batch [0649]/[3760] Speed: 93.730330 samples/sec accuracy=81.867788 loss=0.671214 lr=0.006814 Epoch[038] Batch [0699]/[3760] Speed: 94.524483 samples/sec accuracy=81.825893 loss=0.672905 lr=0.006812 Epoch[038] Batch [0749]/[3760] Speed: 93.410852 samples/sec accuracy=81.779167 loss=0.672599 lr=0.006810 Epoch[038] Batch [0799]/[3760] Speed: 94.901422 samples/sec accuracy=81.759766 loss=0.673344 lr=0.006809 Epoch[038] Batch [0849]/[3760] Speed: 93.285052 samples/sec accuracy=81.720588 loss=0.675191 lr=0.006807 Epoch[038] Batch [0899]/[3760] Speed: 94.353642 samples/sec accuracy=81.765625 loss=0.674841 lr=0.006805 Epoch[038] Batch [0949]/[3760] Speed: 93.247389 samples/sec accuracy=81.735197 loss=0.675943 lr=0.006803 Epoch[038] Batch [0999]/[3760] Speed: 92.347834 samples/sec accuracy=81.684375 loss=0.677383 lr=0.006801 Epoch[038] Batch [1049]/[3760] Speed: 94.969683 samples/sec accuracy=81.623512 loss=0.678572 lr=0.006799 Epoch[038] Batch [1099]/[3760] Speed: 94.672825 samples/sec accuracy=81.590909 loss=0.678740 lr=0.006797 Epoch[038] Batch [1149]/[3760] Speed: 93.457252 samples/sec accuracy=81.597826 loss=0.679602 lr=0.006795 Epoch[038] Batch [1199]/[3760] Speed: 93.198921 samples/sec accuracy=81.520833 loss=0.681384 lr=0.006793 Epoch[038] Batch [1249]/[3760] Speed: 94.741816 samples/sec accuracy=81.532500 loss=0.681641 lr=0.006791 Epoch[038] Batch [1299]/[3760] Speed: 94.008702 samples/sec accuracy=81.543269 loss=0.681618 lr=0.006789 Epoch[038] Batch [1349]/[3760] Speed: 93.521072 samples/sec accuracy=81.535880 loss=0.682736 lr=0.006787 Epoch[038] Batch [1399]/[3760] Speed: 93.103998 samples/sec accuracy=81.516741 loss=0.683093 lr=0.006785 Epoch[038] Batch [1449]/[3760] Speed: 93.816584 samples/sec accuracy=81.480603 loss=0.684443 lr=0.006783 Epoch[038] Batch [1499]/[3760] Speed: 94.092410 samples/sec accuracy=81.494792 loss=0.684356 lr=0.006781 Epoch[038] Batch [1549]/[3760] Speed: 93.802343 samples/sec accuracy=81.487903 loss=0.685273 lr=0.006779 Epoch[038] Batch [1599]/[3760] Speed: 94.405632 samples/sec accuracy=81.492188 loss=0.686117 lr=0.006777 Epoch[038] Batch [1649]/[3760] Speed: 93.498619 samples/sec accuracy=81.464015 loss=0.687240 lr=0.006775 Epoch[038] Batch [1699]/[3760] Speed: 93.850397 samples/sec accuracy=81.455882 loss=0.687717 lr=0.006773 Epoch[038] Batch [1749]/[3760] Speed: 94.458082 samples/sec accuracy=81.439286 loss=0.688317 lr=0.006771 Epoch[038] Batch [1799]/[3760] Speed: 93.585662 samples/sec accuracy=81.407118 loss=0.688909 lr=0.006770 Epoch[038] Batch [1849]/[3760] Speed: 93.332456 samples/sec accuracy=81.395270 loss=0.689160 lr=0.006768 Epoch[038] Batch [1899]/[3760] Speed: 94.117887 samples/sec accuracy=81.384046 loss=0.689816 lr=0.006766 Epoch[038] Batch [1949]/[3760] Speed: 93.140770 samples/sec accuracy=81.383013 loss=0.690316 lr=0.006764 Epoch[038] Batch [1999]/[3760] Speed: 94.635358 samples/sec accuracy=81.350000 loss=0.690944 lr=0.006762 Epoch[038] Batch [2049]/[3760] Speed: 94.153308 samples/sec accuracy=81.307927 loss=0.692154 lr=0.006760 Epoch[038] Batch [2099]/[3760] Speed: 93.013816 samples/sec accuracy=81.258929 loss=0.693571 lr=0.006758 Epoch[038] Batch [2149]/[3760] Speed: 93.383853 samples/sec accuracy=81.235465 loss=0.694761 lr=0.006756 Epoch[038] Batch [2199]/[3760] Speed: 94.228391 samples/sec accuracy=81.218750 loss=0.694846 lr=0.006754 Epoch[038] Batch [2249]/[3760] Speed: 93.511537 samples/sec accuracy=81.184028 loss=0.696375 lr=0.006752 Epoch[038] Batch [2299]/[3760] Speed: 93.859541 samples/sec accuracy=81.173234 loss=0.696924 lr=0.006750 Epoch[038] Batch [2349]/[3760] Speed: 93.762580 samples/sec accuracy=81.144282 loss=0.697718 lr=0.006748 Epoch[038] Batch [2399]/[3760] Speed: 93.324204 samples/sec accuracy=81.134766 loss=0.698556 lr=0.006746 Epoch[038] Batch [2449]/[3760] Speed: 93.729245 samples/sec accuracy=81.135204 loss=0.698482 lr=0.006744 Epoch[038] Batch [2499]/[3760] Speed: 94.539913 samples/sec accuracy=81.099375 loss=0.699618 lr=0.006742 Epoch[038] Batch [2549]/[3760] Speed: 93.586126 samples/sec accuracy=81.077206 loss=0.700126 lr=0.006740 Epoch[038] Batch [2599]/[3760] Speed: 93.357151 samples/sec accuracy=81.078726 loss=0.700693 lr=0.006738 Epoch[038] Batch [2649]/[3760] Speed: 92.948284 samples/sec accuracy=81.084316 loss=0.700447 lr=0.006736 Epoch[038] Batch [2699]/[3760] Speed: 94.984812 samples/sec accuracy=81.088542 loss=0.700948 lr=0.006734 Epoch[038] Batch [2749]/[3760] Speed: 93.202848 samples/sec accuracy=81.073864 loss=0.701445 lr=0.006732 Epoch[038] Batch [2799]/[3760] Speed: 93.906373 samples/sec accuracy=81.059152 loss=0.702214 lr=0.006730 Epoch[038] Batch [2849]/[3760] Speed: 93.693079 samples/sec accuracy=81.042215 loss=0.702675 lr=0.006728 Epoch[038] Batch [2899]/[3760] Speed: 93.543669 samples/sec accuracy=81.012931 loss=0.703590 lr=0.006726 Epoch[038] Batch [2949]/[3760] Speed: 94.090844 samples/sec accuracy=81.002648 loss=0.703719 lr=0.006725 Epoch[038] Batch [2999]/[3760] Speed: 94.055131 samples/sec accuracy=80.997396 loss=0.703954 lr=0.006723 Epoch[038] Batch [3049]/[3760] Speed: 93.558255 samples/sec accuracy=80.966701 loss=0.705367 lr=0.006721 Epoch[038] Batch [3099]/[3760] Speed: 93.326959 samples/sec accuracy=80.941532 loss=0.706045 lr=0.006719 Epoch[038] Batch [3149]/[3760] Speed: 93.765988 samples/sec accuracy=80.913194 loss=0.706895 lr=0.006717 Epoch[038] Batch [3199]/[3760] Speed: 93.636849 samples/sec accuracy=80.903809 loss=0.707452 lr=0.006715 Epoch[038] Batch [3249]/[3760] Speed: 93.738026 samples/sec accuracy=80.883654 loss=0.707959 lr=0.006713 Epoch[038] Batch [3299]/[3760] Speed: 93.626589 samples/sec accuracy=80.865057 loss=0.708374 lr=0.006711 Epoch[038] Batch [3349]/[3760] Speed: 92.848881 samples/sec accuracy=80.827425 loss=0.709439 lr=0.006709 Epoch[038] Batch [3399]/[3760] Speed: 93.829778 samples/sec accuracy=80.807904 loss=0.710082 lr=0.006707 Epoch[038] Batch [3449]/[3760] Speed: 93.653355 samples/sec accuracy=80.768116 loss=0.711293 lr=0.006705 Epoch[038] Batch [3499]/[3760] Speed: 93.372213 samples/sec accuracy=80.743750 loss=0.712293 lr=0.006703 Epoch[038] Batch [3549]/[3760] Speed: 93.978672 samples/sec accuracy=80.733715 loss=0.712232 lr=0.006701 Epoch[038] Batch [3599]/[3760] Speed: 93.695949 samples/sec accuracy=80.720920 loss=0.712829 lr=0.006699 Epoch[038] Batch [3649]/[3760] Speed: 95.013868 samples/sec accuracy=80.704195 loss=0.713506 lr=0.006697 Epoch[038] Batch [3699]/[3760] Speed: 93.633038 samples/sec accuracy=80.707770 loss=0.713496 lr=0.006695 Epoch[038] Batch [3749]/[3760] Speed: 104.854613 samples/sec accuracy=80.690417 loss=0.714180 lr=0.006693 Batch [0049]/[0303]: acc-top1=64.406250 acc-top5=84.593750 Batch [0099]/[0303]: acc-top1=62.578125 acc-top5=84.218750 Batch [0149]/[0303]: acc-top1=63.666667 acc-top5=85.020833 Batch [0199]/[0303]: acc-top1=66.187500 acc-top5=86.226562 Batch [0249]/[0303]: acc-top1=65.543750 acc-top5=85.868750 Batch [0299]/[0303]: acc-top1=64.984375 acc-top5=85.895833 [Epoch 038] training: accuracy=80.690658 loss=0.714108 [Epoch 038] speed: 93 samples/sec time cost: 2795.077124 [Epoch 038] validation: acc-top1=64.897896 acc-top5=85.839521 loss=2.122846 Epoch[039] Batch [0049]/[3760] Speed: 64.219793 samples/sec accuracy=81.406250 loss=0.687188 lr=0.006691 Epoch[039] Batch [0099]/[3760] Speed: 93.296848 samples/sec accuracy=81.203125 loss=0.679072 lr=0.006689 Epoch[039] Batch [0149]/[3760] Speed: 94.566022 samples/sec accuracy=81.062500 loss=0.690604 lr=0.006687 Epoch[039] Batch [0199]/[3760] Speed: 94.191394 samples/sec accuracy=81.062500 loss=0.689159 lr=0.006685 Epoch[039] Batch [0249]/[3760] Speed: 93.564770 samples/sec accuracy=81.337500 loss=0.679633 lr=0.006683 Epoch[039] Batch [0299]/[3760] Speed: 93.965621 samples/sec accuracy=81.473958 loss=0.677079 lr=0.006681 Epoch[039] Batch [0349]/[3760] Speed: 93.408487 samples/sec accuracy=81.607143 loss=0.670586 lr=0.006679 Epoch[039] Batch [0399]/[3760] Speed: 93.944435 samples/sec accuracy=81.585938 loss=0.669719 lr=0.006677 Epoch[039] Batch [0449]/[3760] Speed: 94.123057 samples/sec accuracy=81.684028 loss=0.664886 lr=0.006675 Epoch[039] Batch [0499]/[3760] Speed: 93.298861 samples/sec accuracy=81.821875 loss=0.661667 lr=0.006673 Epoch[039] Batch [0549]/[3760] Speed: 92.930383 samples/sec accuracy=81.892045 loss=0.659882 lr=0.006671 Epoch[039] Batch [0599]/[3760] Speed: 95.236405 samples/sec accuracy=81.997396 loss=0.658943 lr=0.006669 Epoch[039] Batch [0649]/[3760] Speed: 94.072459 samples/sec accuracy=82.040865 loss=0.657673 lr=0.006667 Epoch[039] Batch [0699]/[3760] Speed: 93.310887 samples/sec accuracy=82.084821 loss=0.657776 lr=0.006665 Epoch[039] Batch [0749]/[3760] Speed: 92.795591 samples/sec accuracy=82.056250 loss=0.660195 lr=0.006663 Epoch[039] Batch [0799]/[3760] Speed: 95.149590 samples/sec accuracy=82.041016 loss=0.660773 lr=0.006661 Epoch[039] Batch [0849]/[3760] Speed: 94.125451 samples/sec accuracy=82.031250 loss=0.661402 lr=0.006659 Epoch[039] Batch [0899]/[3760] Speed: 94.179769 samples/sec accuracy=82.036458 loss=0.660866 lr=0.006657 Epoch[039] Batch [0949]/[3760] Speed: 93.932955 samples/sec accuracy=82.019737 loss=0.659721 lr=0.006655 Epoch[039] Batch [0999]/[3760] Speed: 92.974195 samples/sec accuracy=81.965625 loss=0.661805 lr=0.006653 Epoch[039] Batch [1049]/[3760] Speed: 94.550372 samples/sec accuracy=81.915179 loss=0.662630 lr=0.006651 Epoch[039] Batch [1099]/[3760] Speed: 93.113231 samples/sec accuracy=81.894886 loss=0.662378 lr=0.006649 Epoch[039] Batch [1149]/[3760] Speed: 94.011891 samples/sec accuracy=81.898098 loss=0.663005 lr=0.006647 Epoch[039] Batch [1199]/[3760] Speed: 93.068513 samples/sec accuracy=81.907552 loss=0.662864 lr=0.006645 Epoch[039] Batch [1249]/[3760] Speed: 94.272145 samples/sec accuracy=81.846250 loss=0.665957 lr=0.006643 Epoch[039] Batch [1299]/[3760] Speed: 93.767726 samples/sec accuracy=81.852163 loss=0.665922 lr=0.006641 Epoch[039] Batch [1349]/[3760] Speed: 93.541912 samples/sec accuracy=81.828704 loss=0.665713 lr=0.006640 Epoch[039] Batch [1399]/[3760] Speed: 93.738505 samples/sec accuracy=81.799107 loss=0.666308 lr=0.006638 Epoch[039] Batch [1449]/[3760] Speed: 93.746506 samples/sec accuracy=81.800647 loss=0.666927 lr=0.006636 Epoch[039] Batch [1499]/[3760] Speed: 93.330613 samples/sec accuracy=81.761458 loss=0.668986 lr=0.006634 Epoch[039] Batch [1549]/[3760] Speed: 93.835515 samples/sec accuracy=81.727823 loss=0.670865 lr=0.006632 Epoch[039] Batch [1599]/[3760] Speed: 93.714073 samples/sec accuracy=81.726562 loss=0.671448 lr=0.006630 Epoch[039] Batch [1649]/[3760] Speed: 93.464181 samples/sec accuracy=81.687500 loss=0.672665 lr=0.006628 Epoch[039] Batch [1699]/[3760] Speed: 94.834197 samples/sec accuracy=81.673713 loss=0.673466 lr=0.006626 Epoch[039] Batch [1749]/[3760] Speed: 92.992171 samples/sec accuracy=81.664286 loss=0.673430 lr=0.006624 Epoch[039] Batch [1799]/[3760] Speed: 94.131583 samples/sec accuracy=81.654514 loss=0.673800 lr=0.006622 Epoch[039] Batch [1849]/[3760] Speed: 93.421229 samples/sec accuracy=81.614020 loss=0.675082 lr=0.006620 Epoch[039] Batch [1899]/[3760] Speed: 94.304080 samples/sec accuracy=81.613487 loss=0.675264 lr=0.006618 Epoch[039] Batch [1949]/[3760] Speed: 93.812886 samples/sec accuracy=81.647436 loss=0.674625 lr=0.006616 Epoch[039] Batch [1999]/[3760] Speed: 93.108207 samples/sec accuracy=81.642187 loss=0.674839 lr=0.006614 Epoch[039] Batch [2049]/[3760] Speed: 93.659668 samples/sec accuracy=81.615091 loss=0.675903 lr=0.006612 Epoch[039] Batch [2099]/[3760] Speed: 93.985615 samples/sec accuracy=81.597470 loss=0.677211 lr=0.006610 Epoch[039] Batch [2149]/[3760] Speed: 93.550771 samples/sec accuracy=81.595203 loss=0.677395 lr=0.006608 Epoch[039] Batch [2199]/[3760] Speed: 93.710598 samples/sec accuracy=81.575994 loss=0.677978 lr=0.006606 Epoch[039] Batch [2249]/[3760] Speed: 93.398180 samples/sec accuracy=81.556944 loss=0.678789 lr=0.006604 Epoch[039] Batch [2299]/[3760] Speed: 92.903291 samples/sec accuracy=81.532609 loss=0.679425 lr=0.006602 Epoch[039] Batch [2349]/[3760] Speed: 94.502796 samples/sec accuracy=81.512633 loss=0.679934 lr=0.006600 Epoch[039] Batch [2399]/[3760] Speed: 94.319317 samples/sec accuracy=81.478516 loss=0.681793 lr=0.006598 Epoch[039] Batch [2449]/[3760] Speed: 94.228059 samples/sec accuracy=81.446429 loss=0.683313 lr=0.006596 Epoch[039] Batch [2499]/[3760] Speed: 92.692308 samples/sec accuracy=81.434375 loss=0.684065 lr=0.006594 Epoch[039] Batch [2549]/[3760] Speed: 94.654904 samples/sec accuracy=81.440564 loss=0.684030 lr=0.006592 Epoch[039] Batch [2599]/[3760] Speed: 93.088319 samples/sec accuracy=81.427885 loss=0.684170 lr=0.006590 Epoch[039] Batch [2649]/[3760] Speed: 92.689625 samples/sec accuracy=81.419811 loss=0.684488 lr=0.006588 Epoch[039] Batch [2699]/[3760] Speed: 93.584605 samples/sec accuracy=81.385995 loss=0.685714 lr=0.006586 Epoch[039] Batch [2749]/[3760] Speed: 93.375556 samples/sec accuracy=81.372727 loss=0.686137 lr=0.006584 Epoch[039] Batch [2799]/[3760] Speed: 93.669399 samples/sec accuracy=81.337054 loss=0.687496 lr=0.006582 Epoch[039] Batch [2849]/[3760] Speed: 93.554424 samples/sec accuracy=81.316338 loss=0.688204 lr=0.006580 Epoch[039] Batch [2899]/[3760] Speed: 92.996922 samples/sec accuracy=81.285022 loss=0.688865 lr=0.006578 Epoch[039] Batch [2949]/[3760] Speed: 93.295659 samples/sec accuracy=81.284958 loss=0.688867 lr=0.006576 Epoch[039] Batch [2999]/[3760] Speed: 95.830326 samples/sec accuracy=81.283854 loss=0.688908 lr=0.006574 Epoch[039] Batch [3049]/[3760] Speed: 94.031573 samples/sec accuracy=81.269980 loss=0.689671 lr=0.006572 Epoch[039] Batch [3099]/[3760] Speed: 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lr=0.006552 Epoch[039] Batch [3599]/[3760] Speed: 92.629567 samples/sec accuracy=81.048177 loss=0.697537 lr=0.006550 Epoch[039] Batch [3649]/[3760] Speed: 94.517123 samples/sec accuracy=81.050514 loss=0.697402 lr=0.006548 Epoch[039] Batch [3699]/[3760] Speed: 93.847930 samples/sec accuracy=81.036740 loss=0.698010 lr=0.006546 Epoch[039] Batch [3749]/[3760] Speed: 105.109564 samples/sec accuracy=81.018333 loss=0.698424 lr=0.006544 Batch [0049]/[0303]: acc-top1=63.968750 acc-top5=85.031250 Batch [0099]/[0303]: acc-top1=62.031250 acc-top5=84.000000 Batch [0149]/[0303]: acc-top1=63.302083 acc-top5=84.791667 Batch [0199]/[0303]: acc-top1=65.843750 acc-top5=86.187500 Batch [0249]/[0303]: acc-top1=65.243750 acc-top5=85.718750 Batch [0299]/[0303]: acc-top1=64.718750 acc-top5=85.567708 [Epoch 039] training: accuracy=81.005652 loss=0.698809 [Epoch 039] speed: 93 samples/sec time cost: 2796.244783 [Epoch 039] validation: acc-top1=64.707096 acc-top5=85.566213 loss=2.179161 Epoch[040] Batch 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accuracy=82.690625 loss=0.639592 lr=0.006524 Epoch[040] Batch [0549]/[3759] Speed: 94.056501 samples/sec accuracy=82.667614 loss=0.640018 lr=0.006522 Epoch[040] Batch [0599]/[3759] Speed: 93.392079 samples/sec accuracy=82.559896 loss=0.642513 lr=0.006520 Epoch[040] Batch [0649]/[3759] Speed: 93.802625 samples/sec accuracy=82.475962 loss=0.644554 lr=0.006518 Epoch[040] Batch [0699]/[3759] Speed: 93.192365 samples/sec accuracy=82.473214 loss=0.643319 lr=0.006516 Epoch[040] Batch [0749]/[3759] Speed: 93.005845 samples/sec accuracy=82.502083 loss=0.642636 lr=0.006514 Epoch[040] Batch [0799]/[3759] Speed: 94.501461 samples/sec accuracy=82.486328 loss=0.642516 lr=0.006512 Epoch[040] Batch [0849]/[3759] Speed: 94.252171 samples/sec accuracy=82.430147 loss=0.646106 lr=0.006510 Epoch[040] Batch [0899]/[3759] Speed: 93.139999 samples/sec accuracy=82.340278 loss=0.648105 lr=0.006508 Epoch[040] Batch [0949]/[3759] Speed: 92.972985 samples/sec accuracy=82.315789 loss=0.647895 lr=0.006506 Epoch[040] 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accuracy=81.969828 loss=0.659880 lr=0.006486 Epoch[040] Batch [1499]/[3759] Speed: 93.037969 samples/sec accuracy=81.937500 loss=0.660463 lr=0.006484 Epoch[040] Batch [1549]/[3759] Speed: 94.082298 samples/sec accuracy=81.900202 loss=0.661043 lr=0.006482 Epoch[040] Batch [1599]/[3759] Speed: 92.516526 samples/sec accuracy=81.851562 loss=0.663095 lr=0.006480 Epoch[040] Batch [1649]/[3759] Speed: 94.953809 samples/sec accuracy=81.847538 loss=0.663355 lr=0.006478 Epoch[040] Batch [1699]/[3759] Speed: 93.574461 samples/sec accuracy=81.818934 loss=0.664032 lr=0.006476 Epoch[040] Batch [1749]/[3759] Speed: 93.776510 samples/sec accuracy=81.758036 loss=0.665849 lr=0.006474 Epoch[040] Batch [1799]/[3759] Speed: 92.531173 samples/sec accuracy=81.712674 loss=0.667191 lr=0.006472 Epoch[040] Batch [1849]/[3759] Speed: 94.051138 samples/sec accuracy=81.706081 loss=0.667197 lr=0.006470 Epoch[040] Batch [1899]/[3759] Speed: 92.534575 samples/sec accuracy=81.716283 loss=0.666943 lr=0.006468 Epoch[040] 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accuracy=81.568359 loss=0.673455 lr=0.006448 Epoch[040] Batch [2449]/[3759] Speed: 92.831294 samples/sec accuracy=81.559949 loss=0.673983 lr=0.006446 Epoch[040] Batch [2499]/[3759] Speed: 94.042923 samples/sec accuracy=81.573750 loss=0.674083 lr=0.006444 Epoch[040] Batch [2549]/[3759] Speed: 93.509231 samples/sec accuracy=81.554534 loss=0.674612 lr=0.006442 Epoch[040] Batch [2599]/[3759] Speed: 93.951072 samples/sec accuracy=81.532452 loss=0.675202 lr=0.006440 Epoch[040] Batch [2649]/[3759] Speed: 93.547777 samples/sec accuracy=81.525943 loss=0.675050 lr=0.006438 Epoch[040] Batch [2699]/[3759] Speed: 93.667305 samples/sec accuracy=81.514468 loss=0.675413 lr=0.006436 Epoch[040] Batch [2749]/[3759] Speed: 94.445873 samples/sec accuracy=81.492045 loss=0.676019 lr=0.006434 Epoch[040] Batch [2799]/[3759] Speed: 93.649043 samples/sec accuracy=81.480469 loss=0.676249 lr=0.006432 Epoch[040] Batch [2849]/[3759] Speed: 93.461206 samples/sec accuracy=81.468750 loss=0.677289 lr=0.006430 Epoch[040] Batch [2899]/[3759] Speed: 94.086254 samples/sec accuracy=81.440194 loss=0.678157 lr=0.006428 Epoch[040] Batch [2949]/[3759] Speed: 93.842804 samples/sec accuracy=81.406780 loss=0.679518 lr=0.006426 Epoch[040] Batch [2999]/[3759] Speed: 93.847201 samples/sec accuracy=81.383333 loss=0.680438 lr=0.006424 Epoch[040] Batch [3049]/[3759] Speed: 93.286709 samples/sec accuracy=81.360143 loss=0.681037 lr=0.006422 Epoch[040] Batch [3099]/[3759] Speed: 92.887765 samples/sec accuracy=81.358871 loss=0.681553 lr=0.006420 Epoch[040] Batch [3149]/[3759] Speed: 94.806623 samples/sec accuracy=81.347222 loss=0.682430 lr=0.006418 Epoch[040] Batch [3199]/[3759] Speed: 93.739679 samples/sec accuracy=81.347656 loss=0.682643 lr=0.006416 Epoch[040] Batch [3249]/[3759] Speed: 93.994225 samples/sec accuracy=81.343269 loss=0.682885 lr=0.006414 Epoch[040] Batch [3299]/[3759] Speed: 92.211963 samples/sec accuracy=81.337121 loss=0.683092 lr=0.006412 Epoch[040] Batch [3349]/[3759] Speed: 94.317510 samples/sec accuracy=81.306903 loss=0.684072 lr=0.006410 Epoch[040] Batch [3399]/[3759] Speed: 92.884587 samples/sec accuracy=81.317096 loss=0.684018 lr=0.006408 Epoch[040] Batch [3449]/[3759] Speed: 94.018345 samples/sec accuracy=81.299819 loss=0.684848 lr=0.006406 Epoch[040] Batch [3499]/[3759] Speed: 93.625628 samples/sec accuracy=81.300446 loss=0.684962 lr=0.006404 Epoch[040] Batch [3549]/[3759] Speed: 94.410928 samples/sec accuracy=81.297975 loss=0.685212 lr=0.006402 Epoch[040] Batch [3599]/[3759] Speed: 93.107256 samples/sec accuracy=81.279080 loss=0.685982 lr=0.006400 Epoch[040] Batch [3649]/[3759] Speed: 93.746195 samples/sec accuracy=81.275257 loss=0.686257 lr=0.006398 Epoch[040] Batch [3699]/[3759] Speed: 93.431380 samples/sec accuracy=81.262247 loss=0.686600 lr=0.006396 Epoch[040] Batch [3749]/[3759] Speed: 107.056404 samples/sec accuracy=81.241250 loss=0.687130 lr=0.006394 Batch [0049]/[0303]: acc-top1=63.562500 acc-top5=84.718750 Batch [0099]/[0303]: acc-top1=61.593750 acc-top5=83.953125 Batch [0149]/[0303]: acc-top1=63.385417 acc-top5=84.843750 Batch [0199]/[0303]: acc-top1=65.929688 acc-top5=86.117188 Batch [0249]/[0303]: acc-top1=65.400000 acc-top5=85.725000 Batch [0299]/[0303]: acc-top1=64.729167 acc-top5=85.744792 [Epoch 040] training: accuracy=81.233789 loss=0.687318 [Epoch 040] speed: 93 samples/sec time cost: 2796.314187 [Epoch 040] validation: acc-top1=64.650371 acc-top5=85.720916 loss=2.201340 Epoch[041] Batch [0049]/[3760] Speed: 64.156131 samples/sec accuracy=82.406250 loss=0.624843 lr=0.006392 Epoch[041] Batch [0099]/[3760] Speed: 93.442016 samples/sec accuracy=83.250000 loss=0.604512 lr=0.006390 Epoch[041] Batch [0149]/[3760] Speed: 93.925072 samples/sec accuracy=83.302083 loss=0.606803 lr=0.006388 Epoch[041] Batch [0199]/[3760] Speed: 93.033848 samples/sec accuracy=83.031250 loss=0.615995 lr=0.006386 Epoch[041] Batch [0249]/[3760] Speed: 94.741680 samples/sec accuracy=83.143750 loss=0.612777 lr=0.006384 Epoch[041] Batch [0299]/[3760] 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loss=0.626102 lr=0.006364 Epoch[041] Batch [0799]/[3760] Speed: 93.915944 samples/sec accuracy=82.869141 loss=0.626253 lr=0.006362 Epoch[041] Batch [0849]/[3760] Speed: 94.746326 samples/sec accuracy=82.803309 loss=0.628686 lr=0.006360 Epoch[041] Batch [0899]/[3760] Speed: 94.251457 samples/sec accuracy=82.748264 loss=0.629581 lr=0.006358 Epoch[041] Batch [0949]/[3760] Speed: 93.389069 samples/sec accuracy=82.720395 loss=0.630861 lr=0.006356 Epoch[041] Batch [0999]/[3760] Speed: 93.899096 samples/sec accuracy=82.632812 loss=0.633401 lr=0.006354 Epoch[041] Batch [1049]/[3760] Speed: 95.105970 samples/sec accuracy=82.601190 loss=0.633941 lr=0.006352 Epoch[041] Batch [1099]/[3760] Speed: 93.424132 samples/sec accuracy=82.593750 loss=0.634084 lr=0.006350 Epoch[041] Batch [1149]/[3760] Speed: 93.597263 samples/sec accuracy=82.608696 loss=0.634700 lr=0.006348 Epoch[041] Batch [1199]/[3760] Speed: 93.000408 samples/sec accuracy=82.567708 loss=0.636380 lr=0.006346 Epoch[041] Batch 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accuracy=82.452206 loss=0.641928 lr=0.006326 Epoch[041] Batch [1749]/[3760] Speed: 94.069303 samples/sec accuracy=82.413393 loss=0.644160 lr=0.006324 Epoch[041] Batch [1799]/[3760] Speed: 93.479139 samples/sec accuracy=82.352431 loss=0.645972 lr=0.006322 Epoch[041] Batch [1849]/[3760] Speed: 94.972425 samples/sec accuracy=82.271959 loss=0.648206 lr=0.006319 Epoch[041] Batch [1899]/[3760] Speed: 93.317158 samples/sec accuracy=82.217928 loss=0.649831 lr=0.006317 Epoch[041] Batch [1949]/[3760] Speed: 94.119590 samples/sec accuracy=82.219551 loss=0.650391 lr=0.006315 Epoch[041] Batch [1999]/[3760] Speed: 93.473297 samples/sec accuracy=82.183594 loss=0.651803 lr=0.006313 Epoch[041] Batch [2049]/[3760] Speed: 94.586729 samples/sec accuracy=82.163110 loss=0.652877 lr=0.006311 Epoch[041] Batch [2099]/[3760] Speed: 93.392335 samples/sec accuracy=82.156250 loss=0.652992 lr=0.006309 Epoch[041] Batch [2149]/[3760] Speed: 93.100931 samples/sec accuracy=82.098110 loss=0.654932 lr=0.006307 Epoch[041] 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accuracy=81.598090 loss=0.672507 lr=0.006249 Epoch[041] Batch [3649]/[3760] Speed: 93.047151 samples/sec accuracy=81.584760 loss=0.672969 lr=0.006247 Epoch[041] Batch [3699]/[3760] Speed: 93.489587 samples/sec accuracy=81.575169 loss=0.673461 lr=0.006245 Epoch[041] Batch [3749]/[3760] Speed: 104.515447 samples/sec accuracy=81.544167 loss=0.674365 lr=0.006243 Batch [0049]/[0303]: acc-top1=65.406250 acc-top5=84.750000 Batch [0099]/[0303]: acc-top1=62.953125 acc-top5=84.500000 Batch [0149]/[0303]: acc-top1=64.093750 acc-top5=85.218750 Batch [0199]/[0303]: acc-top1=66.500000 acc-top5=86.539062 Batch [0249]/[0303]: acc-top1=66.112500 acc-top5=86.168750 Batch [0299]/[0303]: acc-top1=65.479167 acc-top5=86.125000 [Epoch 041] training: accuracy=81.537151 loss=0.674795 [Epoch 041] speed: 93 samples/sec time cost: 2795.617994 [Epoch 041] validation: acc-top1=65.403259 acc-top5=86.050949 loss=2.067920 Epoch[042] Batch [0049]/[3760] Speed: 64.613882 samples/sec accuracy=83.125000 loss=0.622218 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lr=0.006163 Epoch[042] Batch [1999]/[3760] Speed: 93.289472 samples/sec accuracy=82.657813 loss=0.633972 lr=0.006161 Epoch[042] Batch [2049]/[3760] Speed: 93.663729 samples/sec accuracy=82.626524 loss=0.635170 lr=0.006159 Epoch[042] Batch [2099]/[3760] Speed: 94.483311 samples/sec accuracy=82.607143 loss=0.636245 lr=0.006157 Epoch[042] Batch [2149]/[3760] Speed: 93.086139 samples/sec accuracy=82.577762 loss=0.637353 lr=0.006155 Epoch[042] Batch [2199]/[3760] Speed: 94.038426 samples/sec accuracy=82.529830 loss=0.639112 lr=0.006153 Epoch[042] Batch [2249]/[3760] Speed: 92.715463 samples/sec accuracy=82.502083 loss=0.640313 lr=0.006151 Epoch[042] Batch [2299]/[3760] Speed: 94.243544 samples/sec accuracy=82.452446 loss=0.641918 lr=0.006149 Epoch[042] Batch [2349]/[3760] Speed: 93.354592 samples/sec accuracy=82.447473 loss=0.642387 lr=0.006147 Epoch[042] Batch [2399]/[3760] Speed: 93.847125 samples/sec accuracy=82.457031 loss=0.642114 lr=0.006145 Epoch[042] Batch [2449]/[3760] Speed: 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lr=0.006125 Epoch[042] Batch [2949]/[3760] Speed: 93.321325 samples/sec accuracy=82.224047 loss=0.650546 lr=0.006123 Epoch[042] Batch [2999]/[3760] Speed: 93.361602 samples/sec accuracy=82.216667 loss=0.650976 lr=0.006121 Epoch[042] Batch [3049]/[3760] Speed: 94.965346 samples/sec accuracy=82.190061 loss=0.651602 lr=0.006118 Epoch[042] Batch [3099]/[3760] Speed: 93.682742 samples/sec accuracy=82.162802 loss=0.652539 lr=0.006116 Epoch[042] Batch [3149]/[3760] Speed: 93.039325 samples/sec accuracy=82.132440 loss=0.653614 lr=0.006114 Epoch[042] Batch [3199]/[3760] Speed: 92.376375 samples/sec accuracy=82.096680 loss=0.654573 lr=0.006112 Epoch[042] Batch [3249]/[3760] Speed: 94.428209 samples/sec accuracy=82.084615 loss=0.654746 lr=0.006110 Epoch[042] Batch [3299]/[3760] Speed: 93.043726 samples/sec accuracy=82.084280 loss=0.654888 lr=0.006108 Epoch[042] Batch [3349]/[3760] Speed: 93.467286 samples/sec accuracy=82.070896 loss=0.655475 lr=0.006106 Epoch[042] Batch [3399]/[3760] Speed: 94.393469 samples/sec accuracy=82.053309 loss=0.656047 lr=0.006104 Epoch[042] Batch [3449]/[3760] Speed: 94.446165 samples/sec accuracy=82.033062 loss=0.656949 lr=0.006102 Epoch[042] Batch [3499]/[3760] Speed: 93.189178 samples/sec accuracy=82.015179 loss=0.657838 lr=0.006100 Epoch[042] Batch [3549]/[3760] Speed: 93.210440 samples/sec accuracy=81.996919 loss=0.658758 lr=0.006098 Epoch[042] Batch [3599]/[3760] Speed: 94.950289 samples/sec accuracy=81.979167 loss=0.659162 lr=0.006096 Epoch[042] Batch [3649]/[3760] Speed: 93.386050 samples/sec accuracy=81.963185 loss=0.660351 lr=0.006094 Epoch[042] Batch [3699]/[3760] Speed: 92.893340 samples/sec accuracy=81.945524 loss=0.660912 lr=0.006092 Epoch[042] Batch [3749]/[3760] Speed: 105.560449 samples/sec accuracy=81.933333 loss=0.661092 lr=0.006090 Batch [0049]/[0303]: acc-top1=61.875000 acc-top5=83.718750 Batch [0099]/[0303]: acc-top1=61.875000 acc-top5=84.203125 Batch [0149]/[0303]: acc-top1=63.187500 acc-top5=84.833333 Batch [0199]/[0303]: acc-top1=65.640625 acc-top5=86.070312 Batch [0249]/[0303]: acc-top1=65.306250 acc-top5=85.818750 Batch [0299]/[0303]: acc-top1=64.854167 acc-top5=85.776042 [Epoch 042] training: accuracy=81.921543 loss=0.661496 [Epoch 042] speed: 93 samples/sec time cost: 2796.900348 [Epoch 042] validation: acc-top1=64.789604 acc-top5=85.726073 loss=2.306257 Epoch[043] Batch [0049]/[3759] Speed: 64.632776 samples/sec accuracy=83.968750 loss=0.589955 lr=0.006088 Epoch[043] Batch [0099]/[3759] Speed: 94.546938 samples/sec accuracy=84.000000 loss=0.575188 lr=0.006085 Epoch[043] Batch [0149]/[3759] Speed: 93.607344 samples/sec accuracy=83.791667 loss=0.584556 lr=0.006083 Epoch[043] Batch [0199]/[3759] Speed: 92.397187 samples/sec accuracy=83.570312 loss=0.593606 lr=0.006081 Epoch[043] Batch [0249]/[3759] Speed: 94.637955 samples/sec accuracy=83.506250 loss=0.594822 lr=0.006079 Epoch[043] Batch [0299]/[3759] Speed: 93.035054 samples/sec accuracy=83.541667 loss=0.596614 lr=0.006077 Epoch[043] Batch 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accuracy=82.383562 loss=0.643705 lr=0.005940 Epoch[043] Batch [3699]/[3759] Speed: 94.084751 samples/sec accuracy=82.381757 loss=0.643751 lr=0.005938 Epoch[043] Batch [3749]/[3759] Speed: 105.037546 samples/sec accuracy=82.359583 loss=0.644204 lr=0.005936 Batch [0049]/[0303]: acc-top1=63.437500 acc-top5=83.750000 Batch [0099]/[0303]: acc-top1=62.156250 acc-top5=83.296875 Batch [0149]/[0303]: acc-top1=63.062500 acc-top5=84.260417 Batch [0199]/[0303]: acc-top1=66.000000 acc-top5=85.640625 Batch [0249]/[0303]: acc-top1=65.631250 acc-top5=85.406250 Batch [0299]/[0303]: acc-top1=65.130208 acc-top5=85.411458 [Epoch 043] training: accuracy=82.362746 loss=0.644223 [Epoch 043] speed: 93 samples/sec time cost: 2798.532428 [Epoch 043] validation: acc-top1=64.944307 acc-top5=85.354785 loss=2.212853 Epoch[044] Batch [0049]/[3760] Speed: 65.090174 samples/sec accuracy=83.718750 loss=0.593358 lr=0.005934 Epoch[044] Batch [0099]/[3760] Speed: 93.600855 samples/sec accuracy=83.640625 loss=0.594394 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lr=0.005893 Epoch[044] Batch [1099]/[3760] Speed: 94.245272 samples/sec accuracy=83.438920 loss=0.607574 lr=0.005891 Epoch[044] Batch [1149]/[3760] Speed: 93.568200 samples/sec accuracy=83.482337 loss=0.606816 lr=0.005888 Epoch[044] Batch [1199]/[3760] Speed: 93.395278 samples/sec accuracy=83.470052 loss=0.606752 lr=0.005886 Epoch[044] Batch [1249]/[3760] Speed: 92.550997 samples/sec accuracy=83.478750 loss=0.606705 lr=0.005884 Epoch[044] Batch [1299]/[3760] Speed: 95.219507 samples/sec accuracy=83.496394 loss=0.606217 lr=0.005882 Epoch[044] Batch [1349]/[3760] Speed: 93.348756 samples/sec accuracy=83.468750 loss=0.606508 lr=0.005880 Epoch[044] Batch [1399]/[3760] Speed: 94.148202 samples/sec accuracy=83.439732 loss=0.608250 lr=0.005878 Epoch[044] Batch [1449]/[3760] Speed: 93.992884 samples/sec accuracy=83.445043 loss=0.608161 lr=0.005876 Epoch[044] Batch [1499]/[3760] Speed: 94.250681 samples/sec accuracy=83.443750 loss=0.608383 lr=0.005874 Epoch[044] Batch [1549]/[3760] Speed: 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lr=0.005854 Epoch[044] Batch [2049]/[3760] Speed: 93.766527 samples/sec accuracy=83.243902 loss=0.614387 lr=0.005851 Epoch[044] Batch [2099]/[3760] Speed: 92.893756 samples/sec accuracy=83.232887 loss=0.615006 lr=0.005849 Epoch[044] Batch [2149]/[3760] Speed: 94.506944 samples/sec accuracy=83.184593 loss=0.616257 lr=0.005847 Epoch[044] Batch [2199]/[3760] Speed: 93.223867 samples/sec accuracy=83.137784 loss=0.617470 lr=0.005845 Epoch[044] Batch [2249]/[3760] Speed: 93.610037 samples/sec accuracy=83.113889 loss=0.618457 lr=0.005843 Epoch[044] Batch [2299]/[3760] Speed: 94.136157 samples/sec accuracy=83.078125 loss=0.619690 lr=0.005841 Epoch[044] Batch [2349]/[3760] Speed: 94.500655 samples/sec accuracy=83.032580 loss=0.621428 lr=0.005839 Epoch[044] Batch [2399]/[3760] Speed: 93.236125 samples/sec accuracy=83.027995 loss=0.621474 lr=0.005837 Epoch[044] Batch [2449]/[3760] Speed: 92.856848 samples/sec accuracy=83.009566 loss=0.622169 lr=0.005835 Epoch[044] Batch [2499]/[3760] Speed: 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lr=0.005814 Epoch[044] Batch [2999]/[3760] Speed: 94.249955 samples/sec accuracy=82.911458 loss=0.627208 lr=0.005812 Epoch[044] Batch [3049]/[3760] Speed: 94.107160 samples/sec accuracy=82.898053 loss=0.627756 lr=0.005810 Epoch[044] Batch [3099]/[3760] Speed: 92.963893 samples/sec accuracy=82.880544 loss=0.628232 lr=0.005808 Epoch[044] Batch [3149]/[3760] Speed: 95.232958 samples/sec accuracy=82.879960 loss=0.628516 lr=0.005806 Epoch[044] Batch [3199]/[3760] Speed: 92.865867 samples/sec accuracy=82.890625 loss=0.628396 lr=0.005804 Epoch[044] Batch [3249]/[3760] Speed: 93.973748 samples/sec accuracy=82.878365 loss=0.628287 lr=0.005802 Epoch[044] Batch [3299]/[3760] Speed: 93.775296 samples/sec accuracy=82.862216 loss=0.628898 lr=0.005800 Epoch[044] Batch [3349]/[3760] Speed: 92.962776 samples/sec accuracy=82.858209 loss=0.629217 lr=0.005798 Epoch[044] Batch [3399]/[3760] Speed: 94.205260 samples/sec accuracy=82.836397 loss=0.629754 lr=0.005796 Epoch[044] Batch [3449]/[3760] Speed: 94.194600 samples/sec accuracy=82.822011 loss=0.630027 lr=0.005794 Epoch[044] Batch [3499]/[3760] Speed: 93.726629 samples/sec accuracy=82.800893 loss=0.630658 lr=0.005792 Epoch[044] Batch [3549]/[3760] Speed: 93.202743 samples/sec accuracy=82.774648 loss=0.631662 lr=0.005790 Epoch[044] Batch [3599]/[3760] Speed: 92.739752 samples/sec accuracy=82.763455 loss=0.632070 lr=0.005788 Epoch[044] Batch [3649]/[3760] Speed: 94.203055 samples/sec accuracy=82.753425 loss=0.632367 lr=0.005785 Epoch[044] Batch [3699]/[3760] Speed: 93.926388 samples/sec accuracy=82.732264 loss=0.633493 lr=0.005783 Epoch[044] Batch [3749]/[3760] Speed: 105.271070 samples/sec accuracy=82.716667 loss=0.633623 lr=0.005781 Batch [0049]/[0303]: acc-top1=63.250000 acc-top5=84.500000 Batch [0099]/[0303]: acc-top1=61.937500 acc-top5=84.250000 Batch [0149]/[0303]: acc-top1=62.843750 acc-top5=84.729167 Batch [0199]/[0303]: acc-top1=65.625000 acc-top5=85.859375 Batch [0249]/[0303]: acc-top1=64.912500 acc-top5=85.275000 Batch [0299]/[0303]: acc-top1=64.562500 acc-top5=85.307292 [Epoch 044] training: accuracy=82.709441 loss=0.633668 [Epoch 044] speed: 93 samples/sec time cost: 2795.313550 [Epoch 044] validation: acc-top1=64.614274 acc-top5=85.329002 loss=2.225988 Epoch[045] Batch [0049]/[3760] Speed: 64.724144 samples/sec accuracy=84.093750 loss=0.581694 lr=0.005779 Epoch[045] Batch [0099]/[3760] Speed: 93.525157 samples/sec accuracy=84.437500 loss=0.576343 lr=0.005777 Epoch[045] Batch [0149]/[3760] Speed: 92.887799 samples/sec accuracy=84.406250 loss=0.577183 lr=0.005775 Epoch[045] Batch [0199]/[3760] Speed: 93.168300 samples/sec accuracy=84.226562 loss=0.581197 lr=0.005773 Epoch[045] Batch [0249]/[3760] Speed: 94.335580 samples/sec accuracy=84.143750 loss=0.585188 lr=0.005771 Epoch[045] Batch [0299]/[3760] Speed: 94.104104 samples/sec accuracy=84.177083 loss=0.583742 lr=0.005769 Epoch[045] Batch [0349]/[3760] Speed: 93.132398 samples/sec accuracy=84.080357 loss=0.584516 lr=0.005767 Epoch[045] Batch 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accuracy=83.946691 loss=0.585328 lr=0.005746 Epoch[045] Batch [0899]/[3760] Speed: 93.864600 samples/sec accuracy=83.951389 loss=0.585063 lr=0.005744 Epoch[045] Batch [0949]/[3760] Speed: 94.198800 samples/sec accuracy=83.934211 loss=0.585473 lr=0.005742 Epoch[045] Batch [0999]/[3760] Speed: 93.829548 samples/sec accuracy=83.921875 loss=0.585633 lr=0.005740 Epoch[045] Batch [1049]/[3760] Speed: 94.326566 samples/sec accuracy=83.904762 loss=0.586640 lr=0.005738 Epoch[045] Batch [1099]/[3760] Speed: 93.549775 samples/sec accuracy=83.901989 loss=0.586767 lr=0.005736 Epoch[045] Batch [1149]/[3760] Speed: 93.522692 samples/sec accuracy=83.872283 loss=0.588667 lr=0.005733 Epoch[045] Batch [1199]/[3760] Speed: 93.387122 samples/sec accuracy=83.829427 loss=0.589911 lr=0.005731 Epoch[045] Batch [1249]/[3760] Speed: 92.681499 samples/sec accuracy=83.841250 loss=0.589614 lr=0.005729 Epoch[045] Batch [1299]/[3760] Speed: 94.120305 samples/sec accuracy=83.830529 loss=0.589847 lr=0.005727 Epoch[045] 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accuracy=83.636285 loss=0.598568 lr=0.005707 Epoch[045] Batch [1849]/[3760] Speed: 94.393183 samples/sec accuracy=83.607264 loss=0.599375 lr=0.005705 Epoch[045] Batch [1899]/[3760] Speed: 94.014993 samples/sec accuracy=83.612664 loss=0.598732 lr=0.005702 Epoch[045] Batch [1949]/[3760] Speed: 93.645214 samples/sec accuracy=83.620192 loss=0.598178 lr=0.005700 Epoch[045] Batch [1999]/[3760] Speed: 93.095501 samples/sec accuracy=83.588281 loss=0.599441 lr=0.005698 Epoch[045] Batch [2049]/[3760] Speed: 94.957371 samples/sec accuracy=83.564024 loss=0.600348 lr=0.005696 Epoch[045] Batch [2099]/[3760] Speed: 93.379771 samples/sec accuracy=83.525298 loss=0.601405 lr=0.005694 Epoch[045] Batch [2149]/[3760] Speed: 93.107544 samples/sec accuracy=83.519622 loss=0.601176 lr=0.005692 Epoch[045] Batch [2199]/[3760] Speed: 94.530257 samples/sec accuracy=83.517045 loss=0.601643 lr=0.005690 Epoch[045] Batch [2249]/[3760] Speed: 93.346285 samples/sec accuracy=83.475000 loss=0.602865 lr=0.005688 Epoch[045] 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accuracy=83.371023 loss=0.606825 lr=0.005667 Epoch[045] Batch [2799]/[3760] Speed: 93.808814 samples/sec accuracy=83.345982 loss=0.607451 lr=0.005665 Epoch[045] Batch [2849]/[3760] Speed: 93.729127 samples/sec accuracy=83.335526 loss=0.607850 lr=0.005663 Epoch[045] Batch [2899]/[3760] Speed: 94.169038 samples/sec accuracy=83.315733 loss=0.608239 lr=0.005661 Epoch[045] Batch [2949]/[3760] Speed: 92.687238 samples/sec accuracy=83.299788 loss=0.608907 lr=0.005659 Epoch[045] Batch [2999]/[3760] Speed: 94.304181 samples/sec accuracy=83.282292 loss=0.609905 lr=0.005657 Epoch[045] Batch [3049]/[3760] Speed: 93.185829 samples/sec accuracy=83.283299 loss=0.609623 lr=0.005655 Epoch[045] Batch [3099]/[3760] Speed: 93.632105 samples/sec accuracy=83.277722 loss=0.609909 lr=0.005653 Epoch[045] Batch [3149]/[3760] Speed: 92.564363 samples/sec accuracy=83.268849 loss=0.610201 lr=0.005651 Epoch[045] Batch [3199]/[3760] Speed: 94.678051 samples/sec accuracy=83.253906 loss=0.610932 lr=0.005649 Epoch[045] 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accuracy=83.108953 loss=0.616680 lr=0.005628 Epoch[045] Batch [3749]/[3760] Speed: 105.276898 samples/sec accuracy=83.099583 loss=0.617675 lr=0.005626 Batch [0049]/[0303]: acc-top1=64.093750 acc-top5=84.625000 Batch [0099]/[0303]: acc-top1=62.890625 acc-top5=84.390625 Batch [0149]/[0303]: acc-top1=63.927083 acc-top5=84.750000 Batch [0199]/[0303]: acc-top1=66.882812 acc-top5=86.406250 Batch [0249]/[0303]: acc-top1=66.150000 acc-top5=85.900000 Batch [0299]/[0303]: acc-top1=65.687500 acc-top5=85.848958 [Epoch 045] training: accuracy=83.091755 loss=0.617817 [Epoch 045] speed: 93 samples/sec time cost: 2796.907358 [Epoch 045] validation: acc-top1=65.707508 acc-top5=85.854992 loss=2.151681 Epoch[046] Batch [0049]/[3759] Speed: 64.909806 samples/sec accuracy=84.437500 loss=0.553176 lr=0.005623 Epoch[046] Batch [0099]/[3759] Speed: 93.589821 samples/sec accuracy=84.562500 loss=0.565880 lr=0.005621 Epoch[046] Batch [0149]/[3759] Speed: 93.564308 samples/sec accuracy=84.791667 loss=0.552326 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lr=0.005580 Epoch[046] Batch [1149]/[3759] Speed: 93.415364 samples/sec accuracy=84.480978 loss=0.564583 lr=0.005578 Epoch[046] Batch [1199]/[3759] Speed: 92.660638 samples/sec accuracy=84.460938 loss=0.565100 lr=0.005576 Epoch[046] Batch [1249]/[3759] Speed: 94.547157 samples/sec accuracy=84.412500 loss=0.566401 lr=0.005574 Epoch[046] Batch [1299]/[3759] Speed: 94.153094 samples/sec accuracy=84.381010 loss=0.567764 lr=0.005571 Epoch[046] Batch [1349]/[3759] Speed: 93.466852 samples/sec accuracy=84.346065 loss=0.568473 lr=0.005569 Epoch[046] Batch [1399]/[3759] Speed: 95.327746 samples/sec accuracy=84.327009 loss=0.569374 lr=0.005567 Epoch[046] Batch [1449]/[3759] Speed: 93.406419 samples/sec accuracy=84.343750 loss=0.569122 lr=0.005565 Epoch[046] Batch [1499]/[3759] Speed: 92.998730 samples/sec accuracy=84.313542 loss=0.569557 lr=0.005563 Epoch[046] Batch [1549]/[3759] Speed: 93.281130 samples/sec accuracy=84.313508 loss=0.569663 lr=0.005561 Epoch[046] Batch [1599]/[3759] Speed: 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lr=0.005540 Epoch[046] Batch [2099]/[3759] Speed: 93.035753 samples/sec accuracy=84.078125 loss=0.578634 lr=0.005538 Epoch[046] Batch [2149]/[3759] Speed: 94.510520 samples/sec accuracy=84.070494 loss=0.579078 lr=0.005536 Epoch[046] Batch [2199]/[3759] Speed: 93.430607 samples/sec accuracy=84.073153 loss=0.579012 lr=0.005534 Epoch[046] Batch [2249]/[3759] Speed: 93.470101 samples/sec accuracy=84.076389 loss=0.579166 lr=0.005532 Epoch[046] Batch [2299]/[3759] Speed: 93.918441 samples/sec accuracy=84.067255 loss=0.579421 lr=0.005530 Epoch[046] Batch [2349]/[3759] Speed: 93.448105 samples/sec accuracy=84.074468 loss=0.579525 lr=0.005528 Epoch[046] Batch [2399]/[3759] Speed: 92.968155 samples/sec accuracy=84.067057 loss=0.580259 lr=0.005526 Epoch[046] Batch [2449]/[3759] Speed: 93.208890 samples/sec accuracy=84.030612 loss=0.581301 lr=0.005524 Epoch[046] Batch [2499]/[3759] Speed: 95.316244 samples/sec accuracy=83.969375 loss=0.582644 lr=0.005522 Epoch[046] Batch [2549]/[3759] Speed: 93.676885 samples/sec accuracy=83.987745 loss=0.582233 lr=0.005520 Epoch[046] Batch [2599]/[3759] Speed: 92.397068 samples/sec accuracy=83.949519 loss=0.582958 lr=0.005517 Epoch[046] Batch [2649]/[3759] Speed: 95.365538 samples/sec accuracy=83.931604 loss=0.583960 lr=0.005515 Epoch[046] Batch [2699]/[3759] Speed: 93.058469 samples/sec accuracy=83.915509 loss=0.585053 lr=0.005513 Epoch[046] Batch [2749]/[3759] Speed: 93.289549 samples/sec accuracy=83.870455 loss=0.586345 lr=0.005511 Epoch[046] Batch [2799]/[3759] Speed: 94.338581 samples/sec accuracy=83.848214 loss=0.587044 lr=0.005509 Epoch[046] Batch [2849]/[3759] Speed: 93.458815 samples/sec accuracy=83.854715 loss=0.587538 lr=0.005507 Epoch[046] Batch [2899]/[3759] Speed: 92.986965 samples/sec accuracy=83.825970 loss=0.588846 lr=0.005505 Epoch[046] Batch [2949]/[3759] Speed: 94.051464 samples/sec accuracy=83.822564 loss=0.589068 lr=0.005503 Epoch[046] Batch [2999]/[3759] Speed: 93.585329 samples/sec accuracy=83.795833 loss=0.590180 lr=0.005501 Epoch[046] Batch [3049]/[3759] Speed: 93.839920 samples/sec accuracy=83.776127 loss=0.590895 lr=0.005499 Epoch[046] Batch [3099]/[3759] Speed: 93.990010 samples/sec accuracy=83.756552 loss=0.591676 lr=0.005497 Epoch[046] Batch [3149]/[3759] Speed: 93.758376 samples/sec accuracy=83.756944 loss=0.591445 lr=0.005495 Epoch[046] Batch [3199]/[3759] Speed: 92.783199 samples/sec accuracy=83.741699 loss=0.591962 lr=0.005493 Epoch[046] Batch [3249]/[3759] Speed: 94.019792 samples/sec accuracy=83.728846 loss=0.592766 lr=0.005490 Epoch[046] Batch [3299]/[3759] Speed: 93.248793 samples/sec accuracy=83.691761 loss=0.593832 lr=0.005488 Epoch[046] Batch [3349]/[3759] Speed: 93.677807 samples/sec accuracy=83.658582 loss=0.595147 lr=0.005486 Epoch[046] Batch [3399]/[3759] Speed: 93.595166 samples/sec accuracy=83.631434 loss=0.596056 lr=0.005484 Epoch[046] Batch [3449]/[3759] Speed: 93.789930 samples/sec accuracy=83.617754 loss=0.596488 lr=0.005482 Epoch[046] Batch [3499]/[3759] Speed: 93.562356 samples/sec accuracy=83.591518 loss=0.597389 lr=0.005480 Epoch[046] Batch [3549]/[3759] Speed: 93.784162 samples/sec accuracy=83.572623 loss=0.598102 lr=0.005478 Epoch[046] Batch [3599]/[3759] Speed: 93.789369 samples/sec accuracy=83.553385 loss=0.598665 lr=0.005476 Epoch[046] Batch [3649]/[3759] Speed: 93.821606 samples/sec accuracy=83.534675 loss=0.599318 lr=0.005474 Epoch[046] Batch [3699]/[3759] Speed: 93.745218 samples/sec accuracy=83.521115 loss=0.599547 lr=0.005472 Epoch[046] Batch [3749]/[3759] Speed: 106.149105 samples/sec accuracy=83.511667 loss=0.599895 lr=0.005470 Batch [0049]/[0303]: acc-top1=63.750000 acc-top5=83.687500 Batch [0099]/[0303]: acc-top1=62.625000 acc-top5=83.531250 Batch [0149]/[0303]: acc-top1=63.572917 acc-top5=84.427083 Batch [0199]/[0303]: acc-top1=66.093750 acc-top5=85.757812 Batch [0249]/[0303]: acc-top1=65.718750 acc-top5=85.606250 Batch [0299]/[0303]: acc-top1=65.364583 acc-top5=85.687500 [Epoch 046] training: accuracy=83.505836 loss=0.600057 [Epoch 046] speed: 93 samples/sec time cost: 2797.161061 [Epoch 046] validation: acc-top1=65.315594 acc-top5=85.664191 loss=2.289602 Epoch[047] Batch [0049]/[3760] Speed: 64.764013 samples/sec accuracy=85.375000 loss=0.552108 lr=0.005467 Epoch[047] Batch [0099]/[3760] Speed: 92.879857 samples/sec accuracy=85.703125 loss=0.528674 lr=0.005465 Epoch[047] Batch [0149]/[3760] Speed: 93.967545 samples/sec accuracy=85.760417 loss=0.525460 lr=0.005463 Epoch[047] Batch [0199]/[3760] Speed: 93.448486 samples/sec accuracy=85.640625 loss=0.529718 lr=0.005461 Epoch[047] Batch [0249]/[3760] Speed: 93.290414 samples/sec accuracy=85.556250 loss=0.529204 lr=0.005459 Epoch[047] Batch [0299]/[3760] Speed: 94.789138 samples/sec accuracy=85.484375 loss=0.533001 lr=0.005457 Epoch[047] Batch [0349]/[3760] Speed: 93.884651 samples/sec accuracy=85.303571 loss=0.541170 lr=0.005455 Epoch[047] Batch [0399]/[3760] Speed: 92.871216 samples/sec accuracy=85.304688 loss=0.541489 lr=0.005453 Epoch[047] 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accuracy=85.107639 loss=0.547340 lr=0.005432 Epoch[047] Batch [0949]/[3760] Speed: 93.534673 samples/sec accuracy=85.072368 loss=0.549563 lr=0.005430 Epoch[047] Batch [0999]/[3760] Speed: 93.345668 samples/sec accuracy=85.067188 loss=0.549737 lr=0.005428 Epoch[047] Batch [1049]/[3760] Speed: 93.824644 samples/sec accuracy=84.991071 loss=0.553861 lr=0.005426 Epoch[047] Batch [1099]/[3760] Speed: 94.338792 samples/sec accuracy=84.977273 loss=0.553726 lr=0.005423 Epoch[047] Batch [1149]/[3760] Speed: 93.961334 samples/sec accuracy=84.989130 loss=0.553009 lr=0.005421 Epoch[047] Batch [1199]/[3760] Speed: 93.325750 samples/sec accuracy=84.972656 loss=0.553473 lr=0.005419 Epoch[047] Batch [1249]/[3760] Speed: 93.389965 samples/sec accuracy=84.961250 loss=0.553739 lr=0.005417 Epoch[047] Batch [1299]/[3760] Speed: 93.804038 samples/sec accuracy=84.944712 loss=0.553856 lr=0.005415 Epoch[047] Batch [1349]/[3760] Speed: 93.582363 samples/sec accuracy=84.905093 loss=0.554863 lr=0.005413 Epoch[047] 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accuracy=84.113750 loss=0.581508 lr=0.005313 Batch [0049]/[0303]: acc-top1=65.031250 acc-top5=84.593750 Batch [0099]/[0303]: acc-top1=63.125000 acc-top5=84.218750 Batch [0149]/[0303]: acc-top1=64.125000 acc-top5=84.656250 Batch [0199]/[0303]: acc-top1=66.695312 acc-top5=85.851562 Batch [0249]/[0303]: acc-top1=66.012500 acc-top5=85.400000 Batch [0299]/[0303]: acc-top1=65.567708 acc-top5=85.489583 [Epoch 047] training: accuracy=84.113614 loss=0.581449 [Epoch 047] speed: 93 samples/sec time cost: 2798.636753 [Epoch 047] validation: acc-top1=65.563119 acc-top5=85.457921 loss=2.205392 Epoch[048] Batch [0049]/[3760] Speed: 64.659760 samples/sec accuracy=85.968750 loss=0.524457 lr=0.005311 Epoch[048] Batch [0099]/[3760] Speed: 93.895269 samples/sec accuracy=85.609375 loss=0.519076 lr=0.005308 Epoch[048] Batch [0149]/[3760] Speed: 92.489419 samples/sec accuracy=85.958333 loss=0.516393 lr=0.005306 Epoch[048] Batch [0199]/[3760] Speed: 93.532043 samples/sec accuracy=85.875000 loss=0.515382 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lr=0.005185 Epoch[048] Batch [3099]/[3760] Speed: 94.136759 samples/sec accuracy=84.502016 loss=0.563346 lr=0.005183 Epoch[048] Batch [3149]/[3760] Speed: 93.317558 samples/sec accuracy=84.498512 loss=0.563852 lr=0.005181 Epoch[048] Batch [3199]/[3760] Speed: 93.787154 samples/sec accuracy=84.484375 loss=0.564342 lr=0.005179 Epoch[048] Batch [3249]/[3760] Speed: 94.779613 samples/sec accuracy=84.445192 loss=0.565283 lr=0.005177 Epoch[048] Batch [3299]/[3760] Speed: 93.238843 samples/sec accuracy=84.434186 loss=0.565514 lr=0.005175 Epoch[048] Batch [3349]/[3760] Speed: 93.333465 samples/sec accuracy=84.414179 loss=0.566056 lr=0.005173 Epoch[048] Batch [3399]/[3760] Speed: 94.449478 samples/sec accuracy=84.392923 loss=0.567045 lr=0.005171 Epoch[048] Batch [3449]/[3760] Speed: 93.988269 samples/sec accuracy=84.389040 loss=0.567154 lr=0.005169 Epoch[048] Batch [3499]/[3760] Speed: 92.772280 samples/sec accuracy=84.373661 loss=0.567608 lr=0.005167 Epoch[048] Batch [3549]/[3760] Speed: 94.965441 samples/sec accuracy=84.364877 loss=0.567841 lr=0.005164 Epoch[048] Batch [3599]/[3760] Speed: 93.494548 samples/sec accuracy=84.350694 loss=0.568539 lr=0.005162 Epoch[048] Batch [3649]/[3760] Speed: 94.576762 samples/sec accuracy=84.329623 loss=0.569386 lr=0.005160 Epoch[048] Batch [3699]/[3760] Speed: 93.509702 samples/sec accuracy=84.315456 loss=0.569542 lr=0.005158 Epoch[048] Batch [3749]/[3760] Speed: 105.215004 samples/sec accuracy=84.294583 loss=0.570297 lr=0.005156 Batch [0049]/[0303]: acc-top1=65.187500 acc-top5=84.031250 Batch [0099]/[0303]: acc-top1=62.734375 acc-top5=83.781250 Batch [0149]/[0303]: acc-top1=63.947917 acc-top5=84.645833 Batch [0199]/[0303]: acc-top1=66.578125 acc-top5=86.023438 Batch [0249]/[0303]: acc-top1=65.931250 acc-top5=85.643750 Batch [0299]/[0303]: acc-top1=65.447917 acc-top5=85.484375 [Epoch 048] training: accuracy=84.285655 loss=0.570650 [Epoch 048] speed: 93 samples/sec time cost: 2796.479326 [Epoch 048] validation: acc-top1=65.372318 acc-top5=85.432137 loss=2.183508 Epoch[049] Batch [0049]/[3759] Speed: 64.195964 samples/sec accuracy=86.156250 loss=0.517026 lr=0.005154 Epoch[049] Batch [0099]/[3759] Speed: 94.810114 samples/sec accuracy=85.750000 loss=0.519492 lr=0.005152 Epoch[049] Batch [0149]/[3759] Speed: 93.044765 samples/sec accuracy=85.416667 loss=0.533332 lr=0.005149 Epoch[049] Batch [0199]/[3759] Speed: 93.580422 samples/sec accuracy=85.664062 loss=0.523140 lr=0.005147 Epoch[049] Batch [0249]/[3759] Speed: 94.675581 samples/sec accuracy=85.612500 loss=0.523018 lr=0.005145 Epoch[049] Batch [0299]/[3759] Speed: 93.556841 samples/sec accuracy=85.437500 loss=0.526632 lr=0.005143 Epoch[049] Batch [0349]/[3759] Speed: 93.837606 samples/sec accuracy=85.464286 loss=0.525254 lr=0.005141 Epoch[049] Batch [0399]/[3759] Speed: 93.196562 samples/sec accuracy=85.402344 loss=0.525744 lr=0.005139 Epoch[049] Batch [0449]/[3759] Speed: 94.197478 samples/sec accuracy=85.322917 loss=0.528012 lr=0.005137 Epoch[049] Batch 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accuracy=84.685855 loss=0.552691 lr=0.005037 Epoch[049] Batch [2899]/[3759] Speed: 92.633175 samples/sec accuracy=84.665409 loss=0.553516 lr=0.005035 Epoch[049] Batch [2949]/[3759] Speed: 94.098189 samples/sec accuracy=84.656250 loss=0.554062 lr=0.005032 Epoch[049] Batch [2999]/[3759] Speed: 92.869484 samples/sec accuracy=84.631771 loss=0.555060 lr=0.005030 Epoch[049] Batch [3049]/[3759] Speed: 93.674044 samples/sec accuracy=84.614242 loss=0.555601 lr=0.005028 Epoch[049] Batch [3099]/[3759] Speed: 94.722827 samples/sec accuracy=84.594254 loss=0.556151 lr=0.005026 Epoch[049] Batch [3149]/[3759] Speed: 92.826876 samples/sec accuracy=84.588790 loss=0.556570 lr=0.005024 Epoch[049] Batch [3199]/[3759] Speed: 92.294056 samples/sec accuracy=84.562988 loss=0.557224 lr=0.005022 Epoch[049] Batch [3249]/[3759] Speed: 95.109475 samples/sec accuracy=84.567788 loss=0.557327 lr=0.005020 Epoch[049] Batch [3299]/[3759] Speed: 93.433022 samples/sec accuracy=84.551610 loss=0.557585 lr=0.005018 Epoch[049] 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[0099]/[0303]: acc-top1=62.781250 acc-top5=83.890625 Batch [0149]/[0303]: acc-top1=63.364583 acc-top5=84.468750 Batch [0199]/[0303]: acc-top1=66.296875 acc-top5=86.007812 Batch [0249]/[0303]: acc-top1=65.768750 acc-top5=85.675000 Batch [0299]/[0303]: acc-top1=65.354167 acc-top5=85.755208 [Epoch 049] training: accuracy=84.470188 loss=0.560298 [Epoch 049] speed: 93 samples/sec time cost: 2796.603030 [Epoch 049] validation: acc-top1=65.264026 acc-top5=85.700289 loss=2.255031 Epoch[050] Batch [0049]/[3760] Speed: 64.493916 samples/sec accuracy=86.125000 loss=0.502077 lr=0.004997 Epoch[050] Batch [0099]/[3760] Speed: 93.686400 samples/sec accuracy=85.953125 loss=0.506750 lr=0.004994 Epoch[050] Batch [0149]/[3760] Speed: 93.145832 samples/sec accuracy=85.968750 loss=0.502375 lr=0.004992 Epoch[050] Batch [0199]/[3760] Speed: 93.996986 samples/sec accuracy=85.953125 loss=0.500542 lr=0.004990 Epoch[050] Batch [0249]/[3760] Speed: 93.565057 samples/sec accuracy=86.118750 loss=0.497443 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lr=0.004869 Epoch[050] Batch [3149]/[3760] Speed: 93.625439 samples/sec accuracy=85.133433 loss=0.539611 lr=0.004867 Epoch[050] Batch [3199]/[3760] Speed: 93.054276 samples/sec accuracy=85.129395 loss=0.540117 lr=0.004865 Epoch[050] Batch [3249]/[3760] Speed: 95.049719 samples/sec accuracy=85.110577 loss=0.540589 lr=0.004863 Epoch[050] Batch [3299]/[3760] Speed: 93.494295 samples/sec accuracy=85.093277 loss=0.541196 lr=0.004861 Epoch[050] Batch [3349]/[3760] Speed: 93.030319 samples/sec accuracy=85.075560 loss=0.541674 lr=0.004859 Epoch[050] Batch [3399]/[3760] Speed: 94.202283 samples/sec accuracy=85.036305 loss=0.542600 lr=0.004857 Epoch[050] Batch [3449]/[3760] Speed: 93.456431 samples/sec accuracy=85.042572 loss=0.542355 lr=0.004854 Epoch[050] Batch [3499]/[3760] Speed: 94.130589 samples/sec accuracy=85.033036 loss=0.542505 lr=0.004852 Epoch[050] Batch [3549]/[3760] Speed: 93.650220 samples/sec accuracy=85.006162 loss=0.543458 lr=0.004850 Epoch[050] Batch [3599]/[3760] Speed: 93.381123 samples/sec accuracy=84.999132 loss=0.544035 lr=0.004848 Epoch[050] Batch [3649]/[3760] Speed: 94.373077 samples/sec accuracy=85.005137 loss=0.544079 lr=0.004846 Epoch[050] Batch [3699]/[3760] Speed: 93.732951 samples/sec accuracy=84.983108 loss=0.544717 lr=0.004844 Epoch[050] Batch [3749]/[3760] Speed: 105.070905 samples/sec accuracy=84.967917 loss=0.545096 lr=0.004842 Batch [0049]/[0303]: acc-top1=65.406250 acc-top5=85.312500 Batch [0099]/[0303]: acc-top1=63.328125 acc-top5=84.765625 Batch [0149]/[0303]: acc-top1=63.916667 acc-top5=85.020833 Batch [0199]/[0303]: acc-top1=66.203125 acc-top5=86.117188 Batch [0249]/[0303]: acc-top1=65.656250 acc-top5=85.618750 Batch [0299]/[0303]: acc-top1=65.437500 acc-top5=85.765625 [Epoch 050] training: accuracy=84.965924 loss=0.545112 [Epoch 050] speed: 93 samples/sec time cost: 2798.158595 [Epoch 050] validation: acc-top1=65.372318 acc-top5=85.705446 loss=2.235969 Epoch[051] Batch [0049]/[3760] Speed: 65.057439 samples/sec accuracy=87.093750 loss=0.482685 lr=0.004839 Epoch[051] Batch [0099]/[3760] Speed: 93.428935 samples/sec accuracy=86.640625 loss=0.484475 lr=0.004837 Epoch[051] Batch [0149]/[3760] Speed: 92.854166 samples/sec accuracy=86.552083 loss=0.486693 lr=0.004835 Epoch[051] Batch [0199]/[3760] Speed: 94.350553 samples/sec accuracy=86.601562 loss=0.485217 lr=0.004833 Epoch[051] Batch [0249]/[3760] Speed: 93.570388 samples/sec accuracy=86.712500 loss=0.483874 lr=0.004831 Epoch[051] Batch [0299]/[3760] Speed: 92.708548 samples/sec accuracy=86.723958 loss=0.485563 lr=0.004829 Epoch[051] Batch [0349]/[3760] Speed: 94.414981 samples/sec accuracy=86.647321 loss=0.487643 lr=0.004827 Epoch[051] Batch [0399]/[3760] Speed: 93.727180 samples/sec accuracy=86.609375 loss=0.488962 lr=0.004825 Epoch[051] Batch [0449]/[3760] Speed: 93.760717 samples/sec accuracy=86.503472 loss=0.489355 lr=0.004823 Epoch[051] Batch [0499]/[3760] Speed: 93.197088 samples/sec accuracy=86.450000 loss=0.490890 lr=0.004821 Epoch[051] 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accuracy=85.682112 loss=0.517547 lr=0.004720 Epoch[051] Batch [2949]/[3760] Speed: 93.001902 samples/sec accuracy=85.659428 loss=0.518012 lr=0.004718 Epoch[051] Batch [2999]/[3760] Speed: 93.442242 samples/sec accuracy=85.654167 loss=0.518037 lr=0.004716 Epoch[051] Batch [3049]/[3760] Speed: 93.804662 samples/sec accuracy=85.638832 loss=0.518687 lr=0.004714 Epoch[051] Batch [3099]/[3760] Speed: 93.179371 samples/sec accuracy=85.622984 loss=0.519400 lr=0.004712 Epoch[051] Batch [3149]/[3760] Speed: 94.541500 samples/sec accuracy=85.607639 loss=0.520076 lr=0.004710 Epoch[051] Batch [3199]/[3760] Speed: 93.420675 samples/sec accuracy=85.583496 loss=0.520813 lr=0.004708 Epoch[051] Batch [3249]/[3760] Speed: 93.489772 samples/sec accuracy=85.574038 loss=0.521077 lr=0.004706 Epoch[051] Batch [3299]/[3760] Speed: 92.950302 samples/sec accuracy=85.579545 loss=0.520845 lr=0.004704 Epoch[051] Batch [3349]/[3760] Speed: 92.893270 samples/sec accuracy=85.556437 loss=0.521563 lr=0.004702 Epoch[051] 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acc-top5=84.458333 Batch [0199]/[0303]: acc-top1=65.890625 acc-top5=85.937500 Batch [0249]/[0303]: acc-top1=65.631250 acc-top5=85.706250 Batch [0299]/[0303]: acc-top1=65.140625 acc-top5=85.734375 [Epoch 051] training: accuracy=85.466672 loss=0.525595 [Epoch 051] speed: 93 samples/sec time cost: 2798.218972 [Epoch 051] validation: acc-top1=65.114480 acc-top5=85.679662 loss=2.331557 Epoch[052] Batch [0049]/[3759] Speed: 65.160752 samples/sec accuracy=86.875000 loss=0.489429 lr=0.004683 Epoch[052] Batch [0099]/[3759] Speed: 93.843335 samples/sec accuracy=87.078125 loss=0.478296 lr=0.004680 Epoch[052] Batch [0149]/[3759] Speed: 93.510758 samples/sec accuracy=86.822917 loss=0.480398 lr=0.004678 Epoch[052] Batch [0199]/[3759] Speed: 93.842767 samples/sec accuracy=87.015625 loss=0.474545 lr=0.004676 Epoch[052] Batch [0249]/[3759] Speed: 93.890339 samples/sec accuracy=87.081250 loss=0.472608 lr=0.004674 Epoch[052] Batch [0299]/[3759] Speed: 92.603656 samples/sec accuracy=87.203125 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accuracy=86.746250 loss=0.478213 lr=0.004632 Epoch[052] Batch [1299]/[3759] Speed: 92.716193 samples/sec accuracy=86.759615 loss=0.477871 lr=0.004630 Epoch[052] Batch [1349]/[3759] Speed: 92.955244 samples/sec accuracy=86.732639 loss=0.478940 lr=0.004628 Epoch[052] Batch [1399]/[3759] Speed: 94.460581 samples/sec accuracy=86.698661 loss=0.480370 lr=0.004626 Epoch[052] Batch [1449]/[3759] Speed: 93.204853 samples/sec accuracy=86.643319 loss=0.482275 lr=0.004624 Epoch[052] Batch [1499]/[3759] Speed: 93.899305 samples/sec accuracy=86.640625 loss=0.483043 lr=0.004622 Epoch[052] Batch [1549]/[3759] Speed: 93.476033 samples/sec accuracy=86.644153 loss=0.483907 lr=0.004620 Epoch[052] Batch [1599]/[3759] Speed: 92.865100 samples/sec accuracy=86.648438 loss=0.483962 lr=0.004618 Epoch[052] Batch [1649]/[3759] Speed: 94.071878 samples/sec accuracy=86.664773 loss=0.483239 lr=0.004616 Epoch[052] Batch [1699]/[3759] Speed: 93.583601 samples/sec accuracy=86.661765 loss=0.483474 lr=0.004614 Epoch[052] 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accuracy=86.391335 loss=0.493163 lr=0.004593 Epoch[052] Batch [2249]/[3759] Speed: 93.349667 samples/sec accuracy=86.354861 loss=0.493847 lr=0.004591 Epoch[052] Batch [2299]/[3759] Speed: 94.467914 samples/sec accuracy=86.347147 loss=0.494663 lr=0.004589 Epoch[052] Batch [2349]/[3759] Speed: 93.480744 samples/sec accuracy=86.325798 loss=0.495793 lr=0.004587 Epoch[052] Batch [2399]/[3759] Speed: 92.891645 samples/sec accuracy=86.305990 loss=0.496471 lr=0.004585 Epoch[052] Batch [2449]/[3759] Speed: 94.421728 samples/sec accuracy=86.284439 loss=0.496886 lr=0.004583 Epoch[052] Batch [2499]/[3759] Speed: 93.144865 samples/sec accuracy=86.255625 loss=0.497552 lr=0.004580 Epoch[052] Batch [2549]/[3759] Speed: 93.603832 samples/sec accuracy=86.257966 loss=0.497480 lr=0.004578 Epoch[052] Batch [2599]/[3759] Speed: 93.786247 samples/sec accuracy=86.241587 loss=0.498028 lr=0.004576 Epoch[052] Batch [2649]/[3759] Speed: 94.015442 samples/sec accuracy=86.208137 loss=0.498824 lr=0.004574 Epoch[052] 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accuracy=86.088790 loss=0.503464 lr=0.004553 Epoch[052] Batch [3199]/[3759] Speed: 93.769805 samples/sec accuracy=86.072754 loss=0.504199 lr=0.004551 Epoch[052] Batch [3249]/[3759] Speed: 94.037033 samples/sec accuracy=86.058654 loss=0.504735 lr=0.004549 Epoch[052] Batch [3299]/[3759] Speed: 92.897474 samples/sec accuracy=86.053504 loss=0.504562 lr=0.004547 Epoch[052] Batch [3349]/[3759] Speed: 94.049537 samples/sec accuracy=86.041511 loss=0.505016 lr=0.004545 Epoch[052] Batch [3399]/[3759] Speed: 93.423583 samples/sec accuracy=86.011489 loss=0.505851 lr=0.004543 Epoch[052] Batch [3449]/[3759] Speed: 93.938583 samples/sec accuracy=85.982337 loss=0.506534 lr=0.004541 Epoch[052] Batch [3499]/[3759] Speed: 93.705812 samples/sec accuracy=85.968750 loss=0.507264 lr=0.004539 Epoch[052] Batch [3549]/[3759] Speed: 93.401664 samples/sec accuracy=85.976232 loss=0.507104 lr=0.004537 Epoch[052] Batch [3599]/[3759] Speed: 93.833432 samples/sec accuracy=85.966580 loss=0.507389 lr=0.004535 Epoch[052] Batch [3649]/[3759] Speed: 93.647869 samples/sec accuracy=85.964041 loss=0.507657 lr=0.004533 Epoch[052] Batch [3699]/[3759] Speed: 92.797097 samples/sec accuracy=85.972128 loss=0.507502 lr=0.004530 Epoch[052] Batch [3749]/[3759] Speed: 107.918507 samples/sec accuracy=85.966250 loss=0.508202 lr=0.004528 Batch [0049]/[0303]: acc-top1=64.781250 acc-top5=84.812500 Batch [0099]/[0303]: acc-top1=63.562500 acc-top5=84.593750 Batch [0149]/[0303]: acc-top1=64.687500 acc-top5=85.062500 Batch [0199]/[0303]: acc-top1=67.351562 acc-top5=86.437500 Batch [0249]/[0303]: acc-top1=66.612500 acc-top5=85.825000 Batch [0299]/[0303]: acc-top1=65.572917 acc-top5=85.770833 [Epoch 052] training: accuracy=85.967013 loss=0.508179 [Epoch 052] speed: 93 samples/sec time cost: 2796.073543 [Epoch 052] validation: acc-top1=65.588903 acc-top5=85.751856 loss=2.298691 Epoch[053] Batch [0049]/[3760] Speed: 65.101997 samples/sec accuracy=87.187500 loss=0.469528 lr=0.004526 Epoch[053] Batch [0099]/[3760] Speed: 92.545020 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lr=0.004387 Epoch[053] Batch [3449]/[3760] Speed: 94.952247 samples/sec accuracy=86.497736 loss=0.488929 lr=0.004385 Epoch[053] Batch [3499]/[3760] Speed: 92.799252 samples/sec accuracy=86.471875 loss=0.489599 lr=0.004383 Epoch[053] Batch [3549]/[3760] Speed: 93.877740 samples/sec accuracy=86.462148 loss=0.490315 lr=0.004381 Epoch[053] Batch [3599]/[3760] Speed: 93.355727 samples/sec accuracy=86.437934 loss=0.491034 lr=0.004378 Epoch[053] Batch [3649]/[3760] Speed: 92.884903 samples/sec accuracy=86.434075 loss=0.491389 lr=0.004376 Epoch[053] Batch [3699]/[3760] Speed: 93.764159 samples/sec accuracy=86.420186 loss=0.491828 lr=0.004374 Epoch[053] Batch [3749]/[3760] Speed: 105.375672 samples/sec accuracy=86.415833 loss=0.492035 lr=0.004372 Batch [0049]/[0303]: acc-top1=66.125000 acc-top5=84.937500 Batch [0099]/[0303]: acc-top1=64.093750 acc-top5=84.578125 Batch [0149]/[0303]: acc-top1=64.895833 acc-top5=84.937500 Batch [0199]/[0303]: acc-top1=67.273438 acc-top5=86.156250 Batch [0249]/[0303]: acc-top1=66.631250 acc-top5=85.862500 Batch [0299]/[0303]: acc-top1=66.078125 acc-top5=85.932292 [Epoch 053] training: accuracy=86.411652 loss=0.492102 [Epoch 053] speed: 93 samples/sec time cost: 2796.980733 [Epoch 053] validation: acc-top1=66.001444 acc-top5=85.916873 loss=2.223216 Epoch[054] Batch [0049]/[3760] Speed: 64.127979 samples/sec accuracy=87.843750 loss=0.446616 lr=0.004370 Epoch[054] Batch [0099]/[3760] Speed: 93.892978 samples/sec accuracy=86.906250 loss=0.473073 lr=0.004368 Epoch[054] Batch [0149]/[3760] Speed: 93.741465 samples/sec accuracy=87.322917 loss=0.467514 lr=0.004366 Epoch[054] Batch [0199]/[3760] Speed: 94.360726 samples/sec accuracy=87.593750 loss=0.460382 lr=0.004364 Epoch[054] Batch [0249]/[3760] Speed: 93.568215 samples/sec accuracy=87.550000 loss=0.461846 lr=0.004361 Epoch[054] Batch [0299]/[3760] Speed: 93.589349 samples/sec accuracy=87.484375 loss=0.462652 lr=0.004359 Epoch[054] Batch [0349]/[3760] Speed: 93.677452 samples/sec 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accuracy=87.420673 loss=0.456139 lr=0.004318 Epoch[054] Batch [1349]/[3760] Speed: 94.349954 samples/sec accuracy=87.408565 loss=0.456703 lr=0.004316 Epoch[054] Batch [1399]/[3760] Speed: 93.040521 samples/sec accuracy=87.387277 loss=0.456783 lr=0.004314 Epoch[054] Batch [1449]/[3760] Speed: 94.394684 samples/sec accuracy=87.363147 loss=0.457284 lr=0.004312 Epoch[054] Batch [1499]/[3760] Speed: 93.687237 samples/sec accuracy=87.359375 loss=0.457489 lr=0.004310 Epoch[054] Batch [1549]/[3760] Speed: 93.123661 samples/sec accuracy=87.384073 loss=0.456801 lr=0.004308 Epoch[054] Batch [1599]/[3760] Speed: 94.216442 samples/sec accuracy=87.350586 loss=0.457721 lr=0.004306 Epoch[054] Batch [1649]/[3760] Speed: 93.395557 samples/sec accuracy=87.348485 loss=0.457907 lr=0.004304 Epoch[054] Batch [1699]/[3760] Speed: 94.146904 samples/sec accuracy=87.346507 loss=0.458214 lr=0.004301 Epoch[054] Batch [1749]/[3760] Speed: 93.432938 samples/sec accuracy=87.360714 loss=0.458132 lr=0.004299 Epoch[054] 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accuracy=87.058105 loss=0.470055 lr=0.004239 Epoch[054] Batch [3249]/[3760] Speed: 92.388894 samples/sec accuracy=87.030288 loss=0.470868 lr=0.004237 Epoch[054] Batch [3299]/[3760] Speed: 94.307087 samples/sec accuracy=87.018939 loss=0.471572 lr=0.004235 Epoch[054] Batch [3349]/[3760] Speed: 93.130424 samples/sec accuracy=87.019123 loss=0.471552 lr=0.004233 Epoch[054] Batch [3399]/[3760] Speed: 93.186573 samples/sec accuracy=87.007812 loss=0.472094 lr=0.004231 Epoch[054] Batch [3449]/[3760] Speed: 94.537203 samples/sec accuracy=86.993207 loss=0.472786 lr=0.004229 Epoch[054] Batch [3499]/[3760] Speed: 93.129031 samples/sec accuracy=86.973214 loss=0.473577 lr=0.004227 Epoch[054] Batch [3549]/[3760] Speed: 94.450732 samples/sec accuracy=86.964349 loss=0.474064 lr=0.004225 Epoch[054] Batch [3599]/[3760] Speed: 93.881714 samples/sec accuracy=86.962674 loss=0.474258 lr=0.004223 Epoch[054] Batch [3649]/[3760] Speed: 92.864800 samples/sec accuracy=86.943921 loss=0.474871 lr=0.004221 Epoch[054] Batch [3699]/[3760] Speed: 94.645964 samples/sec accuracy=86.942145 loss=0.474717 lr=0.004219 Epoch[054] Batch [3749]/[3760] Speed: 103.795421 samples/sec accuracy=86.927083 loss=0.475368 lr=0.004217 Batch [0049]/[0303]: acc-top1=64.031250 acc-top5=84.312500 Batch [0099]/[0303]: acc-top1=63.171875 acc-top5=84.343750 Batch [0149]/[0303]: acc-top1=64.583333 acc-top5=85.041667 Batch [0199]/[0303]: acc-top1=67.296875 acc-top5=86.429688 Batch [0249]/[0303]: acc-top1=66.812500 acc-top5=86.093750 Batch [0299]/[0303]: acc-top1=66.187500 acc-top5=85.968750 [Epoch 054] training: accuracy=86.931516 loss=0.475264 [Epoch 054] speed: 93 samples/sec time cost: 2796.775283 [Epoch 054] validation: acc-top1=66.202558 acc-top5=85.963284 loss=2.225031 Epoch[055] Batch [0049]/[3759] Speed: 64.503966 samples/sec accuracy=89.031250 loss=0.398355 lr=0.004214 Epoch[055] Batch [0099]/[3759] Speed: 94.664848 samples/sec accuracy=88.406250 loss=0.424588 lr=0.004212 Epoch[055] Batch [0149]/[3759] Speed: 92.929802 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lr=0.004113 Epoch[055] Batch [2549]/[3759] Speed: 94.692423 samples/sec accuracy=87.574142 loss=0.447296 lr=0.004111 Epoch[055] Batch [2599]/[3759] Speed: 94.246400 samples/sec accuracy=87.563101 loss=0.447690 lr=0.004109 Epoch[055] Batch [2649]/[3759] Speed: 94.535933 samples/sec accuracy=87.543042 loss=0.448365 lr=0.004107 Epoch[055] Batch [2699]/[3759] Speed: 92.760538 samples/sec accuracy=87.536458 loss=0.448357 lr=0.004105 Epoch[055] Batch [2749]/[3759] Speed: 93.146524 samples/sec accuracy=87.532955 loss=0.448658 lr=0.004103 Epoch[055] Batch [2799]/[3759] Speed: 94.378002 samples/sec accuracy=87.517857 loss=0.449513 lr=0.004101 Epoch[055] Batch [2849]/[3759] Speed: 92.918017 samples/sec accuracy=87.502193 loss=0.450219 lr=0.004099 Epoch[055] Batch [2899]/[3759] Speed: 94.651561 samples/sec accuracy=87.488685 loss=0.450549 lr=0.004097 Epoch[055] Batch [2949]/[3759] Speed: 93.351177 samples/sec accuracy=87.488347 loss=0.450980 lr=0.004095 Epoch[055] Batch [2999]/[3759] Speed: 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lr=0.004074 Epoch[055] Batch [3499]/[3759] Speed: 94.331718 samples/sec accuracy=87.324554 loss=0.456356 lr=0.004072 Epoch[055] Batch [3549]/[3759] Speed: 93.006935 samples/sec accuracy=87.315141 loss=0.456612 lr=0.004070 Epoch[055] Batch [3599]/[3759] Speed: 93.837541 samples/sec accuracy=87.292101 loss=0.457445 lr=0.004068 Epoch[055] Batch [3649]/[3759] Speed: 93.849666 samples/sec accuracy=87.280394 loss=0.457930 lr=0.004066 Epoch[055] Batch [3699]/[3759] Speed: 93.268193 samples/sec accuracy=87.272804 loss=0.458168 lr=0.004064 Epoch[055] Batch [3749]/[3759] Speed: 107.935751 samples/sec accuracy=87.256250 loss=0.458725 lr=0.004062 Batch [0049]/[0303]: acc-top1=64.250000 acc-top5=83.906250 Batch [0099]/[0303]: acc-top1=62.781250 acc-top5=84.140625 Batch [0149]/[0303]: acc-top1=64.093750 acc-top5=85.052083 Batch [0199]/[0303]: acc-top1=66.820312 acc-top5=86.460938 Batch [0249]/[0303]: acc-top1=66.362500 acc-top5=86.031250 Batch [0299]/[0303]: acc-top1=65.765625 acc-top5=86.015625 [Epoch 055] training: accuracy=87.257249 loss=0.458701 [Epoch 055] speed: 93 samples/sec time cost: 2795.613142 [Epoch 055] validation: acc-top1=65.738449 acc-top5=86.020008 loss=2.289925 Epoch[056] Batch [0049]/[3760] Speed: 65.109776 samples/sec accuracy=88.187500 loss=0.426046 lr=0.004060 Epoch[056] Batch [0099]/[3760] Speed: 93.812693 samples/sec accuracy=88.468750 loss=0.421086 lr=0.004057 Epoch[056] Batch [0149]/[3760] Speed: 93.423068 samples/sec accuracy=88.718750 loss=0.416803 lr=0.004055 Epoch[056] Batch [0199]/[3760] Speed: 93.207488 samples/sec accuracy=88.789062 loss=0.414720 lr=0.004053 Epoch[056] Batch [0249]/[3760] Speed: 93.844394 samples/sec accuracy=88.943750 loss=0.412300 lr=0.004051 Epoch[056] Batch [0299]/[3760] Speed: 93.072577 samples/sec accuracy=88.812500 loss=0.416666 lr=0.004049 Epoch[056] Batch [0349]/[3760] Speed: 93.988523 samples/sec accuracy=88.745536 loss=0.417482 lr=0.004047 Epoch[056] Batch [0399]/[3760] Speed: 93.644550 samples/sec accuracy=88.804688 loss=0.414622 lr=0.004045 Epoch[056] Batch [0449]/[3760] Speed: 93.472728 samples/sec accuracy=88.684028 loss=0.417745 lr=0.004043 Epoch[056] Batch [0499]/[3760] Speed: 95.204900 samples/sec accuracy=88.687500 loss=0.417037 lr=0.004041 Epoch[056] Batch [0549]/[3760] Speed: 93.526677 samples/sec accuracy=88.698864 loss=0.415919 lr=0.004039 Epoch[056] Batch [0599]/[3760] Speed: 93.794967 samples/sec accuracy=88.677083 loss=0.417458 lr=0.004037 Epoch[056] Batch [0649]/[3760] Speed: 93.575883 samples/sec accuracy=88.675481 loss=0.416535 lr=0.004035 Epoch[056] Batch [0699]/[3760] Speed: 91.845847 samples/sec accuracy=88.631696 loss=0.416302 lr=0.004033 Epoch[056] Batch [0749]/[3760] Speed: 95.161193 samples/sec accuracy=88.637500 loss=0.416321 lr=0.004031 Epoch[056] Batch [0799]/[3760] Speed: 92.968396 samples/sec accuracy=88.554688 loss=0.418237 lr=0.004029 Epoch[056] Batch [0849]/[3760] Speed: 94.656254 samples/sec accuracy=88.523897 loss=0.420572 lr=0.004027 Epoch[056] Batch [0899]/[3760] Speed: 93.935791 samples/sec accuracy=88.543403 loss=0.419743 lr=0.004025 Epoch[056] Batch [0949]/[3760] Speed: 93.590821 samples/sec accuracy=88.564145 loss=0.420166 lr=0.004023 Epoch[056] Batch [0999]/[3760] Speed: 93.018264 samples/sec accuracy=88.575000 loss=0.420119 lr=0.004021 Epoch[056] Batch [1049]/[3760] Speed: 92.381409 samples/sec accuracy=88.534226 loss=0.420836 lr=0.004019 Epoch[056] Batch [1099]/[3760] Speed: 94.514870 samples/sec accuracy=88.487216 loss=0.421946 lr=0.004016 Epoch[056] Batch [1149]/[3760] Speed: 92.933222 samples/sec accuracy=88.467391 loss=0.422662 lr=0.004014 Epoch[056] Batch [1199]/[3760] Speed: 94.506550 samples/sec accuracy=88.451823 loss=0.423179 lr=0.004012 Epoch[056] Batch [1249]/[3760] Speed: 93.978487 samples/sec accuracy=88.422500 loss=0.423972 lr=0.004010 Epoch[056] Batch [1299]/[3760] Speed: 92.316695 samples/sec accuracy=88.461538 loss=0.423081 lr=0.004008 Epoch[056] Batch [1349]/[3760] Speed: 94.928465 samples/sec accuracy=88.481481 loss=0.422473 lr=0.004006 Epoch[056] Batch [1399]/[3760] Speed: 93.764541 samples/sec accuracy=88.478795 loss=0.422342 lr=0.004004 Epoch[056] Batch [1449]/[3760] Speed: 93.481602 samples/sec accuracy=88.413793 loss=0.423834 lr=0.004002 Epoch[056] Batch [1499]/[3760] Speed: 93.631317 samples/sec accuracy=88.387500 loss=0.424394 lr=0.004000 Epoch[056] Batch [1549]/[3760] Speed: 93.880665 samples/sec accuracy=88.366935 loss=0.425475 lr=0.003998 Epoch[056] Batch [1599]/[3760] Speed: 94.231008 samples/sec accuracy=88.329102 loss=0.427136 lr=0.003996 Epoch[056] Batch [1649]/[3760] Speed: 92.925807 samples/sec accuracy=88.291667 loss=0.428066 lr=0.003994 Epoch[056] Batch [1699]/[3760] Speed: 94.820301 samples/sec accuracy=88.296875 loss=0.428292 lr=0.003992 Epoch[056] Batch [1749]/[3760] Speed: 93.438707 samples/sec accuracy=88.296429 loss=0.429112 lr=0.003990 Epoch[056] Batch [1799]/[3760] Speed: 93.372998 samples/sec accuracy=88.286458 loss=0.429364 lr=0.003988 Epoch[056] Batch [1849]/[3760] Speed: 93.425218 samples/sec accuracy=88.282939 loss=0.429689 lr=0.003986 Epoch[056] Batch [1899]/[3760] Speed: 94.057409 samples/sec accuracy=88.247533 loss=0.430414 lr=0.003984 Epoch[056] Batch [1949]/[3760] Speed: 94.036253 samples/sec accuracy=88.236378 loss=0.430817 lr=0.003982 Epoch[056] Batch [1999]/[3760] Speed: 93.465373 samples/sec accuracy=88.219531 loss=0.431796 lr=0.003980 Epoch[056] Batch [2049]/[3760] Speed: 94.286042 samples/sec accuracy=88.188262 loss=0.432408 lr=0.003978 Epoch[056] Batch [2099]/[3760] Speed: 93.419939 samples/sec accuracy=88.157738 loss=0.432586 lr=0.003976 Epoch[056] Batch [2149]/[3760] Speed: 94.120022 samples/sec accuracy=88.151163 loss=0.432947 lr=0.003974 Epoch[056] Batch [2199]/[3760] Speed: 93.937176 samples/sec accuracy=88.149148 loss=0.432885 lr=0.003971 Epoch[056] Batch [2249]/[3760] Speed: 92.283737 samples/sec accuracy=88.147917 loss=0.432934 lr=0.003969 Epoch[056] Batch [2299]/[3760] Speed: 95.534677 samples/sec accuracy=88.135870 loss=0.433266 lr=0.003967 Epoch[056] Batch [2349]/[3760] Speed: 92.839138 samples/sec accuracy=88.115691 loss=0.433886 lr=0.003965 Epoch[056] Batch [2399]/[3760] Speed: 93.954514 samples/sec accuracy=88.092448 loss=0.434476 lr=0.003963 Epoch[056] Batch [2449]/[3760] Speed: 93.891322 samples/sec accuracy=88.092474 loss=0.434528 lr=0.003961 Epoch[056] Batch [2499]/[3760] Speed: 93.645672 samples/sec accuracy=88.089375 loss=0.434824 lr=0.003959 Epoch[056] Batch [2549]/[3760] Speed: 93.365607 samples/sec accuracy=88.071691 loss=0.435157 lr=0.003957 Epoch[056] Batch [2599]/[3760] Speed: 93.872971 samples/sec accuracy=88.066106 loss=0.435118 lr=0.003955 Epoch[056] Batch [2649]/[3760] Speed: 94.286733 samples/sec accuracy=88.041863 loss=0.435986 lr=0.003953 Epoch[056] Batch [2699]/[3760] Speed: 94.124692 samples/sec accuracy=88.029514 loss=0.436623 lr=0.003951 Epoch[056] Batch [2749]/[3760] Speed: 94.062147 samples/sec accuracy=88.015341 loss=0.437227 lr=0.003949 Epoch[056] Batch [2799]/[3760] Speed: 93.866878 samples/sec accuracy=88.008371 loss=0.437380 lr=0.003947 Epoch[056] Batch [2849]/[3760] Speed: 93.639882 samples/sec accuracy=87.996711 loss=0.437785 lr=0.003945 Epoch[056] Batch [2899]/[3760] Speed: 93.173370 samples/sec accuracy=87.979526 loss=0.438195 lr=0.003943 Epoch[056] Batch [2949]/[3760] Speed: 92.991758 samples/sec accuracy=87.979873 loss=0.438140 lr=0.003941 Epoch[056] Batch [2999]/[3760] Speed: 94.621565 samples/sec accuracy=87.997917 loss=0.437802 lr=0.003939 Epoch[056] Batch [3049]/[3760] Speed: 92.831069 samples/sec accuracy=87.974898 loss=0.438217 lr=0.003937 Epoch[056] Batch [3099]/[3760] Speed: 93.702362 samples/sec accuracy=87.975806 loss=0.438222 lr=0.003935 Epoch[056] Batch [3149]/[3760] Speed: 93.716488 samples/sec accuracy=87.961310 loss=0.438490 lr=0.003933 Epoch[056] Batch [3199]/[3760] Speed: 94.557353 samples/sec accuracy=87.961914 loss=0.438625 lr=0.003931 Epoch[056] Batch [3249]/[3760] Speed: 93.179413 samples/sec accuracy=87.961058 loss=0.438746 lr=0.003929 Epoch[056] Batch [3299]/[3760] Speed: 93.458073 samples/sec accuracy=87.962121 loss=0.439041 lr=0.003927 Epoch[056] Batch [3349]/[3760] Speed: 94.642714 samples/sec accuracy=87.938899 loss=0.439380 lr=0.003924 Epoch[056] Batch [3399]/[3760] Speed: 93.946951 samples/sec accuracy=87.934283 loss=0.439411 lr=0.003922 Epoch[056] Batch [3449]/[3760] Speed: 93.500364 samples/sec accuracy=87.927083 loss=0.439774 lr=0.003920 Epoch[056] Batch [3499]/[3760] Speed: 94.085517 samples/sec accuracy=87.932143 loss=0.439826 lr=0.003918 Epoch[056] Batch [3549]/[3760] Speed: 92.846681 samples/sec accuracy=87.932218 loss=0.439915 lr=0.003916 Epoch[056] Batch [3599]/[3760] Speed: 95.060867 samples/sec accuracy=87.917969 loss=0.440549 lr=0.003914 Epoch[056] Batch [3649]/[3760] Speed: 93.144854 samples/sec accuracy=87.930223 loss=0.440303 lr=0.003912 Epoch[056] Batch [3699]/[3760] Speed: 93.951649 samples/sec accuracy=87.915541 loss=0.440897 lr=0.003910 Epoch[056] Batch [3749]/[3760] Speed: 105.992207 samples/sec accuracy=87.906667 loss=0.441391 lr=0.003908 Batch [0049]/[0303]: acc-top1=63.187500 acc-top5=84.312500 Batch [0099]/[0303]: acc-top1=61.375000 acc-top5=83.390625 Batch [0149]/[0303]: acc-top1=62.864583 acc-top5=84.322917 Batch [0199]/[0303]: acc-top1=66.023438 acc-top5=85.828125 Batch [0249]/[0303]: acc-top1=65.356250 acc-top5=85.312500 Batch [0299]/[0303]: acc-top1=64.833333 acc-top5=85.317708 [Epoch 056] training: accuracy=87.893118 loss=0.441773 [Epoch 056] speed: 93 samples/sec time cost: 2796.007365 [Epoch 056] validation: acc-top1=64.738036 acc-top5=85.282591 loss=2.307476 Epoch[057] Batch [0049]/[3760] Speed: 64.759571 samples/sec accuracy=89.750000 loss=0.376419 lr=0.003906 Epoch[057] Batch [0099]/[3760] Speed: 95.183118 samples/sec accuracy=89.687500 loss=0.384864 lr=0.003904 Epoch[057] Batch [0149]/[3760] Speed: 93.717364 samples/sec accuracy=89.375000 loss=0.391076 lr=0.003902 Epoch[057] Batch [0199]/[3760] Speed: 94.117618 samples/sec accuracy=89.312500 loss=0.395988 lr=0.003900 Epoch[057] Batch [0249]/[3760] Speed: 93.485603 samples/sec accuracy=89.443750 loss=0.390254 lr=0.003898 Epoch[057] Batch [0299]/[3760] Speed: 93.087033 samples/sec accuracy=89.473958 loss=0.389000 lr=0.003896 Epoch[057] Batch [0349]/[3760] Speed: 93.846724 samples/sec accuracy=89.446429 loss=0.388040 lr=0.003893 Epoch[057] Batch [0399]/[3760] Speed: 93.775294 samples/sec accuracy=89.519531 loss=0.385940 lr=0.003891 Epoch[057] Batch [0449]/[3760] Speed: 94.707013 samples/sec accuracy=89.479167 loss=0.386577 lr=0.003889 Epoch[057] Batch [0499]/[3760] Speed: 93.797747 samples/sec accuracy=89.365625 loss=0.391081 lr=0.003887 Epoch[057] Batch [0549]/[3760] Speed: 94.437845 samples/sec accuracy=89.397727 loss=0.392605 lr=0.003885 Epoch[057] Batch [0599]/[3760] Speed: 93.877377 samples/sec accuracy=89.325521 loss=0.394302 lr=0.003883 Epoch[057] Batch [0649]/[3760] Speed: 93.453147 samples/sec accuracy=89.326923 loss=0.394328 lr=0.003881 Epoch[057] Batch [0699]/[3760] Speed: 93.249750 samples/sec accuracy=89.325893 loss=0.395488 lr=0.003879 Epoch[057] Batch [0749]/[3760] Speed: 92.949697 samples/sec accuracy=89.264583 loss=0.397903 lr=0.003877 Epoch[057] Batch [0799]/[3760] Speed: 94.280588 samples/sec accuracy=89.191406 loss=0.399852 lr=0.003875 Epoch[057] Batch [0849]/[3760] Speed: 94.121933 samples/sec accuracy=89.202206 loss=0.399060 lr=0.003873 Epoch[057] Batch [0899]/[3760] Speed: 94.594612 samples/sec accuracy=89.171875 loss=0.400339 lr=0.003871 Epoch[057] Batch [0949]/[3760] Speed: 93.082569 samples/sec accuracy=89.116776 loss=0.401461 lr=0.003869 Epoch[057] Batch [0999]/[3760] Speed: 93.756178 samples/sec accuracy=89.089063 loss=0.402181 lr=0.003867 Epoch[057] Batch [1049]/[3760] Speed: 94.366362 samples/sec accuracy=89.058036 loss=0.402890 lr=0.003865 Epoch[057] Batch [1099]/[3760] Speed: 93.069423 samples/sec accuracy=89.015625 loss=0.403430 lr=0.003863 Epoch[057] Batch [1149]/[3760] Speed: 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lr=0.003804 Epoch[057] Batch [2599]/[3760] Speed: 92.523577 samples/sec accuracy=88.572115 loss=0.414586 lr=0.003802 Epoch[057] Batch [2649]/[3760] Speed: 93.905918 samples/sec accuracy=88.554245 loss=0.415129 lr=0.003800 Epoch[057] Batch [2699]/[3760] Speed: 94.358274 samples/sec accuracy=88.543981 loss=0.415272 lr=0.003798 Epoch[057] Batch [2749]/[3760] Speed: 92.060211 samples/sec accuracy=88.526705 loss=0.415882 lr=0.003796 Epoch[057] Batch [2799]/[3760] Speed: 95.737829 samples/sec accuracy=88.531808 loss=0.415858 lr=0.003794 Epoch[057] Batch [2849]/[3760] Speed: 92.502509 samples/sec accuracy=88.526864 loss=0.416319 lr=0.003792 Epoch[057] Batch [2899]/[3760] Speed: 94.347976 samples/sec accuracy=88.514009 loss=0.416617 lr=0.003790 Epoch[057] Batch [2949]/[3760] Speed: 94.098526 samples/sec accuracy=88.502648 loss=0.416994 lr=0.003788 Epoch[057] Batch [2999]/[3760] Speed: 93.660610 samples/sec accuracy=88.486458 loss=0.417382 lr=0.003786 Epoch[057] Batch [3049]/[3760] Speed: 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lr=0.003766 Epoch[057] Batch [3549]/[3760] Speed: 92.971737 samples/sec accuracy=88.344190 loss=0.422015 lr=0.003763 Epoch[057] Batch [3599]/[3760] Speed: 95.166446 samples/sec accuracy=88.326823 loss=0.422861 lr=0.003761 Epoch[057] Batch [3649]/[3760] Speed: 93.826620 samples/sec accuracy=88.308647 loss=0.423515 lr=0.003759 Epoch[057] Batch [3699]/[3760] Speed: 93.995466 samples/sec accuracy=88.311655 loss=0.423679 lr=0.003757 Epoch[057] Batch [3749]/[3760] Speed: 105.139196 samples/sec accuracy=88.303750 loss=0.424045 lr=0.003755 Batch [0049]/[0303]: acc-top1=65.250000 acc-top5=84.906250 Batch [0099]/[0303]: acc-top1=63.984375 acc-top5=84.828125 Batch [0149]/[0303]: acc-top1=64.833333 acc-top5=85.500000 Batch [0199]/[0303]: acc-top1=67.546875 acc-top5=86.718750 Batch [0249]/[0303]: acc-top1=66.887500 acc-top5=86.293750 Batch [0299]/[0303]: acc-top1=66.322917 acc-top5=86.171875 [Epoch 057] training: accuracy=88.294963 loss=0.424223 [Epoch 057] speed: 93 samples/sec time cost: 2795.144430 [Epoch 057] validation: acc-top1=66.274752 acc-top5=86.148927 loss=2.191678 Epoch[058] Batch [0049]/[3759] Speed: 64.605293 samples/sec accuracy=89.781250 loss=0.370664 lr=0.003753 Epoch[058] Batch [0099]/[3759] Speed: 94.527558 samples/sec accuracy=89.625000 loss=0.377629 lr=0.003751 Epoch[058] Batch [0149]/[3759] Speed: 93.600645 samples/sec accuracy=89.708333 loss=0.376423 lr=0.003749 Epoch[058] Batch [0199]/[3759] Speed: 95.149614 samples/sec accuracy=89.640625 loss=0.375125 lr=0.003747 Epoch[058] Batch [0249]/[3759] Speed: 93.401309 samples/sec accuracy=89.406250 loss=0.378787 lr=0.003745 Epoch[058] Batch [0299]/[3759] Speed: 94.292526 samples/sec accuracy=89.515625 loss=0.377601 lr=0.003743 Epoch[058] Batch [0349]/[3759] Speed: 93.448614 samples/sec accuracy=89.531250 loss=0.380066 lr=0.003741 Epoch[058] Batch [0399]/[3759] Speed: 93.849278 samples/sec accuracy=89.417969 loss=0.383451 lr=0.003739 Epoch[058] Batch [0449]/[3759] Speed: 93.479530 samples/sec accuracy=89.454861 loss=0.382513 lr=0.003737 Epoch[058] Batch [0499]/[3759] Speed: 92.018034 samples/sec accuracy=89.456250 loss=0.382428 lr=0.003735 Epoch[058] Batch [0549]/[3759] Speed: 94.337542 samples/sec accuracy=89.426136 loss=0.383083 lr=0.003733 Epoch[058] Batch [0599]/[3759] Speed: 93.894147 samples/sec accuracy=89.372396 loss=0.384275 lr=0.003731 Epoch[058] Batch [0649]/[3759] Speed: 94.417746 samples/sec accuracy=89.389423 loss=0.384365 lr=0.003729 Epoch[058] Batch [0699]/[3759] Speed: 93.039671 samples/sec accuracy=89.388393 loss=0.382838 lr=0.003727 Epoch[058] Batch [0749]/[3759] Speed: 93.464621 samples/sec accuracy=89.366667 loss=0.384050 lr=0.003725 Epoch[058] Batch [0799]/[3759] Speed: 94.627401 samples/sec accuracy=89.394531 loss=0.383715 lr=0.003723 Epoch[058] Batch [0849]/[3759] Speed: 92.489055 samples/sec accuracy=89.415441 loss=0.383190 lr=0.003721 Epoch[058] Batch [0899]/[3759] Speed: 95.610646 samples/sec accuracy=89.314236 loss=0.385282 lr=0.003719 Epoch[058] 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accuracy=89.209821 loss=0.389689 lr=0.003698 Epoch[058] Batch [1449]/[3759] Speed: 94.136445 samples/sec accuracy=89.201509 loss=0.390105 lr=0.003696 Epoch[058] Batch [1499]/[3759] Speed: 93.188835 samples/sec accuracy=89.173958 loss=0.390696 lr=0.003694 Epoch[058] Batch [1549]/[3759] Speed: 93.768611 samples/sec accuracy=89.177419 loss=0.390797 lr=0.003692 Epoch[058] Batch [1599]/[3759] Speed: 93.210147 samples/sec accuracy=89.172852 loss=0.390838 lr=0.003690 Epoch[058] Batch [1649]/[3759] Speed: 93.036678 samples/sec accuracy=89.150568 loss=0.391519 lr=0.003688 Epoch[058] Batch [1699]/[3759] Speed: 95.039984 samples/sec accuracy=89.150735 loss=0.391714 lr=0.003686 Epoch[058] Batch [1749]/[3759] Speed: 93.064621 samples/sec accuracy=89.125893 loss=0.391989 lr=0.003684 Epoch[058] Batch [1799]/[3759] Speed: 94.196836 samples/sec accuracy=89.090278 loss=0.393045 lr=0.003682 Epoch[058] Batch [1849]/[3759] Speed: 93.483566 samples/sec accuracy=89.062500 loss=0.394214 lr=0.003680 Epoch[058] 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accuracy=88.883644 loss=0.400321 lr=0.003660 Epoch[058] Batch [2399]/[3759] Speed: 93.866294 samples/sec accuracy=88.885417 loss=0.400206 lr=0.003658 Epoch[058] Batch [2449]/[3759] Speed: 92.442594 samples/sec accuracy=88.867347 loss=0.400936 lr=0.003656 Epoch[058] Batch [2499]/[3759] Speed: 94.699666 samples/sec accuracy=88.865000 loss=0.401151 lr=0.003654 Epoch[058] Batch [2549]/[3759] Speed: 92.918902 samples/sec accuracy=88.837010 loss=0.402055 lr=0.003652 Epoch[058] Batch [2599]/[3759] Speed: 94.630059 samples/sec accuracy=88.834736 loss=0.402404 lr=0.003650 Epoch[058] Batch [2649]/[3759] Speed: 92.991479 samples/sec accuracy=88.829599 loss=0.402997 lr=0.003648 Epoch[058] Batch [2699]/[3759] Speed: 94.175557 samples/sec accuracy=88.828704 loss=0.403089 lr=0.003646 Epoch[058] Batch [2749]/[3759] Speed: 93.833320 samples/sec accuracy=88.823295 loss=0.403465 lr=0.003644 Epoch[058] Batch [2799]/[3759] Speed: 93.342946 samples/sec accuracy=88.800223 loss=0.404464 lr=0.003642 Epoch[058] 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accuracy=88.777936 loss=0.405629 lr=0.003622 Epoch[058] Batch [3349]/[3759] Speed: 93.048873 samples/sec accuracy=88.780317 loss=0.405780 lr=0.003620 Epoch[058] Batch [3399]/[3759] Speed: 94.651301 samples/sec accuracy=88.774357 loss=0.405764 lr=0.003618 Epoch[058] Batch [3449]/[3759] Speed: 93.857448 samples/sec accuracy=88.772192 loss=0.405686 lr=0.003616 Epoch[058] Batch [3499]/[3759] Speed: 93.752372 samples/sec accuracy=88.767411 loss=0.405897 lr=0.003614 Epoch[058] Batch [3549]/[3759] Speed: 93.172758 samples/sec accuracy=88.765405 loss=0.406055 lr=0.003612 Epoch[058] Batch [3599]/[3759] Speed: 94.986337 samples/sec accuracy=88.757378 loss=0.406377 lr=0.003610 Epoch[058] Batch [3649]/[3759] Speed: 93.446015 samples/sec accuracy=88.741866 loss=0.406891 lr=0.003608 Epoch[058] Batch [3699]/[3759] Speed: 92.990784 samples/sec accuracy=88.739443 loss=0.406935 lr=0.003606 Epoch[058] Batch [3749]/[3759] Speed: 107.972366 samples/sec accuracy=88.737917 loss=0.406925 lr=0.003604 Batch [0049]/[0303]: acc-top1=63.937500 acc-top5=84.593750 Batch [0099]/[0303]: acc-top1=62.328125 acc-top5=84.328125 Batch [0149]/[0303]: acc-top1=63.968750 acc-top5=85.093750 Batch [0199]/[0303]: acc-top1=66.718750 acc-top5=86.437500 Batch [0249]/[0303]: acc-top1=66.475000 acc-top5=85.993750 Batch [0299]/[0303]: acc-top1=65.994792 acc-top5=85.958333 [Epoch 058] training: accuracy=88.739109 loss=0.406959 [Epoch 058] speed: 93 samples/sec time cost: 2795.368414 [Epoch 058] validation: acc-top1=65.918936 acc-top5=85.922030 loss=2.354557 Epoch[059] Batch [0049]/[3760] Speed: 64.776295 samples/sec accuracy=89.000000 loss=0.387778 lr=0.003601 Epoch[059] Batch [0099]/[3760] Speed: 94.728712 samples/sec accuracy=89.390625 loss=0.382277 lr=0.003599 Epoch[059] Batch [0149]/[3760] Speed: 94.000857 samples/sec accuracy=89.802083 loss=0.371693 lr=0.003597 Epoch[059] Batch [0199]/[3760] Speed: 92.527362 samples/sec accuracy=89.882812 loss=0.367545 lr=0.003595 Epoch[059] Batch [0249]/[3760] Speed: 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lr=0.003462 Epoch[059] Batch [3599]/[3760] Speed: 93.633593 samples/sec accuracy=89.360243 loss=0.387723 lr=0.003460 Epoch[059] Batch [3649]/[3760] Speed: 93.721999 samples/sec accuracy=89.351027 loss=0.387997 lr=0.003458 Epoch[059] Batch [3699]/[3760] Speed: 92.349458 samples/sec accuracy=89.339105 loss=0.388371 lr=0.003456 Epoch[059] Batch [3749]/[3760] Speed: 107.964535 samples/sec accuracy=89.331667 loss=0.388446 lr=0.003454 Batch [0049]/[0303]: acc-top1=64.843750 acc-top5=84.562500 Batch [0099]/[0303]: acc-top1=63.187500 acc-top5=84.703125 Batch [0149]/[0303]: acc-top1=64.666667 acc-top5=85.479167 Batch [0199]/[0303]: acc-top1=67.523438 acc-top5=86.929688 Batch [0249]/[0303]: acc-top1=66.981250 acc-top5=86.462500 Batch [0299]/[0303]: acc-top1=66.593750 acc-top5=86.328125 [Epoch 059] training: accuracy=89.333029 loss=0.388451 [Epoch 059] speed: 93 samples/sec time cost: 2794.243516 [Epoch 059] validation: acc-top1=66.563531 acc-top5=86.324257 loss=2.301590 Epoch[060] Batch 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accuracy=90.200000 loss=0.356764 lr=0.003433 Epoch[060] Batch [0549]/[3760] Speed: 94.623635 samples/sec accuracy=90.181818 loss=0.357854 lr=0.003432 Epoch[060] Batch [0599]/[3760] Speed: 93.580830 samples/sec accuracy=90.171875 loss=0.357667 lr=0.003430 Epoch[060] Batch [0649]/[3760] Speed: 93.393894 samples/sec accuracy=90.173077 loss=0.356699 lr=0.003428 Epoch[060] Batch [0699]/[3760] Speed: 93.263054 samples/sec accuracy=90.169643 loss=0.355847 lr=0.003426 Epoch[060] Batch [0749]/[3760] Speed: 94.163292 samples/sec accuracy=90.227083 loss=0.354376 lr=0.003424 Epoch[060] Batch [0799]/[3760] Speed: 93.433860 samples/sec accuracy=90.210938 loss=0.354301 lr=0.003422 Epoch[060] Batch [0849]/[3760] Speed: 93.214569 samples/sec accuracy=90.270221 loss=0.353203 lr=0.003420 Epoch[060] Batch [0899]/[3760] Speed: 94.953261 samples/sec accuracy=90.312500 loss=0.353030 lr=0.003418 Epoch[060] Batch [0949]/[3760] Speed: 94.009376 samples/sec accuracy=90.284539 loss=0.353866 lr=0.003416 Epoch[060] 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accuracy=90.107759 loss=0.359751 lr=0.003396 Epoch[060] Batch [1499]/[3760] Speed: 92.815034 samples/sec accuracy=90.132292 loss=0.359770 lr=0.003394 Epoch[060] Batch [1549]/[3760] Speed: 93.943090 samples/sec accuracy=90.141129 loss=0.359580 lr=0.003392 Epoch[060] Batch [1599]/[3760] Speed: 93.060457 samples/sec accuracy=90.141602 loss=0.359445 lr=0.003390 Epoch[060] Batch [1649]/[3760] Speed: 94.008061 samples/sec accuracy=90.130682 loss=0.359811 lr=0.003388 Epoch[060] Batch [1699]/[3760] Speed: 93.121041 samples/sec accuracy=90.110294 loss=0.360541 lr=0.003386 Epoch[060] Batch [1749]/[3760] Speed: 91.955831 samples/sec accuracy=90.065179 loss=0.361834 lr=0.003384 Epoch[060] Batch [1799]/[3760] Speed: 95.020894 samples/sec accuracy=90.074653 loss=0.361684 lr=0.003382 Epoch[060] Batch [1849]/[3760] Speed: 92.767843 samples/sec accuracy=90.059966 loss=0.362161 lr=0.003380 Epoch[060] Batch [1899]/[3760] Speed: 95.091158 samples/sec accuracy=90.036184 loss=0.363167 lr=0.003378 Epoch[060] 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accuracy=89.893229 loss=0.366784 lr=0.003358 Epoch[060] Batch [2449]/[3760] Speed: 94.437465 samples/sec accuracy=89.906888 loss=0.366720 lr=0.003356 Epoch[060] Batch [2499]/[3760] Speed: 93.661779 samples/sec accuracy=89.900000 loss=0.366786 lr=0.003354 Epoch[060] Batch [2549]/[3760] Speed: 93.912478 samples/sec accuracy=89.883578 loss=0.367814 lr=0.003352 Epoch[060] Batch [2599]/[3760] Speed: 93.716216 samples/sec accuracy=89.859375 loss=0.368749 lr=0.003350 Epoch[060] Batch [2649]/[3760] Speed: 93.776944 samples/sec accuracy=89.850825 loss=0.369230 lr=0.003348 Epoch[060] Batch [2699]/[3760] Speed: 92.865916 samples/sec accuracy=89.835648 loss=0.369827 lr=0.003346 Epoch[060] Batch [2749]/[3760] Speed: 91.890995 samples/sec accuracy=89.842614 loss=0.369616 lr=0.003344 Epoch[060] Batch [2799]/[3760] Speed: 95.228345 samples/sec accuracy=89.832589 loss=0.369804 lr=0.003343 Epoch[060] Batch [2849]/[3760] Speed: 92.768156 samples/sec accuracy=89.802083 loss=0.370728 lr=0.003341 Epoch[060] Batch [2899]/[3760] Speed: 94.711395 samples/sec accuracy=89.802802 loss=0.370994 lr=0.003339 Epoch[060] Batch [2949]/[3760] Speed: 93.020696 samples/sec accuracy=89.795021 loss=0.371503 lr=0.003337 Epoch[060] Batch [2999]/[3760] Speed: 94.488519 samples/sec accuracy=89.774479 loss=0.371997 lr=0.003335 Epoch[060] Batch [3049]/[3760] Speed: 92.997717 samples/sec accuracy=89.780225 loss=0.371675 lr=0.003333 Epoch[060] Batch [3099]/[3760] Speed: 94.070586 samples/sec accuracy=89.784274 loss=0.371572 lr=0.003331 Epoch[060] Batch [3149]/[3760] Speed: 94.147136 samples/sec accuracy=89.782242 loss=0.371761 lr=0.003329 Epoch[060] Batch [3199]/[3760] Speed: 93.358531 samples/sec accuracy=89.770020 loss=0.372093 lr=0.003327 Epoch[060] Batch [3249]/[3760] Speed: 93.773155 samples/sec accuracy=89.764423 loss=0.372384 lr=0.003325 Epoch[060] Batch [3299]/[3760] Speed: 92.835045 samples/sec accuracy=89.761837 loss=0.372519 lr=0.003323 Epoch[060] Batch [3349]/[3760] Speed: 95.934577 samples/sec accuracy=89.748601 loss=0.372769 lr=0.003321 Epoch[060] Batch [3399]/[3760] Speed: 92.666363 samples/sec accuracy=89.728401 loss=0.373449 lr=0.003319 Epoch[060] Batch [3449]/[3760] Speed: 94.177727 samples/sec accuracy=89.729167 loss=0.373393 lr=0.003317 Epoch[060] Batch [3499]/[3760] Speed: 92.837471 samples/sec accuracy=89.724107 loss=0.373831 lr=0.003315 Epoch[060] Batch [3549]/[3760] Speed: 93.697039 samples/sec accuracy=89.730634 loss=0.373798 lr=0.003313 Epoch[060] Batch [3599]/[3760] Speed: 93.709875 samples/sec accuracy=89.721354 loss=0.374183 lr=0.003311 Epoch[060] Batch [3649]/[3760] Speed: 93.971248 samples/sec accuracy=89.713613 loss=0.374565 lr=0.003309 Epoch[060] Batch [3699]/[3760] Speed: 93.713293 samples/sec accuracy=89.711993 loss=0.374761 lr=0.003307 Epoch[060] Batch [3749]/[3760] Speed: 105.746315 samples/sec accuracy=89.708750 loss=0.375082 lr=0.003305 Batch [0049]/[0303]: acc-top1=63.625000 acc-top5=83.531250 Batch [0099]/[0303]: acc-top1=62.000000 acc-top5=83.953125 Batch [0149]/[0303]: acc-top1=63.416667 acc-top5=84.614583 Batch [0199]/[0303]: acc-top1=66.234375 acc-top5=86.101562 Batch [0249]/[0303]: acc-top1=65.893750 acc-top5=85.850000 Batch [0299]/[0303]: acc-top1=65.494792 acc-top5=85.755208 [Epoch 060] training: accuracy=89.707862 loss=0.375111 [Epoch 060] speed: 93 samples/sec time cost: 2796.089835 [Epoch 060] validation: acc-top1=65.423886 acc-top5=85.720916 loss=2.347114 Epoch[061] Batch [0049]/[3759] Speed: 65.065316 samples/sec accuracy=91.000000 loss=0.334319 lr=0.003303 Epoch[061] Batch [0099]/[3759] Speed: 93.258346 samples/sec accuracy=90.750000 loss=0.349479 lr=0.003301 Epoch[061] Batch [0149]/[3759] Speed: 94.681069 samples/sec accuracy=90.541667 loss=0.347120 lr=0.003299 Epoch[061] Batch [0199]/[3759] Speed: 93.313537 samples/sec accuracy=90.593750 loss=0.345878 lr=0.003297 Epoch[061] Batch [0249]/[3759] Speed: 94.166863 samples/sec accuracy=90.518750 loss=0.350237 lr=0.003295 Epoch[061] Batch [0299]/[3759] 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accuracy=90.285156 loss=0.355072 lr=0.003164 Epoch[061] Batch [3649]/[3759] Speed: 94.017396 samples/sec accuracy=90.291524 loss=0.355064 lr=0.003162 Epoch[061] Batch [3699]/[3759] Speed: 92.941000 samples/sec accuracy=90.279561 loss=0.355396 lr=0.003160 Epoch[061] Batch [3749]/[3759] Speed: 107.975402 samples/sec accuracy=90.275833 loss=0.355576 lr=0.003158 Batch [0049]/[0303]: acc-top1=65.500000 acc-top5=85.281250 Batch [0099]/[0303]: acc-top1=63.468750 acc-top5=84.531250 Batch [0149]/[0303]: acc-top1=64.468750 acc-top5=85.229167 Batch [0199]/[0303]: acc-top1=66.820312 acc-top5=86.500000 Batch [0249]/[0303]: acc-top1=66.612500 acc-top5=86.406250 Batch [0299]/[0303]: acc-top1=66.036458 acc-top5=86.291667 [Epoch 061] training: accuracy=90.279579 loss=0.355551 [Epoch 061] speed: 93 samples/sec time cost: 2793.128362 [Epoch 061] validation: acc-top1=65.893152 acc-top5=86.252063 loss=2.386158 Epoch[062] Batch [0049]/[3760] Speed: 64.707823 samples/sec accuracy=91.718750 loss=0.295141 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94.624052 samples/sec accuracy=90.933364 loss=0.333715 lr=0.003026 Epoch[062] Batch [3449]/[3760] Speed: 93.352969 samples/sec accuracy=90.916214 loss=0.334398 lr=0.003025 Epoch[062] Batch [3499]/[3760] Speed: 93.482280 samples/sec accuracy=90.911161 loss=0.334438 lr=0.003023 Epoch[062] Batch [3549]/[3760] Speed: 93.183958 samples/sec accuracy=90.900968 loss=0.334721 lr=0.003021 Epoch[062] Batch [3599]/[3760] Speed: 92.593092 samples/sec accuracy=90.896267 loss=0.334874 lr=0.003019 Epoch[062] Batch [3649]/[3760] Speed: 94.747818 samples/sec accuracy=90.882705 loss=0.335278 lr=0.003017 Epoch[062] Batch [3699]/[3760] Speed: 92.794583 samples/sec accuracy=90.882179 loss=0.335240 lr=0.003015 Epoch[062] Batch [3749]/[3760] Speed: 107.723563 samples/sec accuracy=90.888333 loss=0.335055 lr=0.003013 Batch [0049]/[0303]: acc-top1=65.531250 acc-top5=84.812500 Batch [0099]/[0303]: acc-top1=64.203125 acc-top5=84.625000 Batch [0149]/[0303]: acc-top1=65.354167 acc-top5=85.406250 Batch [0199]/[0303]: acc-top1=67.695312 acc-top5=86.671875 Batch [0249]/[0303]: acc-top1=67.325000 acc-top5=86.212500 Batch [0299]/[0303]: acc-top1=66.817708 acc-top5=86.171875 [Epoch 062] training: accuracy=90.890542 loss=0.335020 [Epoch 062] speed: 93 samples/sec time cost: 2794.136663 [Epoch 062] validation: acc-top1=66.718234 acc-top5=86.112830 loss=2.297839 Epoch[063] Batch [0049]/[3760] Speed: 64.631457 samples/sec accuracy=91.812500 loss=0.309329 lr=0.003011 Epoch[063] Batch [0099]/[3760] Speed: 94.141903 samples/sec accuracy=91.640625 loss=0.306963 lr=0.003009 Epoch[063] Batch [0149]/[3760] Speed: 93.849236 samples/sec accuracy=91.687500 loss=0.302476 lr=0.003007 Epoch[063] Batch [0199]/[3760] Speed: 94.234685 samples/sec accuracy=91.742188 loss=0.303227 lr=0.003005 Epoch[063] Batch [0249]/[3760] Speed: 93.160519 samples/sec accuracy=91.837500 loss=0.296346 lr=0.003003 Epoch[063] Batch [0299]/[3760] Speed: 94.088832 samples/sec accuracy=91.802083 loss=0.298422 lr=0.003001 Epoch[063] Batch 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accuracy=91.493634 loss=0.313557 lr=0.002910 Epoch[063] Batch [2749]/[3760] Speed: 93.714898 samples/sec accuracy=91.487500 loss=0.313758 lr=0.002908 Epoch[063] Batch [2799]/[3760] Speed: 92.868519 samples/sec accuracy=91.488281 loss=0.313694 lr=0.002906 Epoch[063] Batch [2849]/[3760] Speed: 94.197041 samples/sec accuracy=91.486294 loss=0.313821 lr=0.002904 Epoch[063] Batch [2899]/[3760] Speed: 93.785641 samples/sec accuracy=91.477909 loss=0.314072 lr=0.002902 Epoch[063] Batch [2949]/[3760] Speed: 94.201061 samples/sec accuracy=91.454979 loss=0.314825 lr=0.002900 Epoch[063] Batch [2999]/[3760] Speed: 93.870681 samples/sec accuracy=91.446354 loss=0.315334 lr=0.002898 Epoch[063] Batch [3049]/[3760] Speed: 93.687592 samples/sec accuracy=91.436988 loss=0.315450 lr=0.002896 Epoch[063] Batch [3099]/[3760] Speed: 93.407384 samples/sec accuracy=91.428931 loss=0.315712 lr=0.002894 Epoch[063] Batch [3149]/[3760] Speed: 93.763436 samples/sec accuracy=91.423115 loss=0.315991 lr=0.002893 Epoch[063] 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accuracy=91.333048 loss=0.319520 lr=0.002874 Epoch[063] Batch [3699]/[3760] Speed: 94.834082 samples/sec accuracy=91.331926 loss=0.319577 lr=0.002872 Epoch[063] Batch [3749]/[3760] Speed: 105.043351 samples/sec accuracy=91.330833 loss=0.319823 lr=0.002870 Batch [0049]/[0303]: acc-top1=65.093750 acc-top5=84.625000 Batch [0099]/[0303]: acc-top1=63.109375 acc-top5=84.265625 Batch [0149]/[0303]: acc-top1=64.791667 acc-top5=85.114583 Batch [0199]/[0303]: acc-top1=67.382812 acc-top5=86.507812 Batch [0249]/[0303]: acc-top1=67.006250 acc-top5=86.031250 Batch [0299]/[0303]: acc-top1=66.692708 acc-top5=86.088542 [Epoch 063] training: accuracy=91.323138 loss=0.319914 [Epoch 063] speed: 93 samples/sec time cost: 2795.834591 [Epoch 063] validation: acc-top1=66.640883 acc-top5=86.045792 loss=2.308789 Epoch[064] Batch [0049]/[3759] Speed: 65.017091 samples/sec accuracy=92.593750 loss=0.273362 lr=0.002868 Epoch[064] Batch [0099]/[3759] Speed: 94.024226 samples/sec accuracy=92.468750 loss=0.275101 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lr=0.002830 Epoch[064] Batch [1099]/[3759] Speed: 94.114948 samples/sec accuracy=92.125000 loss=0.291231 lr=0.002828 Epoch[064] Batch [1149]/[3759] Speed: 93.234110 samples/sec accuracy=92.107337 loss=0.291885 lr=0.002826 Epoch[064] Batch [1199]/[3759] Speed: 93.436123 samples/sec accuracy=92.109375 loss=0.292132 lr=0.002824 Epoch[064] Batch [1249]/[3759] Speed: 93.120450 samples/sec accuracy=92.045000 loss=0.293466 lr=0.002822 Epoch[064] Batch [1299]/[3759] Speed: 94.427877 samples/sec accuracy=92.034856 loss=0.293936 lr=0.002820 Epoch[064] Batch [1349]/[3759] Speed: 93.753324 samples/sec accuracy=92.035880 loss=0.293951 lr=0.002819 Epoch[064] Batch [1399]/[3759] Speed: 93.827930 samples/sec accuracy=92.035714 loss=0.294658 lr=0.002817 Epoch[064] Batch [1449]/[3759] Speed: 93.483188 samples/sec accuracy=92.053879 loss=0.293928 lr=0.002815 Epoch[064] Batch [1499]/[3759] Speed: 93.941541 samples/sec accuracy=92.048958 loss=0.293757 lr=0.002813 Epoch[064] Batch [1549]/[3759] Speed: 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lr=0.002794 Epoch[064] Batch [2049]/[3759] Speed: 94.327336 samples/sec accuracy=91.900915 loss=0.298354 lr=0.002792 Epoch[064] Batch [2099]/[3759] Speed: 92.586627 samples/sec accuracy=91.887649 loss=0.298795 lr=0.002790 Epoch[064] Batch [2149]/[3759] Speed: 94.728166 samples/sec accuracy=91.876453 loss=0.298798 lr=0.002789 Epoch[064] Batch [2199]/[3759] Speed: 92.971549 samples/sec accuracy=91.880682 loss=0.299116 lr=0.002787 Epoch[064] Batch [2249]/[3759] Speed: 93.833821 samples/sec accuracy=91.874306 loss=0.299245 lr=0.002785 Epoch[064] Batch [2299]/[3759] Speed: 93.437365 samples/sec accuracy=91.875000 loss=0.298972 lr=0.002783 Epoch[064] Batch [2349]/[3759] Speed: 94.568259 samples/sec accuracy=91.867021 loss=0.299002 lr=0.002781 Epoch[064] Batch [2399]/[3759] Speed: 93.665831 samples/sec accuracy=91.859375 loss=0.298910 lr=0.002779 Epoch[064] Batch [2449]/[3759] Speed: 94.426828 samples/sec accuracy=91.840561 loss=0.299373 lr=0.002777 Epoch[064] Batch [2499]/[3759] Speed: 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lr=0.002759 Epoch[064] Batch [2999]/[3759] Speed: 94.883176 samples/sec accuracy=91.750000 loss=0.302239 lr=0.002757 Epoch[064] Batch [3049]/[3759] Speed: 92.949433 samples/sec accuracy=91.738217 loss=0.302397 lr=0.002755 Epoch[064] Batch [3099]/[3759] Speed: 94.986734 samples/sec accuracy=91.732863 loss=0.302626 lr=0.002753 Epoch[064] Batch [3149]/[3759] Speed: 93.038196 samples/sec accuracy=91.729167 loss=0.302582 lr=0.002751 Epoch[064] Batch [3199]/[3759] Speed: 94.500837 samples/sec accuracy=91.739258 loss=0.302356 lr=0.002749 Epoch[064] Batch [3249]/[3759] Speed: 92.786785 samples/sec accuracy=91.724038 loss=0.302683 lr=0.002747 Epoch[064] Batch [3299]/[3759] Speed: 93.850872 samples/sec accuracy=91.718750 loss=0.302864 lr=0.002746 Epoch[064] Batch [3349]/[3759] Speed: 93.241395 samples/sec accuracy=91.725280 loss=0.302919 lr=0.002744 Epoch[064] Batch [3399]/[3759] Speed: 94.388876 samples/sec accuracy=91.717371 loss=0.303080 lr=0.002742 Epoch[064] Batch [3449]/[3759] Speed: 93.277623 samples/sec accuracy=91.706522 loss=0.303447 lr=0.002740 Epoch[064] Batch [3499]/[3759] Speed: 94.429902 samples/sec accuracy=91.697768 loss=0.303571 lr=0.002738 Epoch[064] Batch [3549]/[3759] Speed: 93.800127 samples/sec accuracy=91.705106 loss=0.303306 lr=0.002736 Epoch[064] Batch [3599]/[3759] Speed: 94.089550 samples/sec accuracy=91.704861 loss=0.303633 lr=0.002734 Epoch[064] Batch [3649]/[3759] Speed: 93.163570 samples/sec accuracy=91.705051 loss=0.303698 lr=0.002733 Epoch[064] Batch [3699]/[3759] Speed: 93.912943 samples/sec accuracy=91.691301 loss=0.304186 lr=0.002731 Epoch[064] Batch [3749]/[3759] Speed: 105.958158 samples/sec accuracy=91.693750 loss=0.304061 lr=0.002729 Batch [0049]/[0303]: acc-top1=65.625000 acc-top5=85.218750 Batch [0099]/[0303]: acc-top1=63.843750 acc-top5=85.078125 Batch [0149]/[0303]: acc-top1=65.135417 acc-top5=85.864583 Batch [0199]/[0303]: acc-top1=67.796875 acc-top5=87.062500 Batch [0249]/[0303]: acc-top1=67.418750 acc-top5=86.575000 Batch [0299]/[0303]: acc-top1=66.812500 acc-top5=86.463542 [Epoch 064] training: accuracy=91.692438 loss=0.304090 [Epoch 064] speed: 93 samples/sec time cost: 2793.282667 [Epoch 064] validation: acc-top1=66.754332 acc-top5=86.453177 loss=2.259903 Epoch[065] Batch [0049]/[3760] Speed: 63.877900 samples/sec accuracy=92.687500 loss=0.267681 lr=0.002727 Epoch[065] Batch [0099]/[3760] Speed: 95.214440 samples/sec accuracy=92.875000 loss=0.263968 lr=0.002725 Epoch[065] Batch [0149]/[3760] Speed: 91.999788 samples/sec accuracy=93.041667 loss=0.260095 lr=0.002723 Epoch[065] Batch [0199]/[3760] Speed: 95.021229 samples/sec accuracy=93.109375 loss=0.258156 lr=0.002721 Epoch[065] Batch [0249]/[3760] Speed: 92.503926 samples/sec accuracy=93.006250 loss=0.261008 lr=0.002719 Epoch[065] Batch [0299]/[3760] Speed: 94.954725 samples/sec accuracy=93.005208 loss=0.262284 lr=0.002717 Epoch[065] Batch [0349]/[3760] Speed: 92.951672 samples/sec accuracy=92.924107 loss=0.265571 lr=0.002715 Epoch[065] Batch 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accuracy=92.328409 loss=0.281786 lr=0.002627 Epoch[065] Batch [2799]/[3760] Speed: 93.188291 samples/sec accuracy=92.318080 loss=0.282004 lr=0.002625 Epoch[065] Batch [2849]/[3760] Speed: 93.741540 samples/sec accuracy=92.302632 loss=0.282470 lr=0.002623 Epoch[065] Batch [2899]/[3760] Speed: 93.364685 samples/sec accuracy=92.298491 loss=0.282276 lr=0.002621 Epoch[065] Batch [2949]/[3760] Speed: 93.633196 samples/sec accuracy=92.296610 loss=0.282208 lr=0.002619 Epoch[065] Batch [2999]/[3760] Speed: 93.159473 samples/sec accuracy=92.291667 loss=0.282408 lr=0.002618 Epoch[065] Batch [3049]/[3760] Speed: 94.112146 samples/sec accuracy=92.295594 loss=0.282347 lr=0.002616 Epoch[065] Batch [3099]/[3760] Speed: 92.834120 samples/sec accuracy=92.289315 loss=0.282539 lr=0.002614 Epoch[065] Batch [3149]/[3760] Speed: 94.375638 samples/sec accuracy=92.294147 loss=0.282604 lr=0.002612 Epoch[065] Batch [3199]/[3760] Speed: 93.679885 samples/sec accuracy=92.280762 loss=0.283119 lr=0.002610 Epoch[065] 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accuracy=92.201436 loss=0.286152 lr=0.002592 Epoch[065] Batch [3749]/[3760] Speed: 106.494594 samples/sec accuracy=92.184167 loss=0.286604 lr=0.002590 Batch [0049]/[0303]: acc-top1=64.500000 acc-top5=84.343750 Batch [0099]/[0303]: acc-top1=62.859375 acc-top5=84.562500 Batch [0149]/[0303]: acc-top1=65.041667 acc-top5=85.572917 Batch [0199]/[0303]: acc-top1=67.726562 acc-top5=86.796875 Batch [0249]/[0303]: acc-top1=67.043750 acc-top5=86.200000 Batch [0299]/[0303]: acc-top1=66.588542 acc-top5=86.187500 [Epoch 065] training: accuracy=92.184176 loss=0.286655 [Epoch 065] speed: 93 samples/sec time cost: 2796.161868 [Epoch 065] validation: acc-top1=66.537748 acc-top5=86.159241 loss=2.330758 Epoch[066] Batch [0049]/[3759] Speed: 64.976302 samples/sec accuracy=92.593750 loss=0.277668 lr=0.002588 Epoch[066] Batch [0099]/[3759] Speed: 92.380911 samples/sec accuracy=92.328125 loss=0.274333 lr=0.002586 Epoch[066] Batch [0149]/[3759] Speed: 95.103862 samples/sec accuracy=92.500000 loss=0.262427 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lr=0.002515 Epoch[066] Batch [2099]/[3759] Speed: 93.935850 samples/sec accuracy=92.561012 loss=0.272136 lr=0.002513 Epoch[066] Batch [2149]/[3759] Speed: 94.086003 samples/sec accuracy=92.550145 loss=0.272583 lr=0.002511 Epoch[066] Batch [2199]/[3759] Speed: 93.108339 samples/sec accuracy=92.536932 loss=0.272840 lr=0.002509 Epoch[066] Batch [2249]/[3759] Speed: 94.617040 samples/sec accuracy=92.536111 loss=0.272802 lr=0.002508 Epoch[066] Batch [2299]/[3759] Speed: 93.352351 samples/sec accuracy=92.544158 loss=0.272748 lr=0.002506 Epoch[066] Batch [2349]/[3759] Speed: 94.572887 samples/sec accuracy=92.527926 loss=0.273182 lr=0.002504 Epoch[066] Batch [2399]/[3759] Speed: 94.003528 samples/sec accuracy=92.535156 loss=0.273278 lr=0.002502 Epoch[066] Batch [2449]/[3759] Speed: 94.128668 samples/sec accuracy=92.525510 loss=0.273473 lr=0.002500 Epoch[066] Batch [2499]/[3759] Speed: 93.711144 samples/sec accuracy=92.539375 loss=0.273363 lr=0.002499 Epoch[066] Batch [2549]/[3759] Speed: 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lr=0.002481 Epoch[066] Batch [3049]/[3759] Speed: 94.195916 samples/sec accuracy=92.554303 loss=0.272417 lr=0.002479 Epoch[066] Batch [3099]/[3759] Speed: 93.488318 samples/sec accuracy=92.557460 loss=0.272228 lr=0.002477 Epoch[066] Batch [3149]/[3759] Speed: 93.128412 samples/sec accuracy=92.553571 loss=0.272287 lr=0.002475 Epoch[066] Batch [3199]/[3759] Speed: 94.377416 samples/sec accuracy=92.548828 loss=0.272289 lr=0.002473 Epoch[066] Batch [3249]/[3759] Speed: 93.779201 samples/sec accuracy=92.553365 loss=0.271991 lr=0.002472 Epoch[066] Batch [3299]/[3759] Speed: 93.538655 samples/sec accuracy=92.554924 loss=0.271889 lr=0.002470 Epoch[066] Batch [3349]/[3759] Speed: 93.979193 samples/sec accuracy=92.548041 loss=0.272299 lr=0.002468 Epoch[066] Batch [3399]/[3759] Speed: 92.774300 samples/sec accuracy=92.549632 loss=0.272478 lr=0.002466 Epoch[066] Batch [3449]/[3759] Speed: 93.301761 samples/sec accuracy=92.533967 loss=0.272992 lr=0.002464 Epoch[066] Batch [3499]/[3759] Speed: 93.177694 samples/sec accuracy=92.530357 loss=0.273114 lr=0.002463 Epoch[066] Batch [3549]/[3759] Speed: 93.906955 samples/sec accuracy=92.534771 loss=0.272969 lr=0.002461 Epoch[066] Batch [3599]/[3759] Speed: 93.316190 samples/sec accuracy=92.532118 loss=0.273032 lr=0.002459 Epoch[066] Batch [3649]/[3759] Speed: 94.386291 samples/sec accuracy=92.531678 loss=0.273196 lr=0.002457 Epoch[066] Batch [3699]/[3759] Speed: 93.882622 samples/sec accuracy=92.525338 loss=0.273393 lr=0.002455 Epoch[066] Batch [3749]/[3759] Speed: 107.377697 samples/sec accuracy=92.529583 loss=0.273430 lr=0.002454 Batch [0049]/[0303]: acc-top1=66.343750 acc-top5=85.375000 Batch [0099]/[0303]: acc-top1=63.687500 acc-top5=84.906250 Batch [0149]/[0303]: acc-top1=64.885417 acc-top5=85.510417 Batch [0199]/[0303]: acc-top1=67.328125 acc-top5=86.703125 Batch [0249]/[0303]: acc-top1=67.050000 acc-top5=86.262500 Batch [0299]/[0303]: acc-top1=66.718750 acc-top5=86.171875 [Epoch 066] training: accuracy=92.527933 loss=0.273498 [Epoch 066] speed: 93 samples/sec time cost: 2796.134100 [Epoch 066] validation: acc-top1=66.702764 acc-top5=86.185025 loss=2.354131 Epoch[067] Batch [0049]/[3760] Speed: 64.473964 samples/sec accuracy=94.187500 loss=0.229456 lr=0.002451 Epoch[067] Batch [0099]/[3760] Speed: 92.785509 samples/sec accuracy=93.828125 loss=0.242020 lr=0.002450 Epoch[067] Batch [0149]/[3760] Speed: 95.003222 samples/sec accuracy=93.947917 loss=0.240544 lr=0.002448 Epoch[067] Batch [0199]/[3760] Speed: 92.028477 samples/sec accuracy=93.726562 loss=0.242553 lr=0.002446 Epoch[067] Batch [0249]/[3760] Speed: 95.548394 samples/sec accuracy=93.762500 loss=0.240004 lr=0.002444 Epoch[067] Batch [0299]/[3760] Speed: 92.277387 samples/sec accuracy=93.729167 loss=0.239894 lr=0.002442 Epoch[067] Batch [0349]/[3760] Speed: 95.176894 samples/sec accuracy=93.812500 loss=0.236681 lr=0.002441 Epoch[067] Batch [0399]/[3760] Speed: 92.784265 samples/sec accuracy=93.769531 loss=0.235802 lr=0.002439 Epoch[067] 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accuracy=93.616319 loss=0.240839 lr=0.002421 Epoch[067] Batch [0949]/[3760] Speed: 94.732464 samples/sec accuracy=93.592105 loss=0.241251 lr=0.002419 Epoch[067] Batch [0999]/[3760] Speed: 93.155955 samples/sec accuracy=93.564063 loss=0.241931 lr=0.002417 Epoch[067] Batch [1049]/[3760] Speed: 94.307690 samples/sec accuracy=93.541667 loss=0.243183 lr=0.002416 Epoch[067] Batch [1099]/[3760] Speed: 92.670000 samples/sec accuracy=93.535511 loss=0.243212 lr=0.002414 Epoch[067] Batch [1149]/[3760] Speed: 94.248348 samples/sec accuracy=93.512228 loss=0.243189 lr=0.002412 Epoch[067] Batch [1199]/[3760] Speed: 93.011954 samples/sec accuracy=93.484375 loss=0.243804 lr=0.002410 Epoch[067] Batch [1249]/[3760] Speed: 95.497985 samples/sec accuracy=93.475000 loss=0.244443 lr=0.002408 Epoch[067] Batch [1299]/[3760] Speed: 92.462441 samples/sec accuracy=93.444712 loss=0.245074 lr=0.002407 Epoch[067] Batch [1349]/[3760] Speed: 94.771995 samples/sec accuracy=93.403935 loss=0.246353 lr=0.002405 Epoch[067] 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accuracy=93.153333 loss=0.255528 lr=0.002320 Batch [0049]/[0303]: acc-top1=66.312500 acc-top5=85.187500 Batch [0099]/[0303]: acc-top1=63.828125 acc-top5=84.625000 Batch [0149]/[0303]: acc-top1=64.593750 acc-top5=85.354167 Batch [0199]/[0303]: acc-top1=67.382812 acc-top5=86.710938 Batch [0249]/[0303]: acc-top1=66.993750 acc-top5=86.300000 Batch [0299]/[0303]: acc-top1=66.531250 acc-top5=86.255208 [Epoch 067] training: accuracy=93.151180 loss=0.255591 [Epoch 067] speed: 93 samples/sec time cost: 2794.378349 [Epoch 067] validation: acc-top1=66.475866 acc-top5=86.257219 loss=2.392186 Epoch[068] Batch [0049]/[3760] Speed: 65.055582 samples/sec accuracy=94.218750 loss=0.209910 lr=0.002318 Epoch[068] Batch [0099]/[3760] Speed: 94.137532 samples/sec accuracy=94.031250 loss=0.222452 lr=0.002316 Epoch[068] Batch [0149]/[3760] Speed: 93.958687 samples/sec accuracy=94.125000 loss=0.219048 lr=0.002314 Epoch[068] Batch [0199]/[3760] Speed: 93.486087 samples/sec accuracy=94.242188 loss=0.218766 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lr=0.002213 Epoch[068] Batch [3099]/[3760] Speed: 93.347407 samples/sec accuracy=93.525706 loss=0.241262 lr=0.002211 Epoch[068] Batch [3149]/[3760] Speed: 93.433313 samples/sec accuracy=93.511905 loss=0.241517 lr=0.002209 Epoch[068] Batch [3199]/[3760] Speed: 93.565874 samples/sec accuracy=93.492188 loss=0.241946 lr=0.002207 Epoch[068] Batch [3249]/[3760] Speed: 94.500063 samples/sec accuracy=93.500000 loss=0.241760 lr=0.002206 Epoch[068] Batch [3299]/[3760] Speed: 93.624940 samples/sec accuracy=93.492898 loss=0.241854 lr=0.002204 Epoch[068] Batch [3349]/[3760] Speed: 94.888466 samples/sec accuracy=93.478545 loss=0.242213 lr=0.002202 Epoch[068] Batch [3399]/[3760] Speed: 92.753932 samples/sec accuracy=93.479320 loss=0.242320 lr=0.002200 Epoch[068] Batch [3449]/[3760] Speed: 93.431567 samples/sec accuracy=93.469656 loss=0.242502 lr=0.002199 Epoch[068] Batch [3499]/[3760] Speed: 92.746457 samples/sec accuracy=93.462054 loss=0.242823 lr=0.002197 Epoch[068] Batch [3549]/[3760] Speed: 94.821973 samples/sec accuracy=93.466989 loss=0.242668 lr=0.002195 Epoch[068] Batch [3599]/[3760] Speed: 92.666586 samples/sec accuracy=93.467014 loss=0.242686 lr=0.002194 Epoch[068] Batch [3649]/[3760] Speed: 94.162930 samples/sec accuracy=93.464041 loss=0.242786 lr=0.002192 Epoch[068] Batch [3699]/[3760] Speed: 93.108430 samples/sec accuracy=93.452703 loss=0.243181 lr=0.002190 Epoch[068] Batch [3749]/[3760] Speed: 107.754848 samples/sec accuracy=93.450833 loss=0.243233 lr=0.002188 Batch [0049]/[0303]: acc-top1=64.500000 acc-top5=84.562500 Batch [0099]/[0303]: acc-top1=63.406250 acc-top5=84.640625 Batch [0149]/[0303]: acc-top1=64.760417 acc-top5=85.562500 Batch [0199]/[0303]: acc-top1=67.679688 acc-top5=86.757812 Batch [0249]/[0303]: acc-top1=67.237500 acc-top5=86.381250 Batch [0299]/[0303]: acc-top1=66.776042 acc-top5=86.442708 [Epoch 068] training: accuracy=93.450382 loss=0.243253 [Epoch 068] speed: 93 samples/sec time cost: 2793.361928 [Epoch 068] validation: acc-top1=66.759488 acc-top5=86.427393 loss=2.366207 Epoch[069] Batch [0049]/[3759] Speed: 64.190572 samples/sec accuracy=94.718750 loss=0.215513 lr=0.002186 Epoch[069] Batch [0099]/[3759] Speed: 94.804844 samples/sec accuracy=94.593750 loss=0.217260 lr=0.002185 Epoch[069] Batch [0149]/[3759] Speed: 93.393426 samples/sec accuracy=94.375000 loss=0.220920 lr=0.002183 Epoch[069] Batch [0199]/[3759] Speed: 93.969156 samples/sec accuracy=94.468750 loss=0.215748 lr=0.002181 Epoch[069] Batch [0249]/[3759] Speed: 93.653907 samples/sec accuracy=94.443750 loss=0.213509 lr=0.002179 Epoch[069] Batch [0299]/[3759] Speed: 94.431584 samples/sec accuracy=94.401042 loss=0.213176 lr=0.002178 Epoch[069] Batch [0349]/[3759] Speed: 92.674730 samples/sec accuracy=94.343750 loss=0.215822 lr=0.002176 Epoch[069] Batch [0399]/[3759] Speed: 94.681919 samples/sec accuracy=94.324219 loss=0.217643 lr=0.002174 Epoch[069] Batch [0449]/[3759] Speed: 92.805265 samples/sec accuracy=94.385417 loss=0.215486 lr=0.002172 Epoch[069] Batch 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[0099]/[0303]: acc-top1=63.515625 acc-top5=84.656250 Batch [0149]/[0303]: acc-top1=64.937500 acc-top5=85.458333 Batch [0199]/[0303]: acc-top1=67.875000 acc-top5=86.921875 Batch [0249]/[0303]: acc-top1=67.425000 acc-top5=86.506250 Batch [0299]/[0303]: acc-top1=67.072917 acc-top5=86.562500 [Epoch 069] training: accuracy=94.045125 loss=0.223641 [Epoch 069] speed: 93 samples/sec time cost: 2792.010112 [Epoch 069] validation: acc-top1=67.022483 acc-top5=86.561469 loss=2.340609 Epoch[070] Batch [0049]/[3760] Speed: 64.923073 samples/sec accuracy=94.156250 loss=0.219545 lr=0.002058 Epoch[070] Batch [0099]/[3760] Speed: 93.800829 samples/sec accuracy=94.421875 loss=0.205879 lr=0.002056 Epoch[070] Batch [0149]/[3760] Speed: 94.320705 samples/sec accuracy=94.614583 loss=0.202238 lr=0.002054 Epoch[070] Batch [0199]/[3760] Speed: 93.647701 samples/sec accuracy=94.601562 loss=0.204467 lr=0.002053 Epoch[070] Batch [0249]/[3760] Speed: 93.930011 samples/sec accuracy=94.712500 loss=0.201504 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lr=0.001956 Epoch[070] Batch [3149]/[3760] Speed: 94.353774 samples/sec accuracy=94.452877 loss=0.210991 lr=0.001954 Epoch[070] Batch [3199]/[3760] Speed: 92.994377 samples/sec accuracy=94.446777 loss=0.211109 lr=0.001952 Epoch[070] Batch [3249]/[3760] Speed: 94.599470 samples/sec accuracy=94.449519 loss=0.210961 lr=0.001951 Epoch[070] Batch [3299]/[3760] Speed: 92.480637 samples/sec accuracy=94.440814 loss=0.211219 lr=0.001949 Epoch[070] Batch [3349]/[3760] Speed: 95.088042 samples/sec accuracy=94.435168 loss=0.211459 lr=0.001947 Epoch[070] Batch [3399]/[3760] Speed: 94.055090 samples/sec accuracy=94.438419 loss=0.211474 lr=0.001946 Epoch[070] Batch [3449]/[3760] Speed: 94.239419 samples/sec accuracy=94.428442 loss=0.211680 lr=0.001944 Epoch[070] Batch [3499]/[3760] Speed: 93.418356 samples/sec accuracy=94.425893 loss=0.211763 lr=0.001943 Epoch[070] Batch [3549]/[3760] Speed: 93.476938 samples/sec accuracy=94.430018 loss=0.211800 lr=0.001941 Epoch[070] Batch [3599]/[3760] Speed: 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accuracy=94.906250 loss=0.190189 lr=0.001932 Epoch[071] Batch [0099]/[3760] Speed: 93.553831 samples/sec accuracy=95.015625 loss=0.186787 lr=0.001931 Epoch[071] Batch [0149]/[3760] Speed: 94.167108 samples/sec accuracy=95.197917 loss=0.180988 lr=0.001929 Epoch[071] Batch [0199]/[3760] Speed: 93.586717 samples/sec accuracy=95.062500 loss=0.184591 lr=0.001927 Epoch[071] Batch [0249]/[3760] Speed: 94.350593 samples/sec accuracy=95.112500 loss=0.184572 lr=0.001926 Epoch[071] Batch [0299]/[3760] Speed: 93.661970 samples/sec accuracy=95.229167 loss=0.182960 lr=0.001924 Epoch[071] Batch [0349]/[3760] Speed: 93.573552 samples/sec accuracy=95.183036 loss=0.183633 lr=0.001922 Epoch[071] Batch [0399]/[3760] Speed: 94.039418 samples/sec accuracy=95.214844 loss=0.182343 lr=0.001921 Epoch[071] Batch [0449]/[3760] Speed: 94.194080 samples/sec accuracy=95.180556 loss=0.185180 lr=0.001919 Epoch[071] Batch [0499]/[3760] Speed: 93.163491 samples/sec accuracy=95.146875 loss=0.185918 lr=0.001917 Epoch[071] 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acc-top5=85.458333 Batch [0199]/[0303]: acc-top1=68.039062 acc-top5=86.765625 Batch [0249]/[0303]: acc-top1=67.331250 acc-top5=86.356250 Batch [0299]/[0303]: acc-top1=66.854167 acc-top5=86.348958 [Epoch 071] training: accuracy=94.873670 loss=0.195423 [Epoch 071] speed: 93 samples/sec time cost: 2795.574418 [Epoch 071] validation: acc-top1=66.826526 acc-top5=86.344884 loss=2.404686 Epoch[072] Batch [0049]/[3759] Speed: 64.911328 samples/sec accuracy=95.968750 loss=0.157132 lr=0.001810 Epoch[072] Batch [0099]/[3759] Speed: 93.290449 samples/sec accuracy=95.890625 loss=0.162414 lr=0.001808 Epoch[072] Batch [0149]/[3759] Speed: 94.699593 samples/sec accuracy=95.864583 loss=0.161861 lr=0.001807 Epoch[072] Batch [0199]/[3759] Speed: 93.402869 samples/sec accuracy=95.726562 loss=0.166378 lr=0.001805 Epoch[072] Batch [0249]/[3759] Speed: 94.593171 samples/sec accuracy=95.662500 loss=0.168013 lr=0.001803 Epoch[072] Batch [0299]/[3759] Speed: 92.572713 samples/sec accuracy=95.619792 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accuracy=95.442500 loss=0.175750 lr=0.001771 Epoch[072] Batch [1299]/[3759] Speed: 95.326772 samples/sec accuracy=95.448317 loss=0.175475 lr=0.001770 Epoch[072] Batch [1349]/[3759] Speed: 93.599226 samples/sec accuracy=95.422454 loss=0.176200 lr=0.001768 Epoch[072] Batch [1399]/[3759] Speed: 93.243646 samples/sec accuracy=95.420759 loss=0.176124 lr=0.001767 Epoch[072] Batch [1449]/[3759] Speed: 93.812431 samples/sec accuracy=95.422414 loss=0.176030 lr=0.001765 Epoch[072] Batch [1499]/[3759] Speed: 93.689151 samples/sec accuracy=95.419792 loss=0.176095 lr=0.001763 Epoch[072] Batch [1549]/[3759] Speed: 92.989564 samples/sec accuracy=95.420363 loss=0.176153 lr=0.001762 Epoch[072] Batch [1599]/[3759] Speed: 93.669736 samples/sec accuracy=95.396484 loss=0.176972 lr=0.001760 Epoch[072] Batch [1649]/[3759] Speed: 93.523247 samples/sec accuracy=95.387311 loss=0.176943 lr=0.001759 Epoch[072] Batch [1699]/[3759] Speed: 92.973030 samples/sec accuracy=95.393382 loss=0.176836 lr=0.001757 Epoch[072] 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accuracy=95.350852 loss=0.178899 lr=0.001741 Epoch[072] Batch [2249]/[3759] Speed: 93.281386 samples/sec accuracy=95.347917 loss=0.179080 lr=0.001739 Epoch[072] Batch [2299]/[3759] Speed: 94.691315 samples/sec accuracy=95.338995 loss=0.179321 lr=0.001738 Epoch[072] Batch [2349]/[3759] Speed: 92.702123 samples/sec accuracy=95.322473 loss=0.179922 lr=0.001736 Epoch[072] Batch [2399]/[3759] Speed: 93.739586 samples/sec accuracy=95.319010 loss=0.180070 lr=0.001735 Epoch[072] Batch [2449]/[3759] Speed: 93.450212 samples/sec accuracy=95.324617 loss=0.180032 lr=0.001733 Epoch[072] Batch [2499]/[3759] Speed: 94.197008 samples/sec accuracy=95.322500 loss=0.180151 lr=0.001732 Epoch[072] Batch [2549]/[3759] Speed: 93.517422 samples/sec accuracy=95.318015 loss=0.180284 lr=0.001730 Epoch[072] Batch [2599]/[3759] Speed: 94.676282 samples/sec accuracy=95.332332 loss=0.179989 lr=0.001728 Epoch[072] Batch [2649]/[3759] Speed: 92.120771 samples/sec accuracy=95.327241 loss=0.180083 lr=0.001727 Epoch[072] 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accuracy=95.302083 loss=0.181034 lr=0.001711 Epoch[072] Batch [3199]/[3759] Speed: 93.296788 samples/sec accuracy=95.305664 loss=0.180990 lr=0.001709 Epoch[072] Batch [3249]/[3759] Speed: 94.432756 samples/sec accuracy=95.310577 loss=0.180863 lr=0.001708 Epoch[072] Batch [3299]/[3759] Speed: 93.475432 samples/sec accuracy=95.312500 loss=0.180767 lr=0.001706 Epoch[072] Batch [3349]/[3759] Speed: 94.024522 samples/sec accuracy=95.312034 loss=0.180765 lr=0.001705 Epoch[072] Batch [3399]/[3759] Speed: 93.467777 samples/sec accuracy=95.315717 loss=0.180808 lr=0.001703 Epoch[072] Batch [3449]/[3759] Speed: 94.345869 samples/sec accuracy=95.316576 loss=0.180777 lr=0.001702 Epoch[072] Batch [3499]/[3759] Speed: 93.479587 samples/sec accuracy=95.316518 loss=0.180674 lr=0.001700 Epoch[072] Batch [3549]/[3759] Speed: 94.288283 samples/sec accuracy=95.306778 loss=0.180918 lr=0.001698 Epoch[072] Batch [3599]/[3759] Speed: 92.604492 samples/sec accuracy=95.299913 loss=0.181118 lr=0.001697 Epoch[072] Batch [3649]/[3759] Speed: 94.911195 samples/sec accuracy=95.294521 loss=0.181387 lr=0.001695 Epoch[072] Batch [3699]/[3759] Speed: 93.553675 samples/sec accuracy=95.294341 loss=0.181625 lr=0.001694 Epoch[072] Batch [3749]/[3759] Speed: 106.081015 samples/sec accuracy=95.292083 loss=0.181878 lr=0.001692 Batch [0049]/[0303]: acc-top1=66.062500 acc-top5=85.250000 Batch [0099]/[0303]: acc-top1=64.328125 acc-top5=84.718750 Batch [0149]/[0303]: acc-top1=65.114583 acc-top5=85.302083 Batch [0199]/[0303]: acc-top1=67.882812 acc-top5=86.546875 Batch [0249]/[0303]: acc-top1=67.581250 acc-top5=86.168750 Batch [0299]/[0303]: acc-top1=67.281250 acc-top5=86.223958 [Epoch 072] training: accuracy=95.291301 loss=0.181886 [Epoch 072] speed: 93 samples/sec time cost: 2793.505815 [Epoch 072] validation: acc-top1=67.223597 acc-top5=86.221122 loss=2.398224 Epoch[073] Batch [0049]/[3760] Speed: 63.990003 samples/sec accuracy=95.750000 loss=0.167799 lr=0.001690 Epoch[073] Batch [0099]/[3760] Speed: 94.869490 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lr=0.001587 Epoch[073] Batch [3449]/[3760] Speed: 94.251288 samples/sec accuracy=95.648551 loss=0.170890 lr=0.001585 Epoch[073] Batch [3499]/[3760] Speed: 92.198534 samples/sec accuracy=95.645982 loss=0.171016 lr=0.001584 Epoch[073] Batch [3549]/[3760] Speed: 94.927629 samples/sec accuracy=95.638644 loss=0.171230 lr=0.001582 Epoch[073] Batch [3599]/[3760] Speed: 94.549841 samples/sec accuracy=95.635417 loss=0.171274 lr=0.001581 Epoch[073] Batch [3649]/[3760] Speed: 93.319141 samples/sec accuracy=95.630993 loss=0.171357 lr=0.001579 Epoch[073] Batch [3699]/[3760] Speed: 94.178309 samples/sec accuracy=95.627111 loss=0.171477 lr=0.001578 Epoch[073] Batch [3749]/[3760] Speed: 105.678137 samples/sec accuracy=95.621667 loss=0.171633 lr=0.001576 Batch [0049]/[0303]: acc-top1=66.156250 acc-top5=84.937500 Batch [0099]/[0303]: acc-top1=64.578125 acc-top5=84.593750 Batch [0149]/[0303]: acc-top1=65.750000 acc-top5=85.656250 Batch [0199]/[0303]: acc-top1=68.335938 acc-top5=87.031250 Batch [0249]/[0303]: acc-top1=67.962500 acc-top5=86.587500 Batch [0299]/[0303]: acc-top1=67.494792 acc-top5=86.557292 [Epoch 073] training: accuracy=95.618767 loss=0.171661 [Epoch 073] speed: 93 samples/sec time cost: 2794.337911 [Epoch 073] validation: acc-top1=67.435025 acc-top5=86.525371 loss=2.394106 Epoch[074] Batch [0049]/[3760] Speed: 65.039000 samples/sec accuracy=95.625000 loss=0.160863 lr=0.001574 Epoch[074] Batch [0099]/[3760] Speed: 93.230306 samples/sec accuracy=95.671875 loss=0.164834 lr=0.001573 Epoch[074] Batch [0149]/[3760] Speed: 94.310664 samples/sec accuracy=95.895833 loss=0.161153 lr=0.001571 Epoch[074] Batch [0199]/[3760] Speed: 93.400720 samples/sec accuracy=95.882812 loss=0.158069 lr=0.001570 Epoch[074] Batch [0249]/[3760] Speed: 94.401377 samples/sec accuracy=95.906250 loss=0.158728 lr=0.001568 Epoch[074] Batch [0299]/[3760] Speed: 93.652511 samples/sec accuracy=95.942708 loss=0.158268 lr=0.001567 Epoch[074] Batch [0349]/[3760] Speed: 93.880070 samples/sec accuracy=95.848214 loss=0.160513 lr=0.001565 Epoch[074] Batch [0399]/[3760] Speed: 92.702725 samples/sec accuracy=95.878906 loss=0.160316 lr=0.001564 Epoch[074] Batch [0449]/[3760] Speed: 94.874972 samples/sec accuracy=95.875000 loss=0.159609 lr=0.001562 Epoch[074] Batch [0499]/[3760] Speed: 92.731348 samples/sec accuracy=95.959375 loss=0.157642 lr=0.001561 Epoch[074] Batch [0549]/[3760] Speed: 94.325306 samples/sec accuracy=95.980114 loss=0.157556 lr=0.001559 Epoch[074] Batch [0599]/[3760] Speed: 91.861733 samples/sec accuracy=96.031250 loss=0.156719 lr=0.001558 Epoch[074] Batch [0649]/[3760] Speed: 95.356956 samples/sec accuracy=96.036058 loss=0.156428 lr=0.001556 Epoch[074] Batch [0699]/[3760] Speed: 93.961520 samples/sec accuracy=96.046875 loss=0.156066 lr=0.001555 Epoch[074] Batch [0749]/[3760] Speed: 93.613721 samples/sec accuracy=96.022917 loss=0.156957 lr=0.001553 Epoch[074] Batch [0799]/[3760] Speed: 93.624676 samples/sec accuracy=95.994141 loss=0.157262 lr=0.001551 Epoch[074] 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accuracy=96.000000 loss=0.156379 lr=0.001536 Epoch[074] Batch [1349]/[3760] Speed: 94.090478 samples/sec accuracy=95.971065 loss=0.157031 lr=0.001535 Epoch[074] Batch [1399]/[3760] Speed: 94.190107 samples/sec accuracy=95.983259 loss=0.157142 lr=0.001533 Epoch[074] Batch [1449]/[3760] Speed: 93.985408 samples/sec accuracy=95.981681 loss=0.157144 lr=0.001532 Epoch[074] Batch [1499]/[3760] Speed: 93.966326 samples/sec accuracy=95.982292 loss=0.157165 lr=0.001530 Epoch[074] Batch [1549]/[3760] Speed: 93.789106 samples/sec accuracy=95.989919 loss=0.156835 lr=0.001529 Epoch[074] Batch [1599]/[3760] Speed: 93.051753 samples/sec accuracy=95.990234 loss=0.156900 lr=0.001527 Epoch[074] Batch [1649]/[3760] Speed: 93.691980 samples/sec accuracy=95.974432 loss=0.157618 lr=0.001526 Epoch[074] Batch [1699]/[3760] Speed: 93.175882 samples/sec accuracy=95.975184 loss=0.157380 lr=0.001524 Epoch[074] Batch [1749]/[3760] Speed: 94.025395 samples/sec accuracy=95.976786 loss=0.157325 lr=0.001523 Epoch[074] 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accuracy=95.963889 loss=0.157825 lr=0.001508 Epoch[074] Batch [2299]/[3760] Speed: 93.712483 samples/sec accuracy=95.952446 loss=0.158106 lr=0.001506 Epoch[074] Batch [2349]/[3760] Speed: 92.499563 samples/sec accuracy=95.942154 loss=0.158420 lr=0.001505 Epoch[074] Batch [2399]/[3760] Speed: 94.259199 samples/sec accuracy=95.940755 loss=0.158523 lr=0.001503 Epoch[074] Batch [2449]/[3760] Speed: 94.035186 samples/sec accuracy=95.938776 loss=0.158632 lr=0.001502 Epoch[074] Batch [2499]/[3760] Speed: 93.415948 samples/sec accuracy=95.934375 loss=0.158385 lr=0.001500 Epoch[074] Batch [2549]/[3760] Speed: 94.608861 samples/sec accuracy=95.928922 loss=0.158469 lr=0.001499 Epoch[074] Batch [2599]/[3760] Speed: 93.143257 samples/sec accuracy=95.920072 loss=0.158672 lr=0.001497 Epoch[074] Batch [2649]/[3760] Speed: 94.217243 samples/sec accuracy=95.910377 loss=0.158837 lr=0.001496 Epoch[074] Batch [2699]/[3760] Speed: 93.216459 samples/sec accuracy=95.917245 loss=0.158736 lr=0.001494 Epoch[074] 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accuracy=95.885742 loss=0.159762 lr=0.001480 Epoch[074] Batch [3249]/[3760] Speed: 93.655726 samples/sec accuracy=95.892788 loss=0.159716 lr=0.001478 Epoch[074] Batch [3299]/[3760] Speed: 93.625742 samples/sec accuracy=95.881629 loss=0.159950 lr=0.001477 Epoch[074] Batch [3349]/[3760] Speed: 93.330340 samples/sec accuracy=95.875933 loss=0.160307 lr=0.001475 Epoch[074] Batch [3399]/[3760] Speed: 94.377094 samples/sec accuracy=95.871783 loss=0.160389 lr=0.001474 Epoch[074] Batch [3449]/[3760] Speed: 92.914127 samples/sec accuracy=95.873641 loss=0.160395 lr=0.001472 Epoch[074] Batch [3499]/[3760] Speed: 94.536006 samples/sec accuracy=95.873214 loss=0.160370 lr=0.001471 Epoch[074] Batch [3549]/[3760] Speed: 92.370825 samples/sec accuracy=95.868838 loss=0.160473 lr=0.001469 Epoch[074] Batch [3599]/[3760] Speed: 94.724426 samples/sec accuracy=95.866753 loss=0.160624 lr=0.001468 Epoch[074] Batch [3649]/[3760] Speed: 93.989572 samples/sec accuracy=95.866010 loss=0.160735 lr=0.001466 Epoch[074] Batch [3699]/[3760] Speed: 93.646714 samples/sec accuracy=95.871199 loss=0.160718 lr=0.001465 Epoch[074] Batch [3749]/[3760] Speed: 105.403927 samples/sec accuracy=95.877083 loss=0.160708 lr=0.001463 Batch [0049]/[0303]: acc-top1=67.031250 acc-top5=85.125000 Batch [0099]/[0303]: acc-top1=65.359375 acc-top5=84.796875 Batch [0149]/[0303]: acc-top1=66.447917 acc-top5=85.750000 Batch [0199]/[0303]: acc-top1=68.671875 acc-top5=86.992188 Batch [0249]/[0303]: acc-top1=68.175000 acc-top5=86.537500 Batch [0299]/[0303]: acc-top1=67.656250 acc-top5=86.484375 [Epoch 074] training: accuracy=95.879322 loss=0.160674 [Epoch 074] speed: 93 samples/sec time cost: 2794.405334 [Epoch 074] validation: acc-top1=67.605198 acc-top5=86.458333 loss=2.354922 Epoch[075] Batch [0049]/[3759] Speed: 65.144499 samples/sec accuracy=96.562500 loss=0.138315 lr=0.001462 Epoch[075] Batch [0099]/[3759] Speed: 94.812032 samples/sec accuracy=96.859375 loss=0.132626 lr=0.001460 Epoch[075] Batch [0149]/[3759] Speed: 93.423540 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lr=0.001418 Epoch[075] Batch [1599]/[3759] Speed: 94.759294 samples/sec accuracy=96.382812 loss=0.144988 lr=0.001416 Epoch[075] Batch [1649]/[3759] Speed: 94.070380 samples/sec accuracy=96.392992 loss=0.144858 lr=0.001415 Epoch[075] Batch [1699]/[3759] Speed: 92.910638 samples/sec accuracy=96.394301 loss=0.144618 lr=0.001413 Epoch[075] Batch [1749]/[3759] Speed: 93.827612 samples/sec accuracy=96.400893 loss=0.144443 lr=0.001412 Epoch[075] Batch [1799]/[3759] Speed: 93.410126 samples/sec accuracy=96.408854 loss=0.144231 lr=0.001410 Epoch[075] Batch [1849]/[3759] Speed: 93.273780 samples/sec accuracy=96.393581 loss=0.144569 lr=0.001409 Epoch[075] Batch [1899]/[3759] Speed: 94.336587 samples/sec accuracy=96.398849 loss=0.144403 lr=0.001407 Epoch[075] Batch [1949]/[3759] Speed: 94.271896 samples/sec accuracy=96.391827 loss=0.144461 lr=0.001406 Epoch[075] Batch [1999]/[3759] Speed: 93.422740 samples/sec accuracy=96.403125 loss=0.144304 lr=0.001404 Epoch[075] Batch [2049]/[3759] Speed: 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lr=0.001390 Epoch[075] Batch [2549]/[3759] Speed: 92.946344 samples/sec accuracy=96.349265 loss=0.146079 lr=0.001388 Epoch[075] Batch [2599]/[3759] Speed: 93.824379 samples/sec accuracy=96.355769 loss=0.145957 lr=0.001387 Epoch[075] Batch [2649]/[3759] Speed: 92.306024 samples/sec accuracy=96.341981 loss=0.146183 lr=0.001386 Epoch[075] Batch [2699]/[3759] Speed: 95.090182 samples/sec accuracy=96.343750 loss=0.146175 lr=0.001384 Epoch[075] Batch [2749]/[3759] Speed: 94.841954 samples/sec accuracy=96.335227 loss=0.146314 lr=0.001383 Epoch[075] Batch [2799]/[3759] Speed: 93.085545 samples/sec accuracy=96.342634 loss=0.146200 lr=0.001381 Epoch[075] Batch [2849]/[3759] Speed: 93.700999 samples/sec accuracy=96.329496 loss=0.146638 lr=0.001380 Epoch[075] Batch [2899]/[3759] Speed: 93.730518 samples/sec accuracy=96.321121 loss=0.146824 lr=0.001378 Epoch[075] Batch [2949]/[3759] Speed: 93.485224 samples/sec accuracy=96.327331 loss=0.146621 lr=0.001377 Epoch[075] Batch [2999]/[3759] Speed: 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lr=0.001363 Epoch[075] Batch [3499]/[3759] Speed: 93.987192 samples/sec accuracy=96.276339 loss=0.147672 lr=0.001361 Epoch[075] Batch [3549]/[3759] Speed: 93.404091 samples/sec accuracy=96.283891 loss=0.147470 lr=0.001360 Epoch[075] Batch [3599]/[3759] Speed: 94.440711 samples/sec accuracy=96.283854 loss=0.147491 lr=0.001358 Epoch[075] Batch [3649]/[3759] Speed: 92.870927 samples/sec accuracy=96.284675 loss=0.147518 lr=0.001357 Epoch[075] Batch [3699]/[3759] Speed: 94.585875 samples/sec accuracy=96.283784 loss=0.147533 lr=0.001355 Epoch[075] Batch [3749]/[3759] Speed: 106.584076 samples/sec accuracy=96.288750 loss=0.147454 lr=0.001354 Batch [0049]/[0303]: acc-top1=66.125000 acc-top5=85.562500 Batch [0099]/[0303]: acc-top1=64.906250 acc-top5=85.171875 Batch [0149]/[0303]: acc-top1=65.656250 acc-top5=85.770833 Batch [0199]/[0303]: acc-top1=68.156250 acc-top5=87.070312 Batch [0249]/[0303]: acc-top1=67.700000 acc-top5=86.656250 Batch [0299]/[0303]: acc-top1=67.380208 acc-top5=86.614583 [Epoch 075] training: accuracy=96.290985 loss=0.147412 [Epoch 075] speed: 93 samples/sec time cost: 2793.465758 [Epoch 075] validation: acc-top1=67.331889 acc-top5=86.602723 loss=2.367637 Epoch[076] Batch [0049]/[3760] Speed: 64.954843 samples/sec accuracy=96.781250 loss=0.136488 lr=0.001352 Epoch[076] Batch [0099]/[3760] Speed: 94.529542 samples/sec accuracy=96.750000 loss=0.139728 lr=0.001351 Epoch[076] Batch [0149]/[3760] Speed: 93.424146 samples/sec accuracy=96.864583 loss=0.135291 lr=0.001349 Epoch[076] Batch [0199]/[3760] Speed: 94.148690 samples/sec accuracy=96.718750 loss=0.137255 lr=0.001348 Epoch[076] Batch [0249]/[3760] Speed: 93.180361 samples/sec accuracy=96.737500 loss=0.135712 lr=0.001347 Epoch[076] Batch [0299]/[3760] Speed: 93.115444 samples/sec accuracy=96.734375 loss=0.134958 lr=0.001345 Epoch[076] Batch [0349]/[3760] Speed: 93.163257 samples/sec accuracy=96.754464 loss=0.133377 lr=0.001344 Epoch[076] Batch [0399]/[3760] Speed: 94.240415 samples/sec accuracy=96.726562 loss=0.134080 lr=0.001342 Epoch[076] Batch [0449]/[3760] Speed: 92.822334 samples/sec accuracy=96.732639 loss=0.133173 lr=0.001341 Epoch[076] Batch [0499]/[3760] Speed: 95.169149 samples/sec accuracy=96.721875 loss=0.133438 lr=0.001339 Epoch[076] Batch [0549]/[3760] Speed: 93.826370 samples/sec accuracy=96.730114 loss=0.133357 lr=0.001338 Epoch[076] Batch [0599]/[3760] Speed: 93.641359 samples/sec accuracy=96.729167 loss=0.133567 lr=0.001337 Epoch[076] Batch [0649]/[3760] Speed: 94.923766 samples/sec accuracy=96.745192 loss=0.133591 lr=0.001335 Epoch[076] Batch [0699]/[3760] Speed: 93.713118 samples/sec accuracy=96.747768 loss=0.133310 lr=0.001334 Epoch[076] Batch [0749]/[3760] Speed: 94.095534 samples/sec accuracy=96.768750 loss=0.132405 lr=0.001332 Epoch[076] Batch [0799]/[3760] Speed: 93.561369 samples/sec accuracy=96.755859 loss=0.133265 lr=0.001331 Epoch[076] Batch [0849]/[3760] Speed: 93.962442 samples/sec accuracy=96.748162 loss=0.133728 lr=0.001330 Epoch[076] 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accuracy=96.712963 loss=0.133351 lr=0.001315 Epoch[076] Batch [1399]/[3760] Speed: 94.924654 samples/sec accuracy=96.691964 loss=0.133806 lr=0.001314 Epoch[076] Batch [1449]/[3760] Speed: 92.273644 samples/sec accuracy=96.701509 loss=0.133315 lr=0.001313 Epoch[076] Batch [1499]/[3760] Speed: 94.780124 samples/sec accuracy=96.682292 loss=0.133881 lr=0.001311 Epoch[076] Batch [1549]/[3760] Speed: 94.055206 samples/sec accuracy=96.678427 loss=0.134056 lr=0.001310 Epoch[076] Batch [1599]/[3760] Speed: 93.363956 samples/sec accuracy=96.678711 loss=0.134009 lr=0.001308 Epoch[076] Batch [1649]/[3760] Speed: 93.738193 samples/sec accuracy=96.667614 loss=0.134202 lr=0.001307 Epoch[076] Batch [1699]/[3760] Speed: 93.732953 samples/sec accuracy=96.652574 loss=0.134444 lr=0.001305 Epoch[076] Batch [1749]/[3760] Speed: 93.848564 samples/sec accuracy=96.663393 loss=0.134193 lr=0.001304 Epoch[076] Batch [1799]/[3760] Speed: 93.601481 samples/sec accuracy=96.665799 loss=0.134091 lr=0.001303 Epoch[076] Batch [1849]/[3760] Speed: 94.428637 samples/sec accuracy=96.684122 loss=0.133702 lr=0.001301 Epoch[076] Batch [1899]/[3760] Speed: 93.768455 samples/sec accuracy=96.695724 loss=0.133422 lr=0.001300 Epoch[076] Batch [1949]/[3760] Speed: 94.755729 samples/sec accuracy=96.681891 loss=0.133737 lr=0.001298 Epoch[076] Batch [1999]/[3760] Speed: 92.440931 samples/sec accuracy=96.678125 loss=0.133817 lr=0.001297 Epoch[076] Batch [2049]/[3760] Speed: 95.055309 samples/sec accuracy=96.690549 loss=0.133680 lr=0.001296 Epoch[076] Batch [2099]/[3760] Speed: 94.209764 samples/sec accuracy=96.682292 loss=0.133969 lr=0.001294 Epoch[076] Batch [2149]/[3760] Speed: 93.776278 samples/sec accuracy=96.683140 loss=0.134084 lr=0.001293 Epoch[076] Batch [2199]/[3760] Speed: 94.057877 samples/sec accuracy=96.676136 loss=0.134255 lr=0.001291 Epoch[076] Batch [2249]/[3760] Speed: 93.623666 samples/sec accuracy=96.667361 loss=0.134758 lr=0.001290 Epoch[076] Batch [2299]/[3760] Speed: 94.004874 samples/sec accuracy=96.662364 loss=0.134757 lr=0.001289 Epoch[076] Batch [2349]/[3760] Speed: 93.518118 samples/sec accuracy=96.655585 loss=0.134843 lr=0.001287 Epoch[076] Batch [2399]/[3760] Speed: 94.139391 samples/sec accuracy=96.649740 loss=0.134823 lr=0.001286 Epoch[076] Batch [2449]/[3760] Speed: 92.909393 samples/sec accuracy=96.664541 loss=0.134470 lr=0.001284 Epoch[076] Batch [2499]/[3760] Speed: 95.329537 samples/sec accuracy=96.658125 loss=0.134777 lr=0.001283 Epoch[076] Batch [2549]/[3760] Speed: 94.078232 samples/sec accuracy=96.658088 loss=0.134865 lr=0.001282 Epoch[076] Batch [2599]/[3760] Speed: 93.015061 samples/sec accuracy=96.653846 loss=0.134986 lr=0.001280 Epoch[076] Batch [2649]/[3760] Speed: 94.569947 samples/sec accuracy=96.655660 loss=0.135043 lr=0.001279 Epoch[076] Batch [2699]/[3760] Speed: 93.961257 samples/sec accuracy=96.645833 loss=0.135128 lr=0.001277 Epoch[076] Batch [2749]/[3760] Speed: 93.620874 samples/sec accuracy=96.655682 loss=0.134881 lr=0.001276 Epoch[076] Batch [2799]/[3760] Speed: 93.129420 samples/sec accuracy=96.656250 loss=0.134877 lr=0.001275 Epoch[076] Batch [2849]/[3760] Speed: 94.660411 samples/sec accuracy=96.645833 loss=0.135137 lr=0.001273 Epoch[076] Batch [2899]/[3760] Speed: 92.726678 samples/sec accuracy=96.655172 loss=0.135042 lr=0.001272 Epoch[076] Batch [2949]/[3760] Speed: 95.370609 samples/sec accuracy=96.656250 loss=0.135125 lr=0.001271 Epoch[076] Batch [2999]/[3760] Speed: 93.617859 samples/sec accuracy=96.657292 loss=0.135109 lr=0.001269 Epoch[076] Batch [3049]/[3760] Speed: 93.035072 samples/sec accuracy=96.660861 loss=0.135097 lr=0.001268 Epoch[076] Batch [3099]/[3760] Speed: 94.029713 samples/sec accuracy=96.656754 loss=0.135175 lr=0.001266 Epoch[076] Batch [3149]/[3760] Speed: 93.551505 samples/sec accuracy=96.649802 loss=0.135253 lr=0.001265 Epoch[076] Batch [3199]/[3760] Speed: 94.289758 samples/sec accuracy=96.643555 loss=0.135396 lr=0.001264 Epoch[076] Batch [3249]/[3760] Speed: 92.884520 samples/sec accuracy=96.642788 loss=0.135343 lr=0.001262 Epoch[076] Batch [3299]/[3760] Speed: 94.370175 samples/sec accuracy=96.636364 loss=0.135561 lr=0.001261 Epoch[076] Batch [3349]/[3760] Speed: 92.699019 samples/sec accuracy=96.630597 loss=0.135661 lr=0.001259 Epoch[076] Batch [3399]/[3760] Speed: 95.355018 samples/sec accuracy=96.629136 loss=0.135723 lr=0.001258 Epoch[076] Batch [3449]/[3760] Speed: 93.908515 samples/sec accuracy=96.624547 loss=0.135862 lr=0.001257 Epoch[076] Batch [3499]/[3760] Speed: 93.048821 samples/sec accuracy=96.624107 loss=0.135908 lr=0.001255 Epoch[076] Batch [3549]/[3760] Speed: 93.855089 samples/sec accuracy=96.615317 loss=0.136053 lr=0.001254 Epoch[076] Batch [3599]/[3760] Speed: 93.133432 samples/sec accuracy=96.621962 loss=0.135949 lr=0.001252 Epoch[076] Batch [3649]/[3760] Speed: 94.253916 samples/sec accuracy=96.621575 loss=0.136103 lr=0.001251 Epoch[076] Batch [3699]/[3760] Speed: 92.487587 samples/sec accuracy=96.620355 loss=0.136074 lr=0.001250 Epoch[076] Batch [3749]/[3760] Speed: 107.011909 samples/sec accuracy=96.612917 loss=0.136153 lr=0.001248 Batch [0049]/[0303]: acc-top1=66.375000 acc-top5=85.031250 Batch [0099]/[0303]: acc-top1=64.562500 acc-top5=84.593750 Batch [0149]/[0303]: acc-top1=66.093750 acc-top5=85.677083 Batch [0199]/[0303]: acc-top1=68.570312 acc-top5=87.171875 Batch [0249]/[0303]: acc-top1=67.931250 acc-top5=86.656250 Batch [0299]/[0303]: acc-top1=67.458333 acc-top5=86.645833 [Epoch 076] training: accuracy=96.610289 loss=0.136172 [Epoch 076] speed: 93 samples/sec time cost: 2793.190695 [Epoch 076] validation: acc-top1=67.419554 acc-top5=86.607880 loss=2.421828 Epoch[077] Batch [0049]/[3760] Speed: 64.250573 samples/sec accuracy=96.968750 loss=0.130459 lr=0.001247 Epoch[077] Batch [0099]/[3760] Speed: 94.349355 samples/sec accuracy=97.140625 loss=0.122126 lr=0.001245 Epoch[077] Batch [0149]/[3760] Speed: 93.936657 samples/sec accuracy=97.229167 loss=0.121596 lr=0.001244 Epoch[077] Batch [0199]/[3760] Speed: 93.166860 samples/sec accuracy=97.054688 loss=0.124615 lr=0.001243 Epoch[077] Batch [0249]/[3760] Speed: 94.093524 samples/sec accuracy=97.050000 loss=0.122931 lr=0.001241 Epoch[077] Batch [0299]/[3760] Speed: 93.538635 samples/sec accuracy=97.046875 loss=0.122095 lr=0.001240 Epoch[077] Batch [0349]/[3760] Speed: 94.230940 samples/sec accuracy=96.959821 loss=0.124348 lr=0.001238 Epoch[077] Batch [0399]/[3760] Speed: 93.028333 samples/sec accuracy=96.945312 loss=0.123897 lr=0.001237 Epoch[077] Batch [0449]/[3760] Speed: 94.109449 samples/sec accuracy=96.937500 loss=0.124204 lr=0.001236 Epoch[077] Batch [0499]/[3760] Speed: 92.462006 samples/sec accuracy=96.993750 loss=0.122910 lr=0.001234 Epoch[077] Batch [0549]/[3760] Speed: 94.252905 samples/sec accuracy=97.039773 loss=0.122636 lr=0.001233 Epoch[077] Batch [0599]/[3760] Speed: 93.422833 samples/sec accuracy=97.049479 loss=0.122549 lr=0.001232 Epoch[077] Batch [0649]/[3760] Speed: 93.881205 samples/sec accuracy=97.016827 loss=0.123704 lr=0.001230 Epoch[077] Batch [0699]/[3760] Speed: 93.989957 samples/sec accuracy=97.037946 loss=0.124007 lr=0.001229 Epoch[077] Batch [0749]/[3760] Speed: 93.787150 samples/sec accuracy=97.033333 loss=0.123913 lr=0.001227 Epoch[077] Batch [0799]/[3760] Speed: 94.218606 samples/sec accuracy=97.048828 loss=0.123424 lr=0.001226 Epoch[077] Batch [0849]/[3760] Speed: 92.434090 samples/sec accuracy=97.020221 loss=0.123714 lr=0.001225 Epoch[077] Batch [0899]/[3760] Speed: 94.490067 samples/sec accuracy=97.013889 loss=0.123623 lr=0.001223 Epoch[077] Batch [0949]/[3760] Speed: 93.097385 samples/sec accuracy=96.981908 loss=0.124411 lr=0.001222 Epoch[077] Batch [0999]/[3760] Speed: 95.126943 samples/sec accuracy=96.973438 loss=0.124611 lr=0.001221 Epoch[077] Batch [1049]/[3760] Speed: 93.768502 samples/sec accuracy=96.961310 loss=0.125105 lr=0.001219 Epoch[077] Batch [1099]/[3760] Speed: 93.810888 samples/sec accuracy=96.953125 loss=0.125929 lr=0.001218 Epoch[077] Batch [1149]/[3760] Speed: 93.642341 samples/sec accuracy=96.937500 loss=0.125982 lr=0.001216 Epoch[077] Batch [1199]/[3760] Speed: 93.508533 samples/sec accuracy=96.921875 loss=0.126201 lr=0.001215 Epoch[077] Batch [1249]/[3760] Speed: 94.583525 samples/sec accuracy=96.922500 loss=0.125915 lr=0.001214 Epoch[077] Batch [1299]/[3760] Speed: 92.898650 samples/sec accuracy=96.895433 loss=0.126488 lr=0.001212 Epoch[077] Batch [1349]/[3760] Speed: 93.427566 samples/sec accuracy=96.891204 loss=0.126601 lr=0.001211 Epoch[077] Batch [1399]/[3760] Speed: 92.613218 samples/sec accuracy=96.881696 loss=0.126697 lr=0.001210 Epoch[077] Batch [1449]/[3760] Speed: 94.708606 samples/sec accuracy=96.884698 loss=0.127105 lr=0.001208 Epoch[077] Batch [1499]/[3760] Speed: 94.584358 samples/sec accuracy=96.877083 loss=0.127388 lr=0.001207 Epoch[077] Batch [1549]/[3760] Speed: 93.198550 samples/sec accuracy=96.885081 loss=0.127300 lr=0.001206 Epoch[077] Batch [1599]/[3760] Speed: 94.325023 samples/sec accuracy=96.879883 loss=0.127294 lr=0.001204 Epoch[077] Batch [1649]/[3760] Speed: 94.257776 samples/sec accuracy=96.881629 loss=0.127160 lr=0.001203 Epoch[077] Batch [1699]/[3760] Speed: 93.344405 samples/sec accuracy=96.886949 loss=0.127131 lr=0.001201 Epoch[077] Batch [1749]/[3760] Speed: 93.166777 samples/sec accuracy=96.881250 loss=0.127121 lr=0.001200 Epoch[077] Batch [1799]/[3760] Speed: 94.310924 samples/sec accuracy=96.858507 loss=0.127514 lr=0.001199 Epoch[077] Batch [1849]/[3760] Speed: 92.416829 samples/sec accuracy=96.842061 loss=0.127885 lr=0.001197 Epoch[077] Batch [1899]/[3760] Speed: 95.517147 samples/sec accuracy=96.838816 loss=0.127913 lr=0.001196 Epoch[077] Batch [1949]/[3760] Speed: 94.151277 samples/sec accuracy=96.853365 loss=0.127527 lr=0.001195 Epoch[077] Batch [1999]/[3760] Speed: 93.345074 samples/sec accuracy=96.834375 loss=0.128066 lr=0.001193 Epoch[077] Batch [2049]/[3760] Speed: 93.721613 samples/sec accuracy=96.829268 loss=0.128037 lr=0.001192 Epoch[077] Batch [2099]/[3760] Speed: 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lr=0.001178 Epoch[077] Batch [2599]/[3760] Speed: 94.239861 samples/sec accuracy=96.816707 loss=0.127964 lr=0.001177 Epoch[077] Batch [2649]/[3760] Speed: 92.587873 samples/sec accuracy=96.803066 loss=0.128262 lr=0.001176 Epoch[077] Batch [2699]/[3760] Speed: 95.378800 samples/sec accuracy=96.809028 loss=0.128046 lr=0.001174 Epoch[077] Batch [2749]/[3760] Speed: 93.784128 samples/sec accuracy=96.815909 loss=0.127927 lr=0.001173 Epoch[077] Batch [2799]/[3760] Speed: 93.419851 samples/sec accuracy=96.817522 loss=0.127959 lr=0.001172 Epoch[077] Batch [2849]/[3760] Speed: 93.734729 samples/sec accuracy=96.808114 loss=0.128284 lr=0.001170 Epoch[077] Batch [2899]/[3760] Speed: 94.794257 samples/sec accuracy=96.803341 loss=0.128370 lr=0.001169 Epoch[077] Batch [2949]/[3760] Speed: 94.704126 samples/sec accuracy=96.810911 loss=0.128205 lr=0.001168 Epoch[077] Batch [2999]/[3760] Speed: 92.925621 samples/sec accuracy=96.810938 loss=0.128185 lr=0.001166 Epoch[077] Batch [3049]/[3760] Speed: 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lr=0.001153 Epoch[077] Batch [3549]/[3760] Speed: 92.784944 samples/sec accuracy=96.830106 loss=0.127914 lr=0.001152 Epoch[077] Batch [3599]/[3760] Speed: 95.171553 samples/sec accuracy=96.828125 loss=0.128074 lr=0.001150 Epoch[077] Batch [3649]/[3760] Speed: 93.733663 samples/sec accuracy=96.824058 loss=0.128165 lr=0.001149 Epoch[077] Batch [3699]/[3760] Speed: 94.491799 samples/sec accuracy=96.830236 loss=0.128144 lr=0.001148 Epoch[077] Batch [3749]/[3760] Speed: 106.193018 samples/sec accuracy=96.821667 loss=0.128276 lr=0.001146 Batch [0049]/[0303]: acc-top1=65.812500 acc-top5=85.031250 Batch [0099]/[0303]: acc-top1=63.828125 acc-top5=84.515625 Batch [0149]/[0303]: acc-top1=65.635417 acc-top5=85.739583 Batch [0199]/[0303]: acc-top1=68.351562 acc-top5=86.992188 Batch [0249]/[0303]: acc-top1=67.868750 acc-top5=86.500000 Batch [0299]/[0303]: acc-top1=67.531250 acc-top5=86.515625 [Epoch 077] training: accuracy=96.820977 loss=0.128339 [Epoch 077] speed: 93 samples/sec time cost: 2793.329517 [Epoch 077] validation: acc-top1=67.476279 acc-top5=86.484117 loss=2.390626 Epoch[078] Batch [0049]/[3759] Speed: 64.611954 samples/sec accuracy=97.062500 loss=0.110563 lr=0.001145 Epoch[078] Batch [0099]/[3759] Speed: 94.510205 samples/sec accuracy=97.171875 loss=0.113915 lr=0.001143 Epoch[078] Batch [0149]/[3759] Speed: 93.147203 samples/sec accuracy=97.020833 loss=0.118476 lr=0.001142 Epoch[078] Batch [0199]/[3759] Speed: 94.120180 samples/sec accuracy=97.031250 loss=0.119536 lr=0.001141 Epoch[078] Batch [0249]/[3759] Speed: 93.215823 samples/sec accuracy=97.056250 loss=0.117500 lr=0.001139 Epoch[078] Batch [0299]/[3759] Speed: 94.694464 samples/sec accuracy=97.109375 loss=0.116277 lr=0.001138 Epoch[078] Batch [0349]/[3759] Speed: 92.170350 samples/sec accuracy=97.196429 loss=0.115078 lr=0.001137 Epoch[078] Batch [0399]/[3759] Speed: 94.784665 samples/sec accuracy=97.250000 loss=0.115584 lr=0.001135 Epoch[078] Batch [0449]/[3759] Speed: 94.589914 samples/sec accuracy=97.239583 loss=0.116003 lr=0.001134 Epoch[078] Batch [0499]/[3759] Speed: 93.416033 samples/sec accuracy=97.240625 loss=0.116011 lr=0.001133 Epoch[078] Batch [0549]/[3759] Speed: 94.086930 samples/sec accuracy=97.215909 loss=0.116781 lr=0.001131 Epoch[078] Batch [0599]/[3759] Speed: 93.306299 samples/sec accuracy=97.203125 loss=0.116676 lr=0.001130 Epoch[078] Batch [0649]/[3759] Speed: 94.099408 samples/sec accuracy=97.216346 loss=0.116222 lr=0.001129 Epoch[078] Batch [0699]/[3759] Speed: 92.552047 samples/sec accuracy=97.241071 loss=0.115980 lr=0.001127 Epoch[078] Batch [0749]/[3759] Speed: 94.412693 samples/sec accuracy=97.254167 loss=0.116087 lr=0.001126 Epoch[078] Batch [0799]/[3759] Speed: 92.322030 samples/sec accuracy=97.242188 loss=0.116981 lr=0.001125 Epoch[078] Batch [0849]/[3759] Speed: 95.749863 samples/sec accuracy=97.244485 loss=0.117301 lr=0.001124 Epoch[078] Batch [0899]/[3759] Speed: 93.478459 samples/sec accuracy=97.220486 loss=0.117477 lr=0.001122 Epoch[078] 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accuracy=97.180804 loss=0.116822 lr=0.001109 Epoch[078] Batch [1449]/[3759] Speed: 94.488169 samples/sec accuracy=97.185345 loss=0.116868 lr=0.001108 Epoch[078] Batch [1499]/[3759] Speed: 92.399152 samples/sec accuracy=97.175000 loss=0.117073 lr=0.001106 Epoch[078] Batch [1549]/[3759] Speed: 93.513080 samples/sec accuracy=97.160282 loss=0.117240 lr=0.001105 Epoch[078] Batch [1599]/[3759] Speed: 92.653360 samples/sec accuracy=97.166016 loss=0.117174 lr=0.001104 Epoch[078] Batch [1649]/[3759] Speed: 94.412405 samples/sec accuracy=97.155303 loss=0.117338 lr=0.001102 Epoch[078] Batch [1699]/[3759] Speed: 93.840608 samples/sec accuracy=97.162684 loss=0.117456 lr=0.001101 Epoch[078] Batch [1749]/[3759] Speed: 92.750836 samples/sec accuracy=97.155357 loss=0.117585 lr=0.001100 Epoch[078] Batch [1799]/[3759] Speed: 93.811858 samples/sec accuracy=97.146701 loss=0.117818 lr=0.001099 Epoch[078] Batch [1849]/[3759] Speed: 93.485852 samples/sec accuracy=97.146115 loss=0.117888 lr=0.001097 Epoch[078] 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accuracy=97.104388 loss=0.118739 lr=0.001084 Epoch[078] Batch [2399]/[3759] Speed: 92.334603 samples/sec accuracy=97.102865 loss=0.118846 lr=0.001083 Epoch[078] Batch [2449]/[3759] Speed: 94.367934 samples/sec accuracy=97.096301 loss=0.119101 lr=0.001082 Epoch[078] Batch [2499]/[3759] Speed: 93.035514 samples/sec accuracy=97.102500 loss=0.118990 lr=0.001080 Epoch[078] Batch [2549]/[3759] Speed: 94.011382 samples/sec accuracy=97.099877 loss=0.118985 lr=0.001079 Epoch[078] Batch [2599]/[3759] Speed: 94.375799 samples/sec accuracy=97.096755 loss=0.119037 lr=0.001078 Epoch[078] Batch [2649]/[3759] Speed: 92.668375 samples/sec accuracy=97.093750 loss=0.119023 lr=0.001076 Epoch[078] Batch [2699]/[3759] Speed: 94.453671 samples/sec accuracy=97.095486 loss=0.118835 lr=0.001075 Epoch[078] Batch [2749]/[3759] Speed: 93.772047 samples/sec accuracy=97.093182 loss=0.118857 lr=0.001074 Epoch[078] Batch [2799]/[3759] Speed: 93.749343 samples/sec accuracy=97.094866 loss=0.118727 lr=0.001073 Epoch[078] 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accuracy=97.067708 loss=0.119301 lr=0.001060 Epoch[078] Batch [3349]/[3759] Speed: 93.508052 samples/sec accuracy=97.058302 loss=0.119700 lr=0.001058 Epoch[078] Batch [3399]/[3759] Speed: 94.200897 samples/sec accuracy=97.051011 loss=0.119908 lr=0.001057 Epoch[078] Batch [3449]/[3759] Speed: 93.216016 samples/sec accuracy=97.050272 loss=0.119860 lr=0.001056 Epoch[078] Batch [3499]/[3759] Speed: 94.273137 samples/sec accuracy=97.045536 loss=0.119920 lr=0.001055 Epoch[078] Batch [3549]/[3759] Speed: 93.047074 samples/sec accuracy=97.042694 loss=0.119969 lr=0.001053 Epoch[078] Batch [3599]/[3759] Speed: 94.217598 samples/sec accuracy=97.045573 loss=0.119930 lr=0.001052 Epoch[078] Batch [3649]/[3759] Speed: 93.931276 samples/sec accuracy=97.050514 loss=0.119910 lr=0.001051 Epoch[078] Batch [3699]/[3759] Speed: 93.065371 samples/sec accuracy=97.045608 loss=0.119971 lr=0.001049 Epoch[078] Batch [3749]/[3759] Speed: 106.900114 samples/sec accuracy=97.045417 loss=0.119964 lr=0.001048 Batch [0049]/[0303]: acc-top1=66.062500 acc-top5=85.250000 Batch [0099]/[0303]: acc-top1=64.562500 acc-top5=84.796875 Batch [0149]/[0303]: acc-top1=65.791667 acc-top5=85.593750 Batch [0199]/[0303]: acc-top1=68.203125 acc-top5=86.914062 Batch [0249]/[0303]: acc-top1=67.731250 acc-top5=86.506250 Batch [0299]/[0303]: acc-top1=67.338542 acc-top5=86.484375 [Epoch 078] training: accuracy=97.047918 loss=0.119931 [Epoch 078] speed: 93 samples/sec time cost: 2794.519517 [Epoch 078] validation: acc-top1=67.321576 acc-top5=86.463490 loss=2.445384 Epoch[079] Batch [0049]/[3760] Speed: 64.192090 samples/sec accuracy=98.062500 loss=0.094293 lr=0.001047 Epoch[079] Batch [0099]/[3760] Speed: 93.545172 samples/sec accuracy=98.000000 loss=0.090602 lr=0.001045 Epoch[079] Batch [0149]/[3760] Speed: 93.392668 samples/sec accuracy=97.739583 loss=0.101077 lr=0.001044 Epoch[079] Batch [0199]/[3760] Speed: 94.550637 samples/sec accuracy=97.617188 loss=0.102585 lr=0.001043 Epoch[079] Batch [0249]/[3760] Speed: 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lr=0.001030 Epoch[079] Batch [0749]/[3760] Speed: 94.722377 samples/sec accuracy=97.339583 loss=0.110374 lr=0.001029 Epoch[079] Batch [0799]/[3760] Speed: 94.496841 samples/sec accuracy=97.337891 loss=0.111104 lr=0.001028 Epoch[079] Batch [0849]/[3760] Speed: 93.173990 samples/sec accuracy=97.340074 loss=0.110993 lr=0.001026 Epoch[079] Batch [0899]/[3760] Speed: 93.945034 samples/sec accuracy=97.335069 loss=0.111057 lr=0.001025 Epoch[079] Batch [0949]/[3760] Speed: 93.278977 samples/sec accuracy=97.279605 loss=0.112576 lr=0.001024 Epoch[079] Batch [0999]/[3760] Speed: 94.396219 samples/sec accuracy=97.271875 loss=0.112664 lr=0.001022 Epoch[079] Batch [1049]/[3760] Speed: 93.163040 samples/sec accuracy=97.290179 loss=0.112152 lr=0.001021 Epoch[079] Batch [1099]/[3760] Speed: 95.102418 samples/sec accuracy=97.282670 loss=0.112543 lr=0.001020 Epoch[079] Batch [1149]/[3760] Speed: 92.754728 samples/sec accuracy=97.294837 loss=0.112124 lr=0.001019 Epoch[079] Batch [1199]/[3760] Speed: 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lr=0.000959 Epoch[079] Batch [3599]/[3760] Speed: 92.624874 samples/sec accuracy=97.229167 loss=0.113694 lr=0.000958 Epoch[079] Batch [3649]/[3760] Speed: 94.909953 samples/sec accuracy=97.219606 loss=0.113986 lr=0.000956 Epoch[079] Batch [3699]/[3760] Speed: 92.073712 samples/sec accuracy=97.215372 loss=0.114098 lr=0.000955 Epoch[079] Batch [3749]/[3760] Speed: 107.760660 samples/sec accuracy=97.217500 loss=0.114051 lr=0.000954 Batch [0049]/[0303]: acc-top1=66.531250 acc-top5=85.906250 Batch [0099]/[0303]: acc-top1=64.843750 acc-top5=85.062500 Batch [0149]/[0303]: acc-top1=66.020833 acc-top5=85.989583 Batch [0199]/[0303]: acc-top1=68.648438 acc-top5=87.210938 Batch [0249]/[0303]: acc-top1=68.212500 acc-top5=86.781250 Batch [0299]/[0303]: acc-top1=67.713542 acc-top5=86.739583 [Epoch 079] training: accuracy=97.217836 loss=0.114021 [Epoch 079] speed: 93 samples/sec time cost: 2795.654349 [Epoch 079] validation: acc-top1=67.703177 acc-top5=86.736799 loss=2.327122 Epoch[080] Batch 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accuracy=97.493750 loss=0.103927 lr=0.000941 Epoch[080] Batch [0549]/[3760] Speed: 93.831711 samples/sec accuracy=97.508523 loss=0.104078 lr=0.000940 Epoch[080] Batch [0599]/[3760] Speed: 94.030881 samples/sec accuracy=97.481771 loss=0.105453 lr=0.000939 Epoch[080] Batch [0649]/[3760] Speed: 93.307516 samples/sec accuracy=97.475962 loss=0.105268 lr=0.000938 Epoch[080] Batch [0699]/[3760] Speed: 94.909680 samples/sec accuracy=97.488839 loss=0.104465 lr=0.000937 Epoch[080] Batch [0749]/[3760] Speed: 92.245836 samples/sec accuracy=97.491667 loss=0.104766 lr=0.000935 Epoch[080] Batch [0799]/[3760] Speed: 95.414615 samples/sec accuracy=97.447266 loss=0.105660 lr=0.000934 Epoch[080] Batch [0849]/[3760] Speed: 93.787156 samples/sec accuracy=97.454044 loss=0.105595 lr=0.000933 Epoch[080] Batch [0899]/[3760] Speed: 93.896802 samples/sec accuracy=97.451389 loss=0.105569 lr=0.000932 Epoch[080] Batch [0949]/[3760] Speed: 93.524929 samples/sec accuracy=97.488487 loss=0.104643 lr=0.000930 Epoch[080] 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accuracy=97.415948 loss=0.107051 lr=0.000918 Epoch[080] Batch [1499]/[3760] Speed: 94.291542 samples/sec accuracy=97.405208 loss=0.107061 lr=0.000917 Epoch[080] Batch [1549]/[3760] Speed: 94.311865 samples/sec accuracy=97.393145 loss=0.107174 lr=0.000916 Epoch[080] Batch [1599]/[3760] Speed: 92.408405 samples/sec accuracy=97.395508 loss=0.106946 lr=0.000915 Epoch[080] Batch [1649]/[3760] Speed: 94.625382 samples/sec accuracy=97.396780 loss=0.107033 lr=0.000914 Epoch[080] Batch [1699]/[3760] Speed: 93.760640 samples/sec accuracy=97.387868 loss=0.107107 lr=0.000912 Epoch[080] Batch [1749]/[3760] Speed: 95.281601 samples/sec accuracy=97.376786 loss=0.107387 lr=0.000911 Epoch[080] Batch [1799]/[3760] Speed: 93.208818 samples/sec accuracy=97.385417 loss=0.107350 lr=0.000910 Epoch[080] Batch [1849]/[3760] Speed: 95.271484 samples/sec accuracy=97.395270 loss=0.107215 lr=0.000909 Epoch[080] Batch [1899]/[3760] Speed: 94.215055 samples/sec accuracy=97.393092 loss=0.107115 lr=0.000907 Epoch[080] 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accuracy=97.408854 loss=0.106803 lr=0.000896 Epoch[080] Batch [2449]/[3760] Speed: 94.385515 samples/sec accuracy=97.406250 loss=0.106975 lr=0.000894 Epoch[080] Batch [2499]/[3760] Speed: 92.222774 samples/sec accuracy=97.410625 loss=0.106884 lr=0.000893 Epoch[080] Batch [2549]/[3760] Speed: 95.298880 samples/sec accuracy=97.406250 loss=0.106996 lr=0.000892 Epoch[080] Batch [2599]/[3760] Speed: 93.487077 samples/sec accuracy=97.412861 loss=0.106877 lr=0.000891 Epoch[080] Batch [2649]/[3760] Speed: 93.395364 samples/sec accuracy=97.415094 loss=0.106893 lr=0.000890 Epoch[080] Batch [2699]/[3760] Speed: 94.285244 samples/sec accuracy=97.424190 loss=0.106744 lr=0.000888 Epoch[080] Batch [2749]/[3760] Speed: 93.765975 samples/sec accuracy=97.424432 loss=0.106619 lr=0.000887 Epoch[080] Batch [2799]/[3760] Speed: 94.519372 samples/sec accuracy=97.423549 loss=0.106658 lr=0.000886 Epoch[080] Batch [2849]/[3760] Speed: 92.040314 samples/sec accuracy=97.427083 loss=0.106464 lr=0.000885 Epoch[080] Batch [2899]/[3760] Speed: 94.485791 samples/sec accuracy=97.418642 loss=0.106571 lr=0.000884 Epoch[080] Batch [2949]/[3760] Speed: 94.536360 samples/sec accuracy=97.410487 loss=0.106715 lr=0.000882 Epoch[080] Batch [2999]/[3760] Speed: 93.381058 samples/sec accuracy=97.414583 loss=0.106616 lr=0.000881 Epoch[080] Batch [3049]/[3760] Speed: 94.060689 samples/sec accuracy=97.410861 loss=0.106580 lr=0.000880 Epoch[080] Batch [3099]/[3760] Speed: 93.660785 samples/sec accuracy=97.407258 loss=0.106594 lr=0.000879 Epoch[080] Batch [3149]/[3760] Speed: 93.788392 samples/sec accuracy=97.406250 loss=0.106639 lr=0.000878 Epoch[080] Batch [3199]/[3760] Speed: 92.244749 samples/sec accuracy=97.401855 loss=0.106892 lr=0.000877 Epoch[080] Batch [3249]/[3760] Speed: 95.446547 samples/sec accuracy=97.404808 loss=0.106825 lr=0.000875 Epoch[080] Batch [3299]/[3760] Speed: 93.149507 samples/sec accuracy=97.408144 loss=0.106865 lr=0.000874 Epoch[080] Batch [3349]/[3760] Speed: 94.202611 samples/sec accuracy=97.403451 loss=0.107005 lr=0.000873 Epoch[080] Batch [3399]/[3760] Speed: 94.895042 samples/sec accuracy=97.400735 loss=0.107055 lr=0.000872 Epoch[080] Batch [3449]/[3760] Speed: 93.412813 samples/sec accuracy=97.401268 loss=0.107097 lr=0.000871 Epoch[080] Batch [3499]/[3760] Speed: 94.010883 samples/sec accuracy=97.403125 loss=0.107029 lr=0.000869 Epoch[080] Batch [3549]/[3760] Speed: 92.445764 samples/sec accuracy=97.404930 loss=0.106962 lr=0.000868 Epoch[080] Batch [3599]/[3760] Speed: 94.803963 samples/sec accuracy=97.407118 loss=0.107041 lr=0.000867 Epoch[080] Batch [3649]/[3760] Speed: 93.392827 samples/sec accuracy=97.412243 loss=0.106917 lr=0.000866 Epoch[080] Batch [3699]/[3760] Speed: 93.627225 samples/sec accuracy=97.407095 loss=0.107073 lr=0.000865 Epoch[080] Batch [3749]/[3760] Speed: 106.682372 samples/sec accuracy=97.405000 loss=0.107077 lr=0.000864 Batch [0049]/[0303]: acc-top1=66.656250 acc-top5=85.375000 Batch [0099]/[0303]: acc-top1=64.843750 acc-top5=84.906250 Batch [0149]/[0303]: acc-top1=66.114583 acc-top5=85.729167 Batch [0199]/[0303]: acc-top1=68.562500 acc-top5=87.070312 Batch [0249]/[0303]: acc-top1=68.118750 acc-top5=86.575000 Batch [0299]/[0303]: acc-top1=67.770833 acc-top5=86.578125 [Epoch 080] training: accuracy=97.406084 loss=0.107002 [Epoch 080] speed: 93 samples/sec time cost: 2792.335321 [Epoch 080] validation: acc-top1=67.754744 acc-top5=86.561469 loss=2.389175 Epoch[081] Batch [0049]/[3759] Speed: 65.367662 samples/sec accuracy=97.500000 loss=0.106810 lr=0.000862 Epoch[081] Batch [0099]/[3759] Speed: 94.508435 samples/sec accuracy=97.421875 loss=0.105976 lr=0.000861 Epoch[081] Batch [0149]/[3759] Speed: 93.495885 samples/sec accuracy=97.447917 loss=0.103263 lr=0.000860 Epoch[081] Batch [0199]/[3759] Speed: 94.696055 samples/sec accuracy=97.523438 loss=0.102270 lr=0.000859 Epoch[081] Batch [0249]/[3759] Speed: 94.110179 samples/sec accuracy=97.500000 loss=0.102415 lr=0.000857 Epoch[081] Batch [0299]/[3759] 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accuracy=97.631076 loss=0.100132 lr=0.000781 Epoch[081] Batch [3649]/[3759] Speed: 93.693689 samples/sec accuracy=97.628853 loss=0.100221 lr=0.000780 Epoch[081] Batch [3699]/[3759] Speed: 93.179808 samples/sec accuracy=97.629645 loss=0.100353 lr=0.000778 Epoch[081] Batch [3749]/[3759] Speed: 107.421983 samples/sec accuracy=97.628333 loss=0.100372 lr=0.000777 Batch [0049]/[0303]: acc-top1=66.718750 acc-top5=85.218750 Batch [0099]/[0303]: acc-top1=64.656250 acc-top5=84.593750 Batch [0149]/[0303]: acc-top1=65.802083 acc-top5=85.677083 Batch [0199]/[0303]: acc-top1=68.570312 acc-top5=87.093750 Batch [0249]/[0303]: acc-top1=68.212500 acc-top5=86.706250 Batch [0299]/[0303]: acc-top1=67.937500 acc-top5=86.593750 [Epoch 081] training: accuracy=97.626945 loss=0.100417 [Epoch 081] speed: 93 samples/sec time cost: 2793.251584 [Epoch 081] validation: acc-top1=67.857880 acc-top5=86.556312 loss=2.397359 Epoch[082] Batch [0049]/[3760] Speed: 64.063089 samples/sec accuracy=98.156250 loss=0.084397 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94.179782 samples/sec accuracy=97.821232 loss=0.093810 lr=0.000703 Epoch[082] Batch [3449]/[3760] Speed: 94.201321 samples/sec accuracy=97.822917 loss=0.093723 lr=0.000702 Epoch[082] Batch [3499]/[3760] Speed: 92.373630 samples/sec accuracy=97.818750 loss=0.093743 lr=0.000701 Epoch[082] Batch [3549]/[3760] Speed: 94.914624 samples/sec accuracy=97.816901 loss=0.093748 lr=0.000700 Epoch[082] Batch [3599]/[3760] Speed: 93.743220 samples/sec accuracy=97.813802 loss=0.093819 lr=0.000699 Epoch[082] Batch [3649]/[3760] Speed: 93.670062 samples/sec accuracy=97.818921 loss=0.093736 lr=0.000697 Epoch[082] Batch [3699]/[3760] Speed: 94.492327 samples/sec accuracy=97.820524 loss=0.093686 lr=0.000696 Epoch[082] Batch [3749]/[3760] Speed: 103.765355 samples/sec accuracy=97.819167 loss=0.093742 lr=0.000695 Batch [0049]/[0303]: acc-top1=66.687500 acc-top5=85.500000 Batch [0099]/[0303]: acc-top1=64.750000 acc-top5=84.937500 Batch [0149]/[0303]: acc-top1=66.083333 acc-top5=85.562500 Batch [0199]/[0303]: acc-top1=69.007812 acc-top5=87.039062 Batch [0249]/[0303]: acc-top1=68.487500 acc-top5=86.543750 Batch [0299]/[0303]: acc-top1=68.088542 acc-top5=86.614583 [Epoch 082] training: accuracy=97.819149 loss=0.093743 [Epoch 082] speed: 93 samples/sec time cost: 2794.734839 [Epoch 082] validation: acc-top1=68.022896 acc-top5=86.566625 loss=2.374023 Epoch[083] Batch [0049]/[3760] Speed: 64.517433 samples/sec accuracy=97.937500 loss=0.085459 lr=0.000694 Epoch[083] Batch [0099]/[3760] Speed: 93.127756 samples/sec accuracy=97.796875 loss=0.090402 lr=0.000693 Epoch[083] Batch [0149]/[3760] Speed: 94.600081 samples/sec accuracy=97.895833 loss=0.090817 lr=0.000692 Epoch[083] Batch [0199]/[3760] Speed: 93.351738 samples/sec accuracy=97.921875 loss=0.090876 lr=0.000691 Epoch[083] Batch [0249]/[3760] Speed: 93.561067 samples/sec accuracy=97.956250 loss=0.089199 lr=0.000690 Epoch[083] Batch [0299]/[3760] Speed: 93.627181 samples/sec accuracy=98.010417 loss=0.087641 lr=0.000689 Epoch[083] Batch 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accuracy=97.981164 loss=0.088535 lr=0.000620 Epoch[083] Batch [3699]/[3760] Speed: 91.041980 samples/sec accuracy=97.988598 loss=0.088456 lr=0.000619 Epoch[083] Batch [3749]/[3760] Speed: 107.942520 samples/sec accuracy=97.990833 loss=0.088396 lr=0.000618 Batch [0049]/[0303]: acc-top1=66.187500 acc-top5=85.468750 Batch [0099]/[0303]: acc-top1=64.796875 acc-top5=84.812500 Batch [0149]/[0303]: acc-top1=66.177083 acc-top5=85.781250 Batch [0199]/[0303]: acc-top1=68.875000 acc-top5=87.101562 Batch [0249]/[0303]: acc-top1=68.487500 acc-top5=86.756250 Batch [0299]/[0303]: acc-top1=68.067708 acc-top5=86.723958 [Epoch 083] training: accuracy=97.991606 loss=0.088344 [Epoch 083] speed: 93 samples/sec time cost: 2794.789462 [Epoch 083] validation: acc-top1=68.033210 acc-top5=86.669761 loss=2.368381 Epoch[084] Batch [0049]/[3759] Speed: 64.889778 samples/sec accuracy=98.125000 loss=0.083634 lr=0.000616 Epoch[084] Batch [0099]/[3759] Speed: 92.831844 samples/sec accuracy=98.328125 loss=0.080497 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lr=0.000559 Epoch[084] Batch [2999]/[3759] Speed: 93.741050 samples/sec accuracy=98.143750 loss=0.082441 lr=0.000558 Epoch[084] Batch [3049]/[3759] Speed: 93.968272 samples/sec accuracy=98.141393 loss=0.082497 lr=0.000557 Epoch[084] Batch [3099]/[3759] Speed: 92.729283 samples/sec accuracy=98.145665 loss=0.082392 lr=0.000556 Epoch[084] Batch [3149]/[3759] Speed: 95.266326 samples/sec accuracy=98.141865 loss=0.082504 lr=0.000556 Epoch[084] Batch [3199]/[3759] Speed: 94.032348 samples/sec accuracy=98.141602 loss=0.082514 lr=0.000555 Epoch[084] Batch [3249]/[3759] Speed: 93.641835 samples/sec accuracy=98.140865 loss=0.082624 lr=0.000554 Epoch[084] Batch [3299]/[3759] Speed: 94.027071 samples/sec accuracy=98.141572 loss=0.082579 lr=0.000553 Epoch[084] Batch [3349]/[3759] Speed: 92.506215 samples/sec accuracy=98.138526 loss=0.082619 lr=0.000552 Epoch[084] Batch [3399]/[3759] Speed: 94.652437 samples/sec accuracy=98.138787 loss=0.082645 lr=0.000551 Epoch[084] Batch [3449]/[3759] Speed: 93.882996 samples/sec accuracy=98.137681 loss=0.082633 lr=0.000550 Epoch[084] Batch [3499]/[3759] Speed: 94.089855 samples/sec accuracy=98.134375 loss=0.082731 lr=0.000549 Epoch[084] Batch [3549]/[3759] Speed: 94.072386 samples/sec accuracy=98.135123 loss=0.082770 lr=0.000548 Epoch[084] Batch [3599]/[3759] Speed: 92.376469 samples/sec accuracy=98.131076 loss=0.082722 lr=0.000547 Epoch[084] Batch [3649]/[3759] Speed: 94.353354 samples/sec accuracy=98.128853 loss=0.082890 lr=0.000546 Epoch[084] Batch [3699]/[3759] Speed: 93.469498 samples/sec accuracy=98.129645 loss=0.082939 lr=0.000545 Epoch[084] Batch [3749]/[3759] Speed: 105.829053 samples/sec accuracy=98.124167 loss=0.083117 lr=0.000544 Batch [0049]/[0303]: acc-top1=66.093750 acc-top5=85.000000 Batch [0099]/[0303]: acc-top1=64.625000 acc-top5=84.625000 Batch [0149]/[0303]: acc-top1=66.031250 acc-top5=85.718750 Batch [0199]/[0303]: acc-top1=68.820312 acc-top5=87.117188 Batch [0249]/[0303]: acc-top1=68.262500 acc-top5=86.718750 Batch [0299]/[0303]: acc-top1=67.989583 acc-top5=86.729167 [Epoch 084] training: accuracy=98.123670 loss=0.083128 [Epoch 084] speed: 93 samples/sec time cost: 2795.308020 [Epoch 084] validation: acc-top1=67.966172 acc-top5=86.685231 loss=2.377327 Epoch[085] Batch [0049]/[3760] Speed: 64.730153 samples/sec accuracy=97.843750 loss=0.088861 lr=0.000543 Epoch[085] Batch [0099]/[3760] Speed: 93.702424 samples/sec accuracy=97.828125 loss=0.084608 lr=0.000542 Epoch[085] Batch [0149]/[3760] Speed: 94.005859 samples/sec accuracy=98.093750 loss=0.081509 lr=0.000541 Epoch[085] Batch [0199]/[3760] Speed: 92.047965 samples/sec accuracy=98.148438 loss=0.080509 lr=0.000540 Epoch[085] Batch [0249]/[3760] Speed: 95.529005 samples/sec accuracy=98.162500 loss=0.080755 lr=0.000539 Epoch[085] Batch [0299]/[3760] Speed: 94.174890 samples/sec accuracy=98.156250 loss=0.081090 lr=0.000538 Epoch[085] Batch [0349]/[3760] Speed: 93.726388 samples/sec accuracy=98.187500 loss=0.080329 lr=0.000537 Epoch[085] Batch 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accuracy=98.202206 loss=0.078853 lr=0.000528 Epoch[085] Batch [0899]/[3760] Speed: 94.300762 samples/sec accuracy=98.208333 loss=0.079097 lr=0.000527 Epoch[085] Batch [0949]/[3760] Speed: 92.924634 samples/sec accuracy=98.210526 loss=0.079165 lr=0.000526 Epoch[085] Batch [0999]/[3760] Speed: 94.083816 samples/sec accuracy=98.201562 loss=0.079449 lr=0.000525 Epoch[085] Batch [1049]/[3760] Speed: 94.271951 samples/sec accuracy=98.203869 loss=0.079519 lr=0.000524 Epoch[085] Batch [1099]/[3760] Speed: 93.369156 samples/sec accuracy=98.176136 loss=0.080401 lr=0.000523 Epoch[085] Batch [1149]/[3760] Speed: 94.271120 samples/sec accuracy=98.171196 loss=0.080402 lr=0.000522 Epoch[085] Batch [1199]/[3760] Speed: 94.042574 samples/sec accuracy=98.161458 loss=0.080707 lr=0.000521 Epoch[085] Batch [1249]/[3760] Speed: 93.806842 samples/sec accuracy=98.155000 loss=0.080842 lr=0.000520 Epoch[085] Batch [1299]/[3760] Speed: 91.852684 samples/sec accuracy=98.157452 loss=0.080789 lr=0.000520 Epoch[085] 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accuracy=98.116319 loss=0.081843 lr=0.000510 Epoch[085] Batch [1849]/[3760] Speed: 94.678301 samples/sec accuracy=98.131757 loss=0.081581 lr=0.000509 Epoch[085] Batch [1899]/[3760] Speed: 94.004907 samples/sec accuracy=98.130757 loss=0.081585 lr=0.000508 Epoch[085] Batch [1949]/[3760] Speed: 93.394931 samples/sec accuracy=98.133814 loss=0.081487 lr=0.000508 Epoch[085] Batch [1999]/[3760] Speed: 94.045428 samples/sec accuracy=98.124219 loss=0.081812 lr=0.000507 Epoch[085] Batch [2049]/[3760] Speed: 92.569859 samples/sec accuracy=98.124238 loss=0.081815 lr=0.000506 Epoch[085] Batch [2099]/[3760] Speed: 94.545285 samples/sec accuracy=98.130208 loss=0.081646 lr=0.000505 Epoch[085] Batch [2149]/[3760] Speed: 94.141130 samples/sec accuracy=98.134448 loss=0.081619 lr=0.000504 Epoch[085] Batch [2199]/[3760] Speed: 93.343449 samples/sec accuracy=98.132812 loss=0.081560 lr=0.000503 Epoch[085] Batch [2249]/[3760] Speed: 93.995415 samples/sec accuracy=98.141667 loss=0.081309 lr=0.000502 Epoch[085] 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accuracy=98.151136 loss=0.081039 lr=0.000493 Epoch[085] Batch [2799]/[3760] Speed: 93.117923 samples/sec accuracy=98.146763 loss=0.081111 lr=0.000492 Epoch[085] Batch [2849]/[3760] Speed: 94.543956 samples/sec accuracy=98.148575 loss=0.081038 lr=0.000491 Epoch[085] Batch [2899]/[3760] Speed: 93.382997 samples/sec accuracy=98.148168 loss=0.081164 lr=0.000490 Epoch[085] Batch [2949]/[3760] Speed: 93.085166 samples/sec accuracy=98.147775 loss=0.081186 lr=0.000489 Epoch[085] Batch [2999]/[3760] Speed: 93.367743 samples/sec accuracy=98.144792 loss=0.081253 lr=0.000488 Epoch[085] Batch [3049]/[3760] Speed: 93.333798 samples/sec accuracy=98.142418 loss=0.081330 lr=0.000488 Epoch[085] Batch [3099]/[3760] Speed: 93.635029 samples/sec accuracy=98.133569 loss=0.081443 lr=0.000487 Epoch[085] Batch [3149]/[3760] Speed: 92.327005 samples/sec accuracy=98.134425 loss=0.081515 lr=0.000486 Epoch[085] Batch [3199]/[3760] Speed: 95.162572 samples/sec accuracy=98.134277 loss=0.081421 lr=0.000485 Epoch[085] 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accuracy=98.144848 loss=0.081196 lr=0.000476 Epoch[085] Batch [3749]/[3760] Speed: 106.131503 samples/sec accuracy=98.142500 loss=0.081266 lr=0.000475 Batch [0049]/[0303]: acc-top1=67.187500 acc-top5=85.406250 Batch [0099]/[0303]: acc-top1=65.203125 acc-top5=84.750000 Batch [0149]/[0303]: acc-top1=66.406250 acc-top5=85.687500 Batch [0199]/[0303]: acc-top1=69.062500 acc-top5=87.101562 Batch [0249]/[0303]: acc-top1=68.606250 acc-top5=86.643750 Batch [0299]/[0303]: acc-top1=68.218750 acc-top5=86.552083 [Epoch 085] training: accuracy=98.143285 loss=0.081283 [Epoch 085] speed: 93 samples/sec time cost: 2794.302252 [Epoch 085] validation: acc-top1=68.167285 acc-top5=86.499587 loss=2.379085 Epoch[086] Batch [0049]/[3760] Speed: 63.649964 samples/sec accuracy=98.031250 loss=0.084502 lr=0.000474 Epoch[086] Batch [0099]/[3760] Speed: 93.916767 samples/sec accuracy=98.125000 loss=0.078267 lr=0.000473 Epoch[086] Batch [0149]/[3760] Speed: 93.709512 samples/sec accuracy=98.093750 loss=0.080345 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lr=0.000455 Epoch[086] Batch [1149]/[3760] Speed: 93.820296 samples/sec accuracy=98.207880 loss=0.079137 lr=0.000455 Epoch[086] Batch [1199]/[3760] Speed: 93.886441 samples/sec accuracy=98.216146 loss=0.079240 lr=0.000454 Epoch[086] Batch [1249]/[3760] Speed: 92.066207 samples/sec accuracy=98.221250 loss=0.079087 lr=0.000453 Epoch[086] Batch [1299]/[3760] Speed: 95.214711 samples/sec accuracy=98.225962 loss=0.078768 lr=0.000452 Epoch[086] Batch [1349]/[3760] Speed: 94.070721 samples/sec accuracy=98.236111 loss=0.078478 lr=0.000451 Epoch[086] Batch [1399]/[3760] Speed: 94.011344 samples/sec accuracy=98.237723 loss=0.078351 lr=0.000450 Epoch[086] Batch [1449]/[3760] Speed: 94.109006 samples/sec accuracy=98.237069 loss=0.078358 lr=0.000449 Epoch[086] Batch [1499]/[3760] Speed: 91.997322 samples/sec accuracy=98.236458 loss=0.078543 lr=0.000449 Epoch[086] Batch [1549]/[3760] Speed: 96.132085 samples/sec accuracy=98.244960 loss=0.078230 lr=0.000448 Epoch[086] Batch [1599]/[3760] Speed: 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lr=0.000439 Epoch[086] Batch [2099]/[3760] Speed: 94.361336 samples/sec accuracy=98.267857 loss=0.078095 lr=0.000438 Epoch[086] Batch [2149]/[3760] Speed: 92.797829 samples/sec accuracy=98.266715 loss=0.078062 lr=0.000437 Epoch[086] Batch [2199]/[3760] Speed: 94.236579 samples/sec accuracy=98.251420 loss=0.078244 lr=0.000437 Epoch[086] Batch [2249]/[3760] Speed: 92.294900 samples/sec accuracy=98.252083 loss=0.078268 lr=0.000436 Epoch[086] Batch [2299]/[3760] Speed: 95.488654 samples/sec accuracy=98.247283 loss=0.078247 lr=0.000435 Epoch[086] Batch [2349]/[3760] Speed: 93.497321 samples/sec accuracy=98.250665 loss=0.078158 lr=0.000434 Epoch[086] Batch [2399]/[3760] Speed: 92.363323 samples/sec accuracy=98.251953 loss=0.078001 lr=0.000433 Epoch[086] Batch [2449]/[3760] Speed: 94.863299 samples/sec accuracy=98.249362 loss=0.078062 lr=0.000432 Epoch[086] Batch [2499]/[3760] Speed: 92.034692 samples/sec accuracy=98.245625 loss=0.078112 lr=0.000431 Epoch[086] Batch [2549]/[3760] Speed: 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lr=0.000423 Epoch[086] Batch [3049]/[3760] Speed: 95.866540 samples/sec accuracy=98.247439 loss=0.078267 lr=0.000422 Epoch[086] Batch [3099]/[3760] Speed: 93.975378 samples/sec accuracy=98.250000 loss=0.078213 lr=0.000421 Epoch[086] Batch [3149]/[3760] Speed: 93.672297 samples/sec accuracy=98.253968 loss=0.078005 lr=0.000420 Epoch[086] Batch [3199]/[3760] Speed: 94.316959 samples/sec accuracy=98.250977 loss=0.078026 lr=0.000420 Epoch[086] Batch [3249]/[3760] Speed: 91.934630 samples/sec accuracy=98.251442 loss=0.077965 lr=0.000419 Epoch[086] Batch [3299]/[3760] Speed: 95.182109 samples/sec accuracy=98.248580 loss=0.078117 lr=0.000418 Epoch[086] Batch [3349]/[3760] Speed: 94.003930 samples/sec accuracy=98.256996 loss=0.078000 lr=0.000417 Epoch[086] Batch [3399]/[3760] Speed: 93.751864 samples/sec accuracy=98.255515 loss=0.078005 lr=0.000416 Epoch[086] Batch [3449]/[3760] Speed: 94.276202 samples/sec accuracy=98.257699 loss=0.077873 lr=0.000415 Epoch[086] Batch [3499]/[3760] Speed: 91.309503 samples/sec accuracy=98.256696 loss=0.077931 lr=0.000415 Epoch[086] Batch [3549]/[3760] Speed: 96.064634 samples/sec accuracy=98.254842 loss=0.077978 lr=0.000414 Epoch[086] Batch [3599]/[3760] Speed: 94.271914 samples/sec accuracy=98.253906 loss=0.078005 lr=0.000413 Epoch[086] Batch [3649]/[3760] Speed: 93.113978 samples/sec accuracy=98.255993 loss=0.077962 lr=0.000412 Epoch[086] Batch [3699]/[3760] Speed: 94.988527 samples/sec accuracy=98.255068 loss=0.077947 lr=0.000411 Epoch[086] Batch [3749]/[3760] Speed: 105.306626 samples/sec accuracy=98.260417 loss=0.077782 lr=0.000410 Batch [0049]/[0303]: acc-top1=66.812500 acc-top5=85.593750 Batch [0099]/[0303]: acc-top1=65.078125 acc-top5=85.109375 Batch [0149]/[0303]: acc-top1=66.437500 acc-top5=85.927083 Batch [0199]/[0303]: acc-top1=69.101562 acc-top5=87.148438 Batch [0249]/[0303]: acc-top1=68.668750 acc-top5=86.668750 Batch [0299]/[0303]: acc-top1=68.291667 acc-top5=86.630208 [Epoch 086] training: accuracy=98.262134 loss=0.077721 [Epoch 086] speed: 93 samples/sec time cost: 2794.143827 [Epoch 086] validation: acc-top1=68.265264 acc-top5=86.587252 loss=2.359926 Epoch[087] Batch [0049]/[3759] Speed: 65.189009 samples/sec accuracy=98.343750 loss=0.070474 lr=0.000409 Epoch[087] Batch [0099]/[3759] Speed: 93.849440 samples/sec accuracy=98.546875 loss=0.066229 lr=0.000409 Epoch[087] Batch [0149]/[3759] Speed: 93.712180 samples/sec accuracy=98.437500 loss=0.069412 lr=0.000408 Epoch[087] Batch [0199]/[3759] Speed: 93.240636 samples/sec accuracy=98.460938 loss=0.070233 lr=0.000407 Epoch[087] Batch [0249]/[3759] Speed: 93.083936 samples/sec accuracy=98.393750 loss=0.072292 lr=0.000406 Epoch[087] Batch [0299]/[3759] Speed: 93.661121 samples/sec accuracy=98.442708 loss=0.070681 lr=0.000405 Epoch[087] Batch [0349]/[3759] Speed: 94.437074 samples/sec accuracy=98.495536 loss=0.070194 lr=0.000404 Epoch[087] Batch [0399]/[3759] Speed: 93.608437 samples/sec accuracy=98.460938 loss=0.070498 lr=0.000404 Epoch[087] 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accuracy=98.350694 loss=0.072748 lr=0.000395 Epoch[087] Batch [0949]/[3759] Speed: 93.958723 samples/sec accuracy=98.343750 loss=0.073461 lr=0.000395 Epoch[087] Batch [0999]/[3759] Speed: 93.133552 samples/sec accuracy=98.340625 loss=0.073512 lr=0.000394 Epoch[087] Batch [1049]/[3759] Speed: 95.137030 samples/sec accuracy=98.351190 loss=0.073300 lr=0.000393 Epoch[087] Batch [1099]/[3759] Speed: 94.352776 samples/sec accuracy=98.346591 loss=0.073277 lr=0.000392 Epoch[087] Batch [1149]/[3759] Speed: 93.717123 samples/sec accuracy=98.339674 loss=0.073614 lr=0.000391 Epoch[087] Batch [1199]/[3759] Speed: 94.468835 samples/sec accuracy=98.348958 loss=0.073578 lr=0.000391 Epoch[087] Batch [1249]/[3759] Speed: 93.096361 samples/sec accuracy=98.343750 loss=0.073531 lr=0.000390 Epoch[087] Batch [1299]/[3759] Speed: 94.495964 samples/sec accuracy=98.358173 loss=0.073185 lr=0.000389 Epoch[087] Batch [1349]/[3759] Speed: 93.884075 samples/sec accuracy=98.357639 loss=0.072975 lr=0.000388 Epoch[087] 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accuracy=98.380068 loss=0.072925 lr=0.000380 Epoch[087] Batch [1899]/[3759] Speed: 93.668819 samples/sec accuracy=98.374178 loss=0.073001 lr=0.000379 Epoch[087] Batch [1949]/[3759] Speed: 94.242093 samples/sec accuracy=98.375801 loss=0.073081 lr=0.000379 Epoch[087] Batch [1999]/[3759] Speed: 92.759012 samples/sec accuracy=98.385156 loss=0.072890 lr=0.000378 Epoch[087] Batch [2049]/[3759] Speed: 94.307669 samples/sec accuracy=98.387957 loss=0.072785 lr=0.000377 Epoch[087] Batch [2099]/[3759] Speed: 94.042864 samples/sec accuracy=98.387649 loss=0.072757 lr=0.000376 Epoch[087] Batch [2149]/[3759] Speed: 92.863446 samples/sec accuracy=98.388808 loss=0.072891 lr=0.000375 Epoch[087] Batch [2199]/[3759] Speed: 94.963429 samples/sec accuracy=98.388494 loss=0.072850 lr=0.000375 Epoch[087] Batch [2249]/[3759] Speed: 92.664299 samples/sec accuracy=98.388194 loss=0.072911 lr=0.000374 Epoch[087] Batch [2299]/[3759] Speed: 94.961623 samples/sec accuracy=98.384511 loss=0.073100 lr=0.000373 Epoch[087] 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accuracy=98.373884 loss=0.072801 lr=0.000365 Epoch[087] Batch [2849]/[3759] Speed: 94.245904 samples/sec accuracy=98.369518 loss=0.072837 lr=0.000364 Epoch[087] Batch [2899]/[3759] Speed: 93.702261 samples/sec accuracy=98.365841 loss=0.072911 lr=0.000364 Epoch[087] Batch [2949]/[3759] Speed: 94.522583 samples/sec accuracy=98.363347 loss=0.073099 lr=0.000363 Epoch[087] Batch [2999]/[3759] Speed: 92.487775 samples/sec accuracy=98.364583 loss=0.072982 lr=0.000362 Epoch[087] Batch [3049]/[3759] Speed: 94.509786 samples/sec accuracy=98.368852 loss=0.072920 lr=0.000361 Epoch[087] Batch [3099]/[3759] Speed: 94.481324 samples/sec accuracy=98.368952 loss=0.073084 lr=0.000360 Epoch[087] Batch [3149]/[3759] Speed: 93.419368 samples/sec accuracy=98.373016 loss=0.073048 lr=0.000360 Epoch[087] Batch [3199]/[3759] Speed: 93.196391 samples/sec accuracy=98.368652 loss=0.073109 lr=0.000359 Epoch[087] Batch [3249]/[3759] Speed: 93.262286 samples/sec accuracy=98.365385 loss=0.073172 lr=0.000358 Epoch[087] 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accuracy=98.365000 loss=0.073347 lr=0.000350 Batch [0049]/[0303]: acc-top1=66.500000 acc-top5=85.593750 Batch [0099]/[0303]: acc-top1=64.890625 acc-top5=84.812500 Batch [0149]/[0303]: acc-top1=66.031250 acc-top5=85.802083 Batch [0199]/[0303]: acc-top1=68.867188 acc-top5=87.140625 Batch [0249]/[0303]: acc-top1=68.443750 acc-top5=86.687500 Batch [0299]/[0303]: acc-top1=68.088542 acc-top5=86.598958 [Epoch 087] training: accuracy=98.362680 loss=0.073368 [Epoch 087] speed: 93 samples/sec time cost: 2793.185024 [Epoch 087] validation: acc-top1=68.028053 acc-top5=86.545998 loss=2.378901 Epoch[088] Batch [0049]/[3760] Speed: 64.285998 samples/sec accuracy=98.687500 loss=0.066794 lr=0.000349 Epoch[088] Batch [0099]/[3760] Speed: 93.909823 samples/sec accuracy=98.531250 loss=0.068764 lr=0.000349 Epoch[088] Batch [0149]/[3760] Speed: 92.857651 samples/sec accuracy=98.531250 loss=0.068801 lr=0.000348 Epoch[088] Batch [0199]/[3760] Speed: 93.935582 samples/sec accuracy=98.632812 loss=0.068756 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lr=0.000333 Epoch[088] Batch [1199]/[3760] Speed: 93.304021 samples/sec accuracy=98.510417 loss=0.069149 lr=0.000332 Epoch[088] Batch [1249]/[3760] Speed: 91.655319 samples/sec accuracy=98.501250 loss=0.069273 lr=0.000331 Epoch[088] Batch [1299]/[3760] Speed: 96.326882 samples/sec accuracy=98.506010 loss=0.068975 lr=0.000331 Epoch[088] Batch [1349]/[3760] Speed: 93.804616 samples/sec accuracy=98.508102 loss=0.068909 lr=0.000330 Epoch[088] Batch [1399]/[3760] Speed: 93.548180 samples/sec accuracy=98.506696 loss=0.068964 lr=0.000329 Epoch[088] Batch [1449]/[3760] Speed: 93.682847 samples/sec accuracy=98.497845 loss=0.068992 lr=0.000328 Epoch[088] Batch [1499]/[3760] Speed: 94.207887 samples/sec accuracy=98.500000 loss=0.068958 lr=0.000328 Epoch[088] Batch [1549]/[3760] Speed: 94.072387 samples/sec accuracy=98.508065 loss=0.068788 lr=0.000327 Epoch[088] Batch [1599]/[3760] Speed: 93.350610 samples/sec accuracy=98.510742 loss=0.068834 lr=0.000326 Epoch[088] Batch [1649]/[3760] Speed: 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lr=0.000319 Epoch[088] Batch [2149]/[3760] Speed: 93.082020 samples/sec accuracy=98.493459 loss=0.069120 lr=0.000318 Epoch[088] Batch [2199]/[3760] Speed: 94.674661 samples/sec accuracy=98.492898 loss=0.069077 lr=0.000317 Epoch[088] Batch [2249]/[3760] Speed: 93.836992 samples/sec accuracy=98.491667 loss=0.069254 lr=0.000316 Epoch[088] Batch [2299]/[3760] Speed: 93.082357 samples/sec accuracy=98.492527 loss=0.069287 lr=0.000316 Epoch[088] Batch [2349]/[3760] Speed: 93.330004 samples/sec accuracy=98.487367 loss=0.069469 lr=0.000315 Epoch[088] Batch [2399]/[3760] Speed: 92.961387 samples/sec accuracy=98.490234 loss=0.069424 lr=0.000314 Epoch[088] Batch [2449]/[3760] Speed: 94.559110 samples/sec accuracy=98.491071 loss=0.069249 lr=0.000314 Epoch[088] Batch [2499]/[3760] Speed: 93.925339 samples/sec accuracy=98.486250 loss=0.069467 lr=0.000313 Epoch[088] Batch [2549]/[3760] Speed: 93.181682 samples/sec accuracy=98.484069 loss=0.069459 lr=0.000312 Epoch[088] Batch [2599]/[3760] Speed: 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lr=0.000305 Epoch[088] Batch [3099]/[3760] Speed: 94.240857 samples/sec accuracy=98.485383 loss=0.069468 lr=0.000304 Epoch[088] Batch [3149]/[3760] Speed: 95.191744 samples/sec accuracy=98.481151 loss=0.069562 lr=0.000303 Epoch[088] Batch [3199]/[3760] Speed: 92.695021 samples/sec accuracy=98.483887 loss=0.069578 lr=0.000303 Epoch[088] Batch [3249]/[3760] Speed: 94.128592 samples/sec accuracy=98.484135 loss=0.069531 lr=0.000302 Epoch[088] Batch [3299]/[3760] Speed: 92.905614 samples/sec accuracy=98.481534 loss=0.069624 lr=0.000301 Epoch[088] Batch [3349]/[3760] Speed: 94.279681 samples/sec accuracy=98.475280 loss=0.069829 lr=0.000301 Epoch[088] Batch [3399]/[3760] Speed: 94.006749 samples/sec accuracy=98.480699 loss=0.069681 lr=0.000300 Epoch[088] Batch [3449]/[3760] Speed: 93.438521 samples/sec accuracy=98.487772 loss=0.069587 lr=0.000299 Epoch[088] Batch [3499]/[3760] Speed: 94.359852 samples/sec accuracy=98.487946 loss=0.069577 lr=0.000298 Epoch[088] Batch [3549]/[3760] Speed: 93.476447 samples/sec accuracy=98.489877 loss=0.069633 lr=0.000298 Epoch[088] Batch [3599]/[3760] Speed: 94.086614 samples/sec accuracy=98.487847 loss=0.069694 lr=0.000297 Epoch[088] Batch [3649]/[3760] Speed: 93.180259 samples/sec accuracy=98.487586 loss=0.069714 lr=0.000296 Epoch[088] Batch [3699]/[3760] Speed: 93.028534 samples/sec accuracy=98.486486 loss=0.069827 lr=0.000296 Epoch[088] Batch [3749]/[3760] Speed: 105.979652 samples/sec accuracy=98.485000 loss=0.069831 lr=0.000295 Batch [0049]/[0303]: acc-top1=67.062500 acc-top5=85.656250 Batch [0099]/[0303]: acc-top1=64.937500 acc-top5=84.968750 Batch [0149]/[0303]: acc-top1=66.135417 acc-top5=85.968750 Batch [0199]/[0303]: acc-top1=68.921875 acc-top5=87.304688 Batch [0249]/[0303]: acc-top1=68.481250 acc-top5=86.787500 Batch [0299]/[0303]: acc-top1=68.140625 acc-top5=86.734375 [Epoch 088] training: accuracy=98.483211 loss=0.069889 [Epoch 088] speed: 93 samples/sec time cost: 2795.263837 [Epoch 088] validation: acc-top1=68.110561 acc-top5=86.690388 loss=2.395955 Epoch[089] Batch [0049]/[3760] Speed: 65.111062 samples/sec accuracy=98.468750 loss=0.066290 lr=0.000294 Epoch[089] Batch [0099]/[3760] Speed: 93.887496 samples/sec accuracy=98.515625 loss=0.064450 lr=0.000293 Epoch[089] Batch [0149]/[3760] Speed: 93.545574 samples/sec accuracy=98.489583 loss=0.066437 lr=0.000293 Epoch[089] Batch [0199]/[3760] Speed: 93.565825 samples/sec accuracy=98.460938 loss=0.068013 lr=0.000292 Epoch[089] Batch [0249]/[3760] Speed: 93.554305 samples/sec accuracy=98.437500 loss=0.067751 lr=0.000291 Epoch[089] Batch [0299]/[3760] Speed: 93.198367 samples/sec accuracy=98.437500 loss=0.067977 lr=0.000291 Epoch[089] Batch [0349]/[3760] Speed: 94.732576 samples/sec accuracy=98.433036 loss=0.068880 lr=0.000290 Epoch[089] Batch [0399]/[3760] Speed: 93.753323 samples/sec accuracy=98.441406 loss=0.069023 lr=0.000289 Epoch[089] Batch [0449]/[3760] Speed: 93.511495 samples/sec accuracy=98.451389 loss=0.068344 lr=0.000288 Epoch[089] Batch 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accuracy=98.519737 loss=0.066635 lr=0.000281 Epoch[089] Batch [0999]/[3760] Speed: 94.099819 samples/sec accuracy=98.529687 loss=0.066684 lr=0.000281 Epoch[089] Batch [1049]/[3760] Speed: 91.925337 samples/sec accuracy=98.531250 loss=0.066916 lr=0.000280 Epoch[089] Batch [1099]/[3760] Speed: 95.044440 samples/sec accuracy=98.528409 loss=0.067113 lr=0.000279 Epoch[089] Batch [1149]/[3760] Speed: 93.827695 samples/sec accuracy=98.521739 loss=0.067529 lr=0.000279 Epoch[089] Batch [1199]/[3760] Speed: 93.828176 samples/sec accuracy=98.511719 loss=0.067684 lr=0.000278 Epoch[089] Batch [1249]/[3760] Speed: 94.536388 samples/sec accuracy=98.507500 loss=0.067657 lr=0.000277 Epoch[089] Batch [1299]/[3760] Speed: 94.209213 samples/sec accuracy=98.516827 loss=0.067520 lr=0.000277 Epoch[089] Batch [1349]/[3760] Speed: 92.965704 samples/sec accuracy=98.504630 loss=0.067742 lr=0.000276 Epoch[089] Batch [1399]/[3760] Speed: 94.941092 samples/sec accuracy=98.487723 loss=0.068143 lr=0.000275 Epoch[089] 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accuracy=98.467654 loss=0.069327 lr=0.000256 Epoch[089] Batch [2899]/[3760] Speed: 95.464821 samples/sec accuracy=98.466595 loss=0.069322 lr=0.000255 Epoch[089] Batch [2949]/[3760] Speed: 93.881190 samples/sec accuracy=98.467691 loss=0.069241 lr=0.000254 Epoch[089] Batch [2999]/[3760] Speed: 93.254584 samples/sec accuracy=98.460417 loss=0.069348 lr=0.000254 Epoch[089] Batch [3049]/[3760] Speed: 93.710508 samples/sec accuracy=98.460041 loss=0.069337 lr=0.000253 Epoch[089] Batch [3099]/[3760] Speed: 93.114674 samples/sec accuracy=98.460685 loss=0.069384 lr=0.000253 Epoch[089] Batch [3149]/[3760] Speed: 92.936073 samples/sec accuracy=98.465278 loss=0.069310 lr=0.000252 Epoch[089] Batch [3199]/[3760] Speed: 93.678980 samples/sec accuracy=98.465820 loss=0.069324 lr=0.000251 Epoch[089] Batch [3249]/[3760] Speed: 93.913751 samples/sec accuracy=98.467308 loss=0.069279 lr=0.000251 Epoch[089] Batch [3299]/[3760] Speed: 93.849446 samples/sec accuracy=98.469697 loss=0.069217 lr=0.000250 Epoch[089] 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[0099]/[0303]: acc-top1=65.390625 acc-top5=85.062500 Batch [0149]/[0303]: acc-top1=66.458333 acc-top5=86.072917 Batch [0199]/[0303]: acc-top1=69.078125 acc-top5=87.335938 Batch [0249]/[0303]: acc-top1=68.700000 acc-top5=86.931250 Batch [0299]/[0303]: acc-top1=68.380208 acc-top5=86.895833 [Epoch 089] training: accuracy=98.464096 loss=0.069263 [Epoch 089] speed: 93 samples/sec time cost: 2794.856164 [Epoch 089] validation: acc-top1=68.332302 acc-top5=86.839934 loss=2.351320 Epoch[090] Batch [0049]/[3759] Speed: 64.740164 samples/sec accuracy=98.812500 loss=0.057743 lr=0.000243 Epoch[090] Batch [0099]/[3759] Speed: 94.155837 samples/sec accuracy=98.765625 loss=0.062042 lr=0.000243 Epoch[090] Batch [0149]/[3759] Speed: 93.404639 samples/sec accuracy=98.562500 loss=0.067370 lr=0.000242 Epoch[090] Batch [0199]/[3759] Speed: 94.796698 samples/sec accuracy=98.546875 loss=0.066961 lr=0.000241 Epoch[090] Batch [0249]/[3759] Speed: 93.275026 samples/sec accuracy=98.587500 loss=0.065832 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lr=0.000217 Epoch[090] Batch [2199]/[3759] Speed: 94.061974 samples/sec accuracy=98.539773 loss=0.066199 lr=0.000216 Epoch[090] Batch [2249]/[3759] Speed: 94.395743 samples/sec accuracy=98.538194 loss=0.066195 lr=0.000216 Epoch[090] Batch [2299]/[3759] Speed: 94.007485 samples/sec accuracy=98.529212 loss=0.066470 lr=0.000215 Epoch[090] Batch [2349]/[3759] Speed: 92.914002 samples/sec accuracy=98.536569 loss=0.066324 lr=0.000215 Epoch[090] Batch [2399]/[3759] Speed: 94.030577 samples/sec accuracy=98.534505 loss=0.066314 lr=0.000214 Epoch[090] Batch [2449]/[3759] Speed: 92.936353 samples/sec accuracy=98.529337 loss=0.066440 lr=0.000213 Epoch[090] Batch [2499]/[3759] Speed: 94.072842 samples/sec accuracy=98.533750 loss=0.066300 lr=0.000213 Epoch[090] Batch [2549]/[3759] Speed: 94.099691 samples/sec accuracy=98.528799 loss=0.066374 lr=0.000212 Epoch[090] Batch [2599]/[3759] Speed: 93.818863 samples/sec accuracy=98.531851 loss=0.066348 lr=0.000212 Epoch[090] Batch [2649]/[3759] Speed: 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lr=0.000206 Epoch[090] Batch [3149]/[3759] Speed: 93.860302 samples/sec accuracy=98.534226 loss=0.066508 lr=0.000205 Epoch[090] Batch [3199]/[3759] Speed: 93.468237 samples/sec accuracy=98.534668 loss=0.066505 lr=0.000204 Epoch[090] Batch [3249]/[3759] Speed: 93.213921 samples/sec accuracy=98.534135 loss=0.066550 lr=0.000204 Epoch[090] Batch [3299]/[3759] Speed: 93.867891 samples/sec accuracy=98.537405 loss=0.066481 lr=0.000203 Epoch[090] Batch [3349]/[3759] Speed: 92.181839 samples/sec accuracy=98.534981 loss=0.066592 lr=0.000203 Epoch[090] Batch [3399]/[3759] Speed: 95.712914 samples/sec accuracy=98.534926 loss=0.066601 lr=0.000202 Epoch[090] Batch [3449]/[3759] Speed: 94.478622 samples/sec accuracy=98.531250 loss=0.066740 lr=0.000201 Epoch[090] Batch [3499]/[3759] Speed: 92.684633 samples/sec accuracy=98.530357 loss=0.066696 lr=0.000201 Epoch[090] Batch [3549]/[3759] Speed: 94.065380 samples/sec accuracy=98.530370 loss=0.066735 lr=0.000200 Epoch[090] Batch [3599]/[3759] Speed: 94.384437 samples/sec accuracy=98.532552 loss=0.066694 lr=0.000200 Epoch[090] Batch [3649]/[3759] Speed: 92.882023 samples/sec accuracy=98.532534 loss=0.066675 lr=0.000199 Epoch[090] Batch [3699]/[3759] Speed: 94.305790 samples/sec accuracy=98.530828 loss=0.066673 lr=0.000199 Epoch[090] Batch [3749]/[3759] Speed: 104.423826 samples/sec accuracy=98.534583 loss=0.066616 lr=0.000198 Batch [0049]/[0303]: acc-top1=66.968750 acc-top5=85.593750 Batch [0099]/[0303]: acc-top1=65.062500 acc-top5=84.953125 Batch [0149]/[0303]: acc-top1=66.250000 acc-top5=85.927083 Batch [0199]/[0303]: acc-top1=68.992188 acc-top5=87.335938 Batch [0249]/[0303]: acc-top1=68.587500 acc-top5=86.781250 Batch [0299]/[0303]: acc-top1=68.286458 acc-top5=86.703125 [Epoch 090] training: accuracy=98.534767 loss=0.066599 [Epoch 090] speed: 93 samples/sec time cost: 2792.743413 [Epoch 090] validation: acc-top1=68.249794 acc-top5=86.659447 loss=2.367397 Epoch[091] Batch [0049]/[3760] Speed: 65.439364 samples/sec accuracy=98.625000 loss=0.066550 lr=0.000197 Epoch[091] Batch [0099]/[3760] Speed: 93.598902 samples/sec accuracy=98.718750 loss=0.063498 lr=0.000197 Epoch[091] Batch [0149]/[3760] Speed: 93.890580 samples/sec accuracy=98.718750 loss=0.063300 lr=0.000196 Epoch[091] Batch [0199]/[3760] Speed: 94.244309 samples/sec accuracy=98.625000 loss=0.064256 lr=0.000196 Epoch[091] Batch [0249]/[3760] Speed: 92.856197 samples/sec accuracy=98.531250 loss=0.066303 lr=0.000195 Epoch[091] Batch [0299]/[3760] Speed: 94.546592 samples/sec accuracy=98.510417 loss=0.067041 lr=0.000194 Epoch[091] Batch [0349]/[3760] Speed: 94.432384 samples/sec accuracy=98.517857 loss=0.067109 lr=0.000194 Epoch[091] Batch [0399]/[3760] Speed: 93.393767 samples/sec accuracy=98.519531 loss=0.067778 lr=0.000193 Epoch[091] Batch [0449]/[3760] Speed: 93.765781 samples/sec accuracy=98.545139 loss=0.066754 lr=0.000193 Epoch[091] Batch [0499]/[3760] Speed: 92.743551 samples/sec accuracy=98.559375 loss=0.066800 lr=0.000192 Epoch[091] 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accuracy=98.601293 loss=0.064542 lr=0.000165 Epoch[091] Batch [2949]/[3760] Speed: 93.983273 samples/sec accuracy=98.599576 loss=0.064527 lr=0.000165 Epoch[091] Batch [2999]/[3760] Speed: 92.998697 samples/sec accuracy=98.602604 loss=0.064460 lr=0.000164 Epoch[091] Batch [3049]/[3760] Speed: 94.406117 samples/sec accuracy=98.603484 loss=0.064461 lr=0.000164 Epoch[091] Batch [3099]/[3760] Speed: 93.611111 samples/sec accuracy=98.603831 loss=0.064446 lr=0.000163 Epoch[091] Batch [3149]/[3760] Speed: 93.004393 samples/sec accuracy=98.606151 loss=0.064408 lr=0.000163 Epoch[091] Batch [3199]/[3760] Speed: 94.354865 samples/sec accuracy=98.604980 loss=0.064396 lr=0.000162 Epoch[091] Batch [3249]/[3760] Speed: 92.267083 samples/sec accuracy=98.600481 loss=0.064481 lr=0.000162 Epoch[091] Batch [3299]/[3760] Speed: 94.062270 samples/sec accuracy=98.603220 loss=0.064418 lr=0.000161 Epoch[091] Batch [3349]/[3760] Speed: 94.223905 samples/sec accuracy=98.604478 loss=0.064394 lr=0.000161 Epoch[091] 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acc-top5=85.906250 Batch [0199]/[0303]: acc-top1=69.179688 acc-top5=87.375000 Batch [0249]/[0303]: acc-top1=68.806250 acc-top5=86.918750 Batch [0299]/[0303]: acc-top1=68.463542 acc-top5=86.937500 [Epoch 091] training: accuracy=98.610788 loss=0.064340 [Epoch 091] speed: 93 samples/sec time cost: 2793.298965 [Epoch 091] validation: acc-top1=68.435437 acc-top5=86.896658 loss=2.364724 Epoch[092] Batch [0049]/[3760] Speed: 63.896944 samples/sec accuracy=98.843750 loss=0.056366 lr=0.000156 Epoch[092] Batch [0099]/[3760] Speed: 94.635171 samples/sec accuracy=98.671875 loss=0.059485 lr=0.000155 Epoch[092] Batch [0149]/[3760] Speed: 93.234420 samples/sec accuracy=98.614583 loss=0.061321 lr=0.000155 Epoch[092] Batch [0199]/[3760] Speed: 94.275164 samples/sec accuracy=98.578125 loss=0.062298 lr=0.000154 Epoch[092] Batch [0249]/[3760] Speed: 94.449041 samples/sec accuracy=98.531250 loss=0.064031 lr=0.000154 Epoch[092] Batch [0299]/[3760] Speed: 93.476709 samples/sec accuracy=98.583333 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accuracy=98.649148 loss=0.063381 lr=0.000134 Epoch[092] Batch [2249]/[3760] Speed: 91.896994 samples/sec accuracy=98.647222 loss=0.063488 lr=0.000134 Epoch[092] Batch [2299]/[3760] Speed: 94.969370 samples/sec accuracy=98.644701 loss=0.063446 lr=0.000133 Epoch[092] Batch [2349]/[3760] Speed: 94.134686 samples/sec accuracy=98.646941 loss=0.063450 lr=0.000133 Epoch[092] Batch [2399]/[3760] Speed: 93.583302 samples/sec accuracy=98.652995 loss=0.063293 lr=0.000133 Epoch[092] Batch [2449]/[3760] Speed: 94.100631 samples/sec accuracy=98.655612 loss=0.063256 lr=0.000132 Epoch[092] Batch [2499]/[3760] Speed: 93.607889 samples/sec accuracy=98.655000 loss=0.063268 lr=0.000132 Epoch[092] Batch [2549]/[3760] Speed: 93.693212 samples/sec accuracy=98.660539 loss=0.063063 lr=0.000131 Epoch[092] Batch [2599]/[3760] Speed: 94.345930 samples/sec accuracy=98.659856 loss=0.063068 lr=0.000131 Epoch[092] Batch [2649]/[3760] Speed: 93.363777 samples/sec accuracy=98.666863 loss=0.062849 lr=0.000130 Epoch[092] 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accuracy=98.676587 loss=0.062673 lr=0.000125 Epoch[092] Batch [3199]/[3760] Speed: 93.637167 samples/sec accuracy=98.676270 loss=0.062730 lr=0.000125 Epoch[092] Batch [3249]/[3760] Speed: 94.159074 samples/sec accuracy=98.675000 loss=0.062743 lr=0.000125 Epoch[092] Batch [3299]/[3760] Speed: 93.261913 samples/sec accuracy=98.669981 loss=0.062784 lr=0.000124 Epoch[092] Batch [3349]/[3760] Speed: 92.968663 samples/sec accuracy=98.671642 loss=0.062754 lr=0.000124 Epoch[092] Batch [3399]/[3760] Speed: 93.524821 samples/sec accuracy=98.671415 loss=0.062783 lr=0.000123 Epoch[092] Batch [3449]/[3760] Speed: 92.864450 samples/sec accuracy=98.672554 loss=0.062789 lr=0.000123 Epoch[092] Batch [3499]/[3760] Speed: 94.147543 samples/sec accuracy=98.675000 loss=0.062796 lr=0.000122 Epoch[092] Batch [3549]/[3760] Speed: 93.568380 samples/sec accuracy=98.675616 loss=0.062717 lr=0.000122 Epoch[092] Batch [3599]/[3760] Speed: 93.874662 samples/sec accuracy=98.676215 loss=0.062641 lr=0.000121 Epoch[092] Batch [3649]/[3760] Speed: 94.413563 samples/sec accuracy=98.674229 loss=0.062767 lr=0.000121 Epoch[092] Batch [3699]/[3760] Speed: 91.781608 samples/sec accuracy=98.670608 loss=0.062871 lr=0.000120 Epoch[092] Batch [3749]/[3760] Speed: 107.732983 samples/sec accuracy=98.669583 loss=0.062851 lr=0.000120 Batch [0049]/[0303]: acc-top1=66.968750 acc-top5=86.187500 Batch [0099]/[0303]: acc-top1=65.046875 acc-top5=85.234375 Batch [0149]/[0303]: acc-top1=66.270833 acc-top5=86.208333 Batch [0199]/[0303]: acc-top1=69.109375 acc-top5=87.617188 Batch [0249]/[0303]: acc-top1=68.756250 acc-top5=87.150000 Batch [0299]/[0303]: acc-top1=68.458333 acc-top5=87.078125 [Epoch 092] training: accuracy=98.668135 loss=0.062891 [Epoch 092] speed: 93 samples/sec time cost: 2794.922753 [Epoch 092] validation: acc-top1=68.445751 acc-top5=87.046205 loss=2.367872 Epoch[093] Batch [0049]/[3759] Speed: 64.519391 samples/sec accuracy=98.500000 loss=0.070560 lr=0.000119 Epoch[093] Batch [0099]/[3759] Speed: 93.736701 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lr=0.000091 Epoch[093] Batch [3449]/[3759] Speed: 94.712342 samples/sec accuracy=98.682518 loss=0.062081 lr=0.000091 Epoch[093] Batch [3499]/[3759] Speed: 94.079478 samples/sec accuracy=98.684375 loss=0.061981 lr=0.000090 Epoch[093] Batch [3549]/[3759] Speed: 92.715805 samples/sec accuracy=98.683539 loss=0.062015 lr=0.000090 Epoch[093] Batch [3599]/[3759] Speed: 94.569661 samples/sec accuracy=98.684028 loss=0.062053 lr=0.000089 Epoch[093] Batch [3649]/[3759] Speed: 94.324392 samples/sec accuracy=98.680223 loss=0.062233 lr=0.000089 Epoch[093] Batch [3699]/[3759] Speed: 93.917504 samples/sec accuracy=98.685389 loss=0.062067 lr=0.000089 Epoch[093] Batch [3749]/[3759] Speed: 107.141082 samples/sec accuracy=98.685000 loss=0.062099 lr=0.000088 Batch [0049]/[0303]: acc-top1=66.843750 acc-top5=85.843750 Batch [0099]/[0303]: acc-top1=65.015625 acc-top5=85.078125 Batch [0149]/[0303]: acc-top1=66.333333 acc-top5=86.020833 Batch [0199]/[0303]: acc-top1=69.148438 acc-top5=87.375000 Batch [0249]/[0303]: acc-top1=68.806250 acc-top5=86.943750 Batch [0299]/[0303]: acc-top1=68.453125 acc-top5=86.875000 [Epoch 093] training: accuracy=98.683992 loss=0.062145 [Epoch 093] speed: 93 samples/sec time cost: 2792.095686 [Epoch 093] validation: acc-top1=68.435437 acc-top5=86.819307 loss=2.376438 Epoch[094] Batch [0049]/[3760] Speed: 64.748773 samples/sec accuracy=98.687500 loss=0.058925 lr=0.000088 Epoch[094] Batch [0099]/[3760] Speed: 94.411626 samples/sec accuracy=98.703125 loss=0.061484 lr=0.000087 Epoch[094] Batch [0149]/[3760] Speed: 94.399518 samples/sec accuracy=98.666667 loss=0.061752 lr=0.000087 Epoch[094] Batch [0199]/[3760] Speed: 93.018611 samples/sec accuracy=98.757812 loss=0.058553 lr=0.000087 Epoch[094] Batch [0249]/[3760] Speed: 94.500121 samples/sec accuracy=98.768750 loss=0.058458 lr=0.000086 Epoch[094] Batch [0299]/[3760] Speed: 94.037889 samples/sec accuracy=98.692708 loss=0.060287 lr=0.000086 Epoch[094] Batch [0349]/[3760] Speed: 93.077476 samples/sec accuracy=98.651786 loss=0.061686 lr=0.000085 Epoch[094] Batch [0399]/[3760] Speed: 94.085212 samples/sec accuracy=98.687500 loss=0.060816 lr=0.000085 Epoch[094] Batch [0449]/[3760] Speed: 93.246705 samples/sec accuracy=98.673611 loss=0.061123 lr=0.000085 Epoch[094] Batch [0499]/[3760] Speed: 94.525419 samples/sec accuracy=98.681250 loss=0.061340 lr=0.000084 Epoch[094] Batch [0549]/[3760] Speed: 93.703680 samples/sec accuracy=98.681818 loss=0.061214 lr=0.000084 Epoch[094] Batch [0599]/[3760] Speed: 93.453686 samples/sec accuracy=98.695312 loss=0.061329 lr=0.000083 Epoch[094] Batch [0649]/[3760] Speed: 94.332898 samples/sec accuracy=98.689904 loss=0.061317 lr=0.000083 Epoch[094] Batch [0699]/[3760] Speed: 94.187598 samples/sec accuracy=98.718750 loss=0.060643 lr=0.000083 Epoch[094] Batch [0749]/[3760] Speed: 92.796942 samples/sec accuracy=98.720833 loss=0.060917 lr=0.000082 Epoch[094] Batch [0799]/[3760] Speed: 93.647099 samples/sec accuracy=98.726562 loss=0.060860 lr=0.000082 Epoch[094] 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accuracy=98.705529 loss=0.061392 lr=0.000078 Epoch[094] Batch [1349]/[3760] Speed: 93.659506 samples/sec accuracy=98.701389 loss=0.061600 lr=0.000078 Epoch[094] Batch [1399]/[3760] Speed: 94.048764 samples/sec accuracy=98.697545 loss=0.061739 lr=0.000077 Epoch[094] Batch [1449]/[3760] Speed: 93.515532 samples/sec accuracy=98.703664 loss=0.061670 lr=0.000077 Epoch[094] Batch [1499]/[3760] Speed: 93.748164 samples/sec accuracy=98.691667 loss=0.062102 lr=0.000077 Epoch[094] Batch [1549]/[3760] Speed: 93.027715 samples/sec accuracy=98.685484 loss=0.062237 lr=0.000076 Epoch[094] Batch [1599]/[3760] Speed: 93.975206 samples/sec accuracy=98.679688 loss=0.062481 lr=0.000076 Epoch[094] Batch [1649]/[3760] Speed: 91.446343 samples/sec accuracy=98.681818 loss=0.062391 lr=0.000076 Epoch[094] Batch [1699]/[3760] Speed: 95.696512 samples/sec accuracy=98.686581 loss=0.062302 lr=0.000075 Epoch[094] Batch [1749]/[3760] Speed: 93.826245 samples/sec accuracy=98.691071 loss=0.062208 lr=0.000075 Epoch[094] 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accuracy=98.682639 loss=0.062154 lr=0.000071 Epoch[094] Batch [2299]/[3760] Speed: 93.554359 samples/sec accuracy=98.688859 loss=0.062009 lr=0.000071 Epoch[094] Batch [2349]/[3760] Speed: 92.750313 samples/sec accuracy=98.691489 loss=0.061977 lr=0.000071 Epoch[094] Batch [2399]/[3760] Speed: 94.379332 samples/sec accuracy=98.696615 loss=0.061783 lr=0.000070 Epoch[094] Batch [2449]/[3760] Speed: 93.770403 samples/sec accuracy=98.695791 loss=0.061828 lr=0.000070 Epoch[094] Batch [2499]/[3760] Speed: 92.923924 samples/sec accuracy=98.694375 loss=0.061726 lr=0.000070 Epoch[094] Batch [2549]/[3760] Speed: 93.635816 samples/sec accuracy=98.695466 loss=0.061648 lr=0.000069 Epoch[094] Batch [2599]/[3760] Speed: 92.728569 samples/sec accuracy=98.695312 loss=0.061609 lr=0.000069 Epoch[094] Batch [2649]/[3760] Speed: 95.737179 samples/sec accuracy=98.695755 loss=0.061550 lr=0.000069 Epoch[094] Batch [2699]/[3760] Speed: 94.010455 samples/sec accuracy=98.697917 loss=0.061538 lr=0.000068 Epoch[094] Batch [2749]/[3760] Speed: 93.124736 samples/sec accuracy=98.696023 loss=0.061465 lr=0.000068 Epoch[094] Batch [2799]/[3760] Speed: 93.983658 samples/sec accuracy=98.695312 loss=0.061392 lr=0.000068 Epoch[094] Batch [2849]/[3760] Speed: 94.166577 samples/sec accuracy=98.696272 loss=0.061437 lr=0.000067 Epoch[094] Batch [2899]/[3760] Speed: 92.933639 samples/sec accuracy=98.695043 loss=0.061572 lr=0.000067 Epoch[094] Batch [2949]/[3760] Speed: 93.669028 samples/sec accuracy=98.694915 loss=0.061630 lr=0.000067 Epoch[094] Batch [2999]/[3760] Speed: 91.757099 samples/sec accuracy=98.696354 loss=0.061593 lr=0.000066 Epoch[094] Batch [3049]/[3760] Speed: 95.001278 samples/sec accuracy=98.692111 loss=0.061602 lr=0.000066 Epoch[094] Batch [3099]/[3760] Speed: 94.189392 samples/sec accuracy=98.691532 loss=0.061644 lr=0.000066 Epoch[094] Batch [3149]/[3760] Speed: 92.655045 samples/sec accuracy=98.693948 loss=0.061557 lr=0.000065 Epoch[094] Batch [3199]/[3760] Speed: 94.242930 samples/sec accuracy=98.698730 loss=0.061412 lr=0.000065 Epoch[094] Batch [3249]/[3760] Speed: 93.627423 samples/sec accuracy=98.695192 loss=0.061559 lr=0.000065 Epoch[094] Batch [3299]/[3760] Speed: 93.398157 samples/sec accuracy=98.692708 loss=0.061688 lr=0.000064 Epoch[094] Batch [3349]/[3760] Speed: 93.674456 samples/sec accuracy=98.694496 loss=0.061609 lr=0.000064 Epoch[094] Batch [3399]/[3760] Speed: 95.119364 samples/sec accuracy=98.696232 loss=0.061577 lr=0.000064 Epoch[094] Batch [3449]/[3760] Speed: 93.524505 samples/sec accuracy=98.693841 loss=0.061625 lr=0.000063 Epoch[094] Batch [3499]/[3760] Speed: 93.731565 samples/sec accuracy=98.695982 loss=0.061549 lr=0.000063 Epoch[094] Batch [3549]/[3760] Speed: 92.325474 samples/sec accuracy=98.691901 loss=0.061674 lr=0.000063 Epoch[094] Batch [3599]/[3760] Speed: 94.277098 samples/sec accuracy=98.697917 loss=0.061486 lr=0.000062 Epoch[094] Batch [3649]/[3760] Speed: 94.258441 samples/sec accuracy=98.696918 loss=0.061469 lr=0.000062 Epoch[094] Batch [3699]/[3760] Speed: 93.324395 samples/sec accuracy=98.696791 loss=0.061414 lr=0.000062 Epoch[094] Batch [3749]/[3760] Speed: 105.679513 samples/sec accuracy=98.697083 loss=0.061466 lr=0.000061 Batch [0049]/[0303]: acc-top1=66.843750 acc-top5=85.875000 Batch [0099]/[0303]: acc-top1=65.281250 acc-top5=85.062500 Batch [0149]/[0303]: acc-top1=66.416667 acc-top5=86.093750 Batch [0199]/[0303]: acc-top1=69.109375 acc-top5=87.476562 Batch [0249]/[0303]: acc-top1=68.600000 acc-top5=86.993750 Batch [0299]/[0303]: acc-top1=68.348958 acc-top5=86.979167 [Epoch 094] training: accuracy=98.695562 loss=0.061480 [Epoch 094] speed: 93 samples/sec time cost: 2794.184471 [Epoch 094] validation: acc-top1=68.316832 acc-top5=86.922442 loss=2.376122 Epoch[095] Batch [0049]/[3760] Speed: 63.845164 samples/sec accuracy=98.500000 loss=0.069639 lr=0.000061 Epoch[095] Batch [0099]/[3760] Speed: 96.169371 samples/sec accuracy=98.703125 loss=0.065918 lr=0.000060 Epoch[095] Batch [0149]/[3760] Speed: 93.658228 samples/sec accuracy=98.718750 loss=0.061805 lr=0.000060 Epoch[095] Batch [0199]/[3760] Speed: 92.921967 samples/sec accuracy=98.648438 loss=0.062624 lr=0.000060 Epoch[095] Batch [0249]/[3760] Speed: 94.798894 samples/sec accuracy=98.587500 loss=0.063288 lr=0.000060 Epoch[095] Batch [0299]/[3760] Speed: 94.368947 samples/sec accuracy=98.614583 loss=0.062684 lr=0.000059 Epoch[095] Batch [0349]/[3760] Speed: 93.806679 samples/sec accuracy=98.678571 loss=0.061291 lr=0.000059 Epoch[095] Batch [0399]/[3760] Speed: 93.487295 samples/sec accuracy=98.679688 loss=0.061552 lr=0.000059 Epoch[095] Batch [0449]/[3760] Speed: 94.275413 samples/sec accuracy=98.673611 loss=0.061975 lr=0.000058 Epoch[095] Batch [0499]/[3760] Speed: 93.487538 samples/sec accuracy=98.668750 loss=0.062565 lr=0.000058 Epoch[095] Batch [0549]/[3760] Speed: 93.804274 samples/sec accuracy=98.653409 loss=0.062669 lr=0.000058 Epoch[095] Batch [0599]/[3760] Speed: 92.751990 samples/sec accuracy=98.653646 loss=0.062668 lr=0.000057 Epoch[095] Batch [0649]/[3760] Speed: 93.699742 samples/sec accuracy=98.692308 loss=0.062133 lr=0.000057 Epoch[095] Batch [0699]/[3760] Speed: 93.881126 samples/sec accuracy=98.705357 loss=0.061550 lr=0.000057 Epoch[095] Batch [0749]/[3760] Speed: 93.021238 samples/sec accuracy=98.695833 loss=0.061653 lr=0.000056 Epoch[095] Batch [0799]/[3760] Speed: 94.221681 samples/sec accuracy=98.695312 loss=0.061742 lr=0.000056 Epoch[095] Batch [0849]/[3760] Speed: 93.867711 samples/sec accuracy=98.702206 loss=0.061793 lr=0.000056 Epoch[095] Batch [0899]/[3760] Speed: 93.208536 samples/sec accuracy=98.696181 loss=0.061686 lr=0.000055 Epoch[095] Batch [0949]/[3760] Speed: 93.600488 samples/sec accuracy=98.687500 loss=0.062004 lr=0.000055 Epoch[095] Batch [0999]/[3760] Speed: 92.179783 samples/sec accuracy=98.681250 loss=0.061950 lr=0.000055 Epoch[095] Batch [1049]/[3760] Speed: 95.036505 samples/sec accuracy=98.677083 loss=0.062079 lr=0.000054 Epoch[095] Batch [1099]/[3760] Speed: 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93.841045 samples/sec accuracy=98.714939 loss=0.061871 lr=0.000049 Epoch[095] Batch [2099]/[3760] Speed: 93.104456 samples/sec accuracy=98.712054 loss=0.061902 lr=0.000048 Epoch[095] Batch [2149]/[3760] Speed: 94.268379 samples/sec accuracy=98.712209 loss=0.061951 lr=0.000048 Epoch[095] Batch [2199]/[3760] Speed: 93.193670 samples/sec accuracy=98.709517 loss=0.061924 lr=0.000048 Epoch[095] Batch [2249]/[3760] Speed: 93.098988 samples/sec accuracy=98.708333 loss=0.061814 lr=0.000047 Epoch[095] Batch [2299]/[3760] Speed: 93.883827 samples/sec accuracy=98.700408 loss=0.061984 lr=0.000047 Epoch[095] Batch [2349]/[3760] Speed: 94.855685 samples/sec accuracy=98.702128 loss=0.062040 lr=0.000047 Epoch[095] Batch [2399]/[3760] Speed: 93.487153 samples/sec accuracy=98.703125 loss=0.061967 lr=0.000047 Epoch[095] Batch [2449]/[3760] Speed: 94.212024 samples/sec accuracy=98.700893 loss=0.062095 lr=0.000046 Epoch[095] Batch [2499]/[3760] Speed: 93.421380 samples/sec accuracy=98.695000 loss=0.062204 lr=0.000046 Epoch[095] Batch [2549]/[3760] Speed: 94.555797 samples/sec accuracy=98.693627 loss=0.062270 lr=0.000046 Epoch[095] Batch [2599]/[3760] Speed: 93.195960 samples/sec accuracy=98.694111 loss=0.062247 lr=0.000045 Epoch[095] Batch [2649]/[3760] Speed: 93.345756 samples/sec accuracy=98.695165 loss=0.062291 lr=0.000045 Epoch[095] Batch [2699]/[3760] Speed: 94.156666 samples/sec accuracy=98.695602 loss=0.062161 lr=0.000045 Epoch[095] Batch [2749]/[3760] Speed: 94.002996 samples/sec accuracy=98.693182 loss=0.062303 lr=0.000045 Epoch[095] Batch [2799]/[3760] Speed: 92.880696 samples/sec accuracy=98.696429 loss=0.062195 lr=0.000044 Epoch[095] Batch [2849]/[3760] Speed: 94.155932 samples/sec accuracy=98.697917 loss=0.062102 lr=0.000044 Epoch[095] Batch [2899]/[3760] Speed: 91.557660 samples/sec accuracy=98.693966 loss=0.062103 lr=0.000044 Epoch[095] Batch [2949]/[3760] Speed: 95.703988 samples/sec accuracy=98.691737 loss=0.062215 lr=0.000043 Epoch[095] Batch [2999]/[3760] Speed: 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lr=0.000041 Epoch[095] Batch [3499]/[3760] Speed: 94.480906 samples/sec accuracy=98.690625 loss=0.062076 lr=0.000040 Epoch[095] Batch [3549]/[3760] Speed: 93.970073 samples/sec accuracy=98.695423 loss=0.062034 lr=0.000040 Epoch[095] Batch [3599]/[3760] Speed: 92.622873 samples/sec accuracy=98.692274 loss=0.062179 lr=0.000040 Epoch[095] Batch [3649]/[3760] Speed: 93.654585 samples/sec accuracy=98.694349 loss=0.062162 lr=0.000040 Epoch[095] Batch [3699]/[3760] Speed: 93.774799 samples/sec accuracy=98.693834 loss=0.062174 lr=0.000039 Epoch[095] Batch [3749]/[3760] Speed: 104.535122 samples/sec accuracy=98.695833 loss=0.062066 lr=0.000039 Batch [0049]/[0303]: acc-top1=66.625000 acc-top5=85.750000 Batch [0099]/[0303]: acc-top1=65.078125 acc-top5=84.906250 Batch [0149]/[0303]: acc-top1=66.447917 acc-top5=86.000000 Batch [0199]/[0303]: acc-top1=69.156250 acc-top5=87.437500 Batch [0249]/[0303]: acc-top1=68.750000 acc-top5=86.937500 Batch [0299]/[0303]: acc-top1=68.421875 acc-top5=86.906250 [Epoch 095] training: accuracy=98.696809 loss=0.062011 [Epoch 095] speed: 93 samples/sec time cost: 2796.150223 [Epoch 095] validation: acc-top1=68.389026 acc-top5=86.850248 loss=2.371251 Epoch[096] Batch [0049]/[3759] Speed: 64.678664 samples/sec accuracy=98.937500 loss=0.056805 lr=0.000039 Epoch[096] Batch [0099]/[3759] Speed: 91.564385 samples/sec accuracy=98.921875 loss=0.057598 lr=0.000039 Epoch[096] Batch [0149]/[3759] Speed: 94.741318 samples/sec accuracy=98.958333 loss=0.056922 lr=0.000038 Epoch[096] Batch [0199]/[3759] Speed: 93.880770 samples/sec accuracy=98.875000 loss=0.058444 lr=0.000038 Epoch[096] Batch [0249]/[3759] Speed: 93.575466 samples/sec accuracy=98.818750 loss=0.058455 lr=0.000038 Epoch[096] Batch [0299]/[3759] Speed: 93.978726 samples/sec accuracy=98.786458 loss=0.058566 lr=0.000038 Epoch[096] Batch [0349]/[3759] Speed: 93.583848 samples/sec accuracy=98.808036 loss=0.057640 lr=0.000037 Epoch[096] Batch [0399]/[3759] Speed: 93.637240 samples/sec accuracy=98.742188 loss=0.058884 lr=0.000037 Epoch[096] Batch [0449]/[3759] Speed: 93.920989 samples/sec accuracy=98.711806 loss=0.058801 lr=0.000037 Epoch[096] Batch [0499]/[3759] Speed: 94.045866 samples/sec accuracy=98.712500 loss=0.058366 lr=0.000037 Epoch[096] Batch [0549]/[3759] Speed: 93.195381 samples/sec accuracy=98.710227 loss=0.058266 lr=0.000036 Epoch[096] Batch [0599]/[3759] Speed: 93.688274 samples/sec accuracy=98.700521 loss=0.058034 lr=0.000036 Epoch[096] Batch [0649]/[3759] Speed: 91.987376 samples/sec accuracy=98.701923 loss=0.058002 lr=0.000036 Epoch[096] Batch [0699]/[3759] Speed: 94.696847 samples/sec accuracy=98.689732 loss=0.058534 lr=0.000036 Epoch[096] Batch [0749]/[3759] Speed: 93.940495 samples/sec accuracy=98.708333 loss=0.057873 lr=0.000035 Epoch[096] Batch [0799]/[3759] Speed: 93.285428 samples/sec accuracy=98.695312 loss=0.058335 lr=0.000035 Epoch[096] Batch [0849]/[3759] Speed: 93.874284 samples/sec accuracy=98.693015 loss=0.058565 lr=0.000035 Epoch[096] 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accuracy=98.710648 loss=0.059111 lr=0.000032 Epoch[096] Batch [1399]/[3759] Speed: 94.020722 samples/sec accuracy=98.717634 loss=0.058928 lr=0.000032 Epoch[096] Batch [1449]/[3759] Speed: 94.447817 samples/sec accuracy=98.716595 loss=0.059101 lr=0.000032 Epoch[096] Batch [1499]/[3759] Speed: 93.160553 samples/sec accuracy=98.712500 loss=0.059073 lr=0.000032 Epoch[096] Batch [1549]/[3759] Speed: 94.275193 samples/sec accuracy=98.711694 loss=0.059294 lr=0.000031 Epoch[096] Batch [1599]/[3759] Speed: 94.202127 samples/sec accuracy=98.709961 loss=0.059479 lr=0.000031 Epoch[096] Batch [1649]/[3759] Speed: 93.656225 samples/sec accuracy=98.708333 loss=0.059757 lr=0.000031 Epoch[096] Batch [1699]/[3759] Speed: 93.230016 samples/sec accuracy=98.711397 loss=0.059680 lr=0.000031 Epoch[096] Batch [1749]/[3759] Speed: 92.446644 samples/sec accuracy=98.707143 loss=0.059939 lr=0.000030 Epoch[096] Batch [1799]/[3759] Speed: 95.063177 samples/sec accuracy=98.702257 loss=0.060048 lr=0.000030 Epoch[096] 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accuracy=98.697690 loss=0.060226 lr=0.000028 Epoch[096] Batch [2349]/[3759] Speed: 94.295196 samples/sec accuracy=98.695479 loss=0.060223 lr=0.000028 Epoch[096] Batch [2399]/[3759] Speed: 94.052908 samples/sec accuracy=98.699219 loss=0.060209 lr=0.000028 Epoch[096] Batch [2449]/[3759] Speed: 93.179746 samples/sec accuracy=98.702806 loss=0.060185 lr=0.000027 Epoch[096] Batch [2499]/[3759] Speed: 93.345327 samples/sec accuracy=98.707500 loss=0.060079 lr=0.000027 Epoch[096] Batch [2549]/[3759] Speed: 94.216550 samples/sec accuracy=98.711397 loss=0.060036 lr=0.000027 Epoch[096] Batch [2599]/[3759] Speed: 93.231636 samples/sec accuracy=98.705529 loss=0.060192 lr=0.000027 Epoch[096] Batch [2649]/[3759] Speed: 94.081185 samples/sec accuracy=98.707547 loss=0.060162 lr=0.000026 Epoch[096] Batch [2699]/[3759] Speed: 92.174710 samples/sec accuracy=98.710648 loss=0.060125 lr=0.000026 Epoch[096] Batch [2749]/[3759] Speed: 95.192898 samples/sec accuracy=98.711932 loss=0.060099 lr=0.000026 Epoch[096] Batch [2799]/[3759] Speed: 93.888860 samples/sec accuracy=98.714286 loss=0.059999 lr=0.000026 Epoch[096] Batch [2849]/[3759] Speed: 93.480214 samples/sec accuracy=98.721491 loss=0.059858 lr=0.000026 Epoch[096] Batch [2899]/[3759] Speed: 93.981507 samples/sec accuracy=98.719828 loss=0.059903 lr=0.000025 Epoch[096] Batch [2949]/[3759] Speed: 94.620063 samples/sec accuracy=98.715042 loss=0.060022 lr=0.000025 Epoch[096] Batch [2999]/[3759] Speed: 93.377743 samples/sec accuracy=98.718750 loss=0.060022 lr=0.000025 Epoch[096] Batch [3049]/[3759] Speed: 94.262707 samples/sec accuracy=98.718238 loss=0.060059 lr=0.000025 Epoch[096] Batch [3099]/[3759] Speed: 93.499329 samples/sec accuracy=98.717742 loss=0.059929 lr=0.000025 Epoch[096] Batch [3149]/[3759] Speed: 93.434375 samples/sec accuracy=98.720734 loss=0.060000 lr=0.000024 Epoch[096] Batch [3199]/[3759] Speed: 93.922345 samples/sec accuracy=98.719238 loss=0.059992 lr=0.000024 Epoch[096] Batch [3249]/[3759] Speed: 91.774570 samples/sec accuracy=98.719712 loss=0.060003 lr=0.000024 Epoch[096] Batch [3299]/[3759] Speed: 95.412507 samples/sec accuracy=98.719697 loss=0.059944 lr=0.000024 Epoch[096] Batch [3349]/[3759] Speed: 93.724414 samples/sec accuracy=98.716884 loss=0.060033 lr=0.000024 Epoch[096] Batch [3399]/[3759] Speed: 93.304306 samples/sec accuracy=98.717831 loss=0.060046 lr=0.000023 Epoch[096] Batch [3449]/[3759] Speed: 94.359915 samples/sec accuracy=98.718750 loss=0.060015 lr=0.000023 Epoch[096] Batch [3499]/[3759] Speed: 93.958886 samples/sec accuracy=98.718750 loss=0.059919 lr=0.000023 Epoch[096] Batch [3549]/[3759] Speed: 92.836569 samples/sec accuracy=98.718750 loss=0.059824 lr=0.000023 Epoch[096] Batch [3599]/[3759] Speed: 93.585790 samples/sec accuracy=98.717014 loss=0.059818 lr=0.000023 Epoch[096] Batch [3649]/[3759] Speed: 93.929284 samples/sec accuracy=98.716182 loss=0.059902 lr=0.000022 Epoch[096] Batch [3699]/[3759] Speed: 93.379345 samples/sec accuracy=98.714949 loss=0.059964 lr=0.000022 Epoch[096] Batch [3749]/[3759] Speed: 106.889001 samples/sec accuracy=98.713333 loss=0.059931 lr=0.000022 Batch [0049]/[0303]: acc-top1=67.156250 acc-top5=85.750000 Batch [0099]/[0303]: acc-top1=65.156250 acc-top5=85.093750 Batch [0149]/[0303]: acc-top1=66.375000 acc-top5=86.052083 Batch [0199]/[0303]: acc-top1=69.179688 acc-top5=87.437500 Batch [0249]/[0303]: acc-top1=68.762500 acc-top5=86.956250 Batch [0299]/[0303]: acc-top1=68.447917 acc-top5=86.916667 [Epoch 096] training: accuracy=98.713504 loss=0.059927 [Epoch 096] speed: 93 samples/sec time cost: 2795.429117 [Epoch 096] validation: acc-top1=68.425124 acc-top5=86.881188 loss=2.373649 Epoch[097] Batch [0049]/[3760] Speed: 64.316915 samples/sec accuracy=99.000000 loss=0.056122 lr=0.000022 Epoch[097] Batch [0099]/[3760] Speed: 94.562665 samples/sec accuracy=98.890625 loss=0.060933 lr=0.000022 Epoch[097] Batch [0149]/[3760] Speed: 93.650568 samples/sec accuracy=98.843750 loss=0.058980 lr=0.000021 Epoch[097] Batch [0199]/[3760] Speed: 93.142642 samples/sec accuracy=98.687500 loss=0.060644 lr=0.000021 Epoch[097] Batch [0249]/[3760] Speed: 93.841442 samples/sec accuracy=98.731250 loss=0.060680 lr=0.000021 Epoch[097] Batch [0299]/[3760] Speed: 93.779899 samples/sec accuracy=98.739583 loss=0.059682 lr=0.000021 Epoch[097] Batch [0349]/[3760] Speed: 92.706972 samples/sec accuracy=98.727679 loss=0.059154 lr=0.000021 Epoch[097] Batch [0399]/[3760] Speed: 94.224134 samples/sec accuracy=98.714844 loss=0.058924 lr=0.000020 Epoch[097] Batch [0449]/[3760] Speed: 91.756667 samples/sec accuracy=98.670139 loss=0.059827 lr=0.000020 Epoch[097] Batch [0499]/[3760] Speed: 95.537464 samples/sec accuracy=98.700000 loss=0.059340 lr=0.000020 Epoch[097] Batch [0549]/[3760] Speed: 94.377510 samples/sec accuracy=98.710227 loss=0.058967 lr=0.000020 Epoch[097] Batch [0599]/[3760] Speed: 93.415422 samples/sec accuracy=98.713542 loss=0.059047 lr=0.000020 Epoch[097] Batch [0649]/[3760] Speed: 94.964930 samples/sec accuracy=98.750000 loss=0.057964 lr=0.000019 Epoch[097] Batch [0699]/[3760] Speed: 94.235317 samples/sec accuracy=98.765625 loss=0.057663 lr=0.000019 Epoch[097] Batch [0749]/[3760] Speed: 93.942233 samples/sec accuracy=98.785417 loss=0.056832 lr=0.000019 Epoch[097] Batch [0799]/[3760] Speed: 93.755269 samples/sec accuracy=98.755859 loss=0.057699 lr=0.000019 Epoch[097] Batch [0849]/[3760] Speed: 94.308470 samples/sec accuracy=98.761029 loss=0.057470 lr=0.000019 Epoch[097] Batch [0899]/[3760] Speed: 93.318013 samples/sec accuracy=98.753472 loss=0.057739 lr=0.000019 Epoch[097] Batch [0949]/[3760] Speed: 94.054368 samples/sec accuracy=98.745066 loss=0.057981 lr=0.000018 Epoch[097] Batch [0999]/[3760] Speed: 91.503003 samples/sec accuracy=98.754688 loss=0.057819 lr=0.000018 Epoch[097] Batch [1049]/[3760] Speed: 95.054660 samples/sec accuracy=98.738095 loss=0.058105 lr=0.000018 Epoch[097] Batch [1099]/[3760] Speed: 94.901190 samples/sec accuracy=98.741477 loss=0.058189 lr=0.000018 Epoch[097] Batch [1149]/[3760] Speed: 92.615039 samples/sec accuracy=98.737772 loss=0.058208 lr=0.000018 Epoch[097] Batch [1199]/[3760] Speed: 93.822536 samples/sec accuracy=98.746094 loss=0.058255 lr=0.000017 Epoch[097] Batch [1249]/[3760] Speed: 93.737984 samples/sec accuracy=98.752500 loss=0.058105 lr=0.000017 Epoch[097] Batch [1299]/[3760] Speed: 93.123549 samples/sec accuracy=98.760817 loss=0.057869 lr=0.000017 Epoch[097] Batch [1349]/[3760] Speed: 93.070422 samples/sec accuracy=98.767361 loss=0.057835 lr=0.000017 Epoch[097] Batch [1399]/[3760] Speed: 93.855731 samples/sec accuracy=98.771205 loss=0.057775 lr=0.000017 Epoch[097] Batch [1449]/[3760] Speed: 93.448135 samples/sec accuracy=98.767241 loss=0.057923 lr=0.000017 Epoch[097] Batch [1499]/[3760] Speed: 94.754021 samples/sec accuracy=98.761458 loss=0.057986 lr=0.000016 Epoch[097] Batch [1549]/[3760] Speed: 94.528338 samples/sec accuracy=98.762097 loss=0.058088 lr=0.000016 Epoch[097] Batch [1599]/[3760] Speed: 93.446737 samples/sec accuracy=98.760742 loss=0.058047 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lr=0.000010 Epoch[097] Batch [3549]/[3760] Speed: 95.124179 samples/sec accuracy=98.750000 loss=0.059192 lr=0.000010 Epoch[097] Batch [3599]/[3760] Speed: 93.853035 samples/sec accuracy=98.750000 loss=0.059138 lr=0.000010 Epoch[097] Batch [3649]/[3760] Speed: 93.037258 samples/sec accuracy=98.746147 loss=0.059294 lr=0.000010 Epoch[097] Batch [3699]/[3760] Speed: 94.608823 samples/sec accuracy=98.747044 loss=0.059303 lr=0.000010 Epoch[097] Batch [3749]/[3760] Speed: 106.413616 samples/sec accuracy=98.748750 loss=0.059295 lr=0.000010 Batch [0049]/[0303]: acc-top1=67.031250 acc-top5=85.937500 Batch [0099]/[0303]: acc-top1=65.234375 acc-top5=85.203125 Batch [0149]/[0303]: acc-top1=66.479167 acc-top5=86.104167 Batch [0199]/[0303]: acc-top1=69.148438 acc-top5=87.500000 Batch [0249]/[0303]: acc-top1=68.750000 acc-top5=86.981250 Batch [0299]/[0303]: acc-top1=68.458333 acc-top5=86.890625 [Epoch 097] training: accuracy=98.747922 loss=0.059297 [Epoch 097] speed: 93 samples/sec time cost: 2795.063166 [Epoch 097] validation: acc-top1=68.430281 acc-top5=86.839934 loss=2.357987 Epoch[098] Batch [0049]/[3759] Speed: 64.321765 samples/sec accuracy=98.531250 loss=0.063436 lr=0.000010 Epoch[098] Batch [0099]/[3759] Speed: 94.198226 samples/sec accuracy=98.578125 loss=0.064304 lr=0.000009 Epoch[098] Batch [0149]/[3759] Speed: 91.279376 samples/sec accuracy=98.656250 loss=0.062087 lr=0.000009 Epoch[098] Batch [0199]/[3759] Speed: 95.907449 samples/sec accuracy=98.679688 loss=0.061104 lr=0.000009 Epoch[098] Batch [0249]/[3759] Speed: 94.180348 samples/sec accuracy=98.737500 loss=0.059522 lr=0.000009 Epoch[098] Batch [0299]/[3759] Speed: 92.735048 samples/sec accuracy=98.796875 loss=0.058337 lr=0.000009 Epoch[098] Batch [0349]/[3759] Speed: 94.636148 samples/sec accuracy=98.767857 loss=0.058584 lr=0.000009 Epoch[098] Batch [0399]/[3759] Speed: 94.372360 samples/sec accuracy=98.757812 loss=0.058586 lr=0.000009 Epoch[098] Batch [0449]/[3759] Speed: 93.416565 samples/sec 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accuracy=98.705357 loss=0.061113 lr=0.000006 Epoch[098] Batch [1449]/[3759] Speed: 95.438427 samples/sec accuracy=98.703664 loss=0.060933 lr=0.000006 Epoch[098] Batch [1499]/[3759] Speed: 93.537569 samples/sec accuracy=98.711458 loss=0.060790 lr=0.000006 Epoch[098] Batch [1549]/[3759] Speed: 93.120128 samples/sec accuracy=98.707661 loss=0.060841 lr=0.000006 Epoch[098] Batch [1599]/[3759] Speed: 93.851459 samples/sec accuracy=98.706055 loss=0.060827 lr=0.000006 Epoch[098] Batch [1649]/[3759] Speed: 94.797440 samples/sec accuracy=98.713068 loss=0.060684 lr=0.000006 Epoch[098] Batch [1699]/[3759] Speed: 92.708557 samples/sec accuracy=98.708640 loss=0.060815 lr=0.000006 Epoch[098] Batch [1749]/[3759] Speed: 94.108175 samples/sec accuracy=98.707143 loss=0.060717 lr=0.000006 Epoch[098] Batch [1799]/[3759] Speed: 93.958293 samples/sec accuracy=98.701389 loss=0.060974 lr=0.000006 Epoch[098] Batch [1849]/[3759] Speed: 91.947927 samples/sec accuracy=98.695101 loss=0.061216 lr=0.000005 Epoch[098] 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accuracy=98.717420 loss=0.060417 lr=0.000005 Epoch[098] Batch [2399]/[3759] Speed: 93.770440 samples/sec accuracy=98.711589 loss=0.060502 lr=0.000004 Epoch[098] Batch [2449]/[3759] Speed: 93.604119 samples/sec accuracy=98.711735 loss=0.060322 lr=0.000004 Epoch[098] Batch [2499]/[3759] Speed: 94.116161 samples/sec accuracy=98.715625 loss=0.060255 lr=0.000004 Epoch[098] Batch [2549]/[3759] Speed: 93.532434 samples/sec accuracy=98.720588 loss=0.060167 lr=0.000004 Epoch[098] Batch [2599]/[3759] Speed: 93.997920 samples/sec accuracy=98.717548 loss=0.060221 lr=0.000004 Epoch[098] Batch [2649]/[3759] Speed: 94.088885 samples/sec accuracy=98.725236 loss=0.060085 lr=0.000004 Epoch[098] Batch [2699]/[3759] Speed: 93.541228 samples/sec accuracy=98.728588 loss=0.060104 lr=0.000004 Epoch[098] Batch [2749]/[3759] Speed: 94.486722 samples/sec accuracy=98.731250 loss=0.059970 lr=0.000004 Epoch[098] Batch [2799]/[3759] Speed: 92.061074 samples/sec accuracy=98.732143 loss=0.059968 lr=0.000004 Epoch[098] 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accuracy=98.737216 loss=0.059683 lr=0.000003 Epoch[098] Batch [3349]/[3759] Speed: 94.192931 samples/sec accuracy=98.741138 loss=0.059619 lr=0.000003 Epoch[098] Batch [3399]/[3759] Speed: 93.176625 samples/sec accuracy=98.743107 loss=0.059498 lr=0.000003 Epoch[098] Batch [3449]/[3759] Speed: 93.465348 samples/sec accuracy=98.741395 loss=0.059501 lr=0.000003 Epoch[098] Batch [3499]/[3759] Speed: 92.102984 samples/sec accuracy=98.740179 loss=0.059563 lr=0.000003 Epoch[098] Batch [3549]/[3759] Speed: 95.135914 samples/sec accuracy=98.737236 loss=0.059589 lr=0.000003 Epoch[098] Batch [3599]/[3759] Speed: 94.039939 samples/sec accuracy=98.736111 loss=0.059611 lr=0.000003 Epoch[098] Batch [3649]/[3759] Speed: 92.713278 samples/sec accuracy=98.734589 loss=0.059600 lr=0.000003 Epoch[098] Batch [3699]/[3759] Speed: 94.452062 samples/sec accuracy=98.729730 loss=0.059708 lr=0.000002 Epoch[098] Batch [3749]/[3759] Speed: 106.813634 samples/sec accuracy=98.729583 loss=0.059700 lr=0.000002 Batch [0049]/[0303]: acc-top1=66.718750 acc-top5=85.937500 Batch [0099]/[0303]: acc-top1=64.875000 acc-top5=85.218750 Batch [0149]/[0303]: acc-top1=66.135417 acc-top5=86.083333 Batch [0199]/[0303]: acc-top1=69.023438 acc-top5=87.382812 Batch [0249]/[0303]: acc-top1=68.650000 acc-top5=86.968750 Batch [0299]/[0303]: acc-top1=68.395833 acc-top5=86.984375 [Epoch 098] training: accuracy=98.729300 loss=0.059723 [Epoch 098] speed: 93 samples/sec time cost: 2794.144789 [Epoch 098] validation: acc-top1=68.378713 acc-top5=86.927599 loss=2.370252 Epoch[099] Batch [0049]/[3760] Speed: 64.303364 samples/sec accuracy=98.468750 loss=0.068229 lr=0.000002 Epoch[099] Batch [0099]/[3760] Speed: 94.118137 samples/sec accuracy=98.531250 loss=0.066061 lr=0.000002 Epoch[099] Batch [0149]/[3760] Speed: 94.073320 samples/sec accuracy=98.666667 loss=0.062364 lr=0.000002 Epoch[099] Batch [0199]/[3760] Speed: 93.173665 samples/sec accuracy=98.617188 loss=0.063319 lr=0.000002 Epoch[099] Batch [0249]/[3760] Speed: 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93.248012 samples/sec accuracy=98.739826 loss=0.060348 lr=0.000000 Epoch[099] Batch [2199]/[3760] Speed: 94.108838 samples/sec accuracy=98.739347 loss=0.060342 lr=0.000000 Epoch[099] Batch [2249]/[3760] Speed: 93.716332 samples/sec accuracy=98.734722 loss=0.060329 lr=0.000000 Epoch[099] Batch [2299]/[3760] Speed: 93.688752 samples/sec accuracy=98.735734 loss=0.060264 lr=0.000000 Epoch[099] Batch [2349]/[3760] Speed: 93.622256 samples/sec accuracy=98.740691 loss=0.060139 lr=0.000000 Epoch[099] Batch [2399]/[3760] Speed: 93.560910 samples/sec accuracy=98.732422 loss=0.060536 lr=0.000000 Epoch[099] Batch [2449]/[3760] Speed: 93.369741 samples/sec accuracy=98.732143 loss=0.060573 lr=0.000000 Epoch[099] Batch [2499]/[3760] Speed: 93.914389 samples/sec accuracy=98.735000 loss=0.060460 lr=0.000000 Epoch[099] Batch [2549]/[3760] Speed: 91.116854 samples/sec accuracy=98.737132 loss=0.060404 lr=0.000000 Epoch[099] Batch [2599]/[3760] Speed: 95.631459 samples/sec accuracy=98.733774 loss=0.060351 lr=0.000000 Epoch[099] Batch [2649]/[3760] Speed: 93.854208 samples/sec accuracy=98.734080 loss=0.060359 lr=0.000000 Epoch[099] Batch [2699]/[3760] Speed: 92.168937 samples/sec accuracy=98.736690 loss=0.060354 lr=0.000000 Epoch[099] Batch [2749]/[3760] Speed: 94.271816 samples/sec accuracy=98.731250 loss=0.060415 lr=0.000000 Epoch[099] Batch [2799]/[3760] Speed: 94.135582 samples/sec accuracy=98.727679 loss=0.060432 lr=0.000000 Epoch[099] Batch [2849]/[3760] Speed: 93.410806 samples/sec accuracy=98.724232 loss=0.060405 lr=0.000000 Epoch[099] Batch [2899]/[3760] Speed: 93.641660 samples/sec accuracy=98.726832 loss=0.060301 lr=0.000000 Epoch[099] Batch [2949]/[3760] Speed: 92.990117 samples/sec accuracy=98.726695 loss=0.060232 lr=0.000000 Epoch[099] Batch [2999]/[3760] Speed: 93.367319 samples/sec accuracy=98.720312 loss=0.060355 lr=0.000000 Epoch[099] Batch [3049]/[3760] Speed: 94.149665 samples/sec accuracy=98.716189 loss=0.060446 lr=0.000000 Epoch[099] Batch [3099]/[3760] Speed: 93.789062 samples/sec accuracy=98.714718 loss=0.060558 lr=0.000000 Epoch[099] Batch [3149]/[3760] Speed: 93.589743 samples/sec accuracy=98.709325 loss=0.060709 lr=0.000000 Epoch[099] Batch [3199]/[3760] Speed: 94.069759 samples/sec accuracy=98.711914 loss=0.060587 lr=0.000000 Epoch[099] Batch [3249]/[3760] Speed: 94.124306 samples/sec accuracy=98.707212 loss=0.060637 lr=0.000000 Epoch[099] Batch [3299]/[3760] Speed: 93.467553 samples/sec accuracy=98.706439 loss=0.060642 lr=0.000000 Epoch[099] Batch [3349]/[3760] Speed: 93.595311 samples/sec accuracy=98.709888 loss=0.060557 lr=0.000000 Epoch[099] Batch [3399]/[3760] Speed: 91.950088 samples/sec accuracy=98.714614 loss=0.060451 lr=0.000000 Epoch[099] Batch [3449]/[3760] Speed: 94.713902 samples/sec accuracy=98.719656 loss=0.060285 lr=0.000000 Epoch[099] Batch [3499]/[3760] Speed: 93.679262 samples/sec accuracy=98.714732 loss=0.060410 lr=0.000000 Epoch[099] Batch [3549]/[3760] Speed: 92.301939 samples/sec accuracy=98.718750 loss=0.060285 lr=0.000000 Epoch[099] Batch [3599]/[3760] Speed: 94.419722 samples/sec accuracy=98.719184 loss=0.060268 lr=0.000000 Epoch[099] Batch [3649]/[3760] Speed: 94.132276 samples/sec accuracy=98.721747 loss=0.060230 lr=0.000000 Epoch[099] Batch [3699]/[3760] Speed: 93.019824 samples/sec accuracy=98.719172 loss=0.060382 lr=0.000000 Epoch[099] Batch [3749]/[3760] Speed: 106.735212 samples/sec accuracy=98.718750 loss=0.060310 lr=0.000000 Batch [0049]/[0303]: acc-top1=66.937500 acc-top5=85.656250 Batch [0099]/[0303]: acc-top1=64.906250 acc-top5=84.906250 Batch [0149]/[0303]: acc-top1=66.177083 acc-top5=85.979167 Batch [0199]/[0303]: acc-top1=68.953125 acc-top5=87.390625 Batch [0249]/[0303]: acc-top1=68.537500 acc-top5=86.918750 Batch [0299]/[0303]: acc-top1=68.317708 acc-top5=86.916667 [Epoch 099] training: accuracy=98.720080 loss=0.060262 [Epoch 099] speed: 93 samples/sec time cost: 2798.592898 [Epoch 099] validation: acc-top1=68.291048 acc-top5=86.870875 loss=2.387971