Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST

Related tags

Deep Learning pytorch image-classification object-detection data-augmentation person-re-identification aaai2020
Overview

Random Erasing Data Augmentation

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Examples

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This code has the source code for the paper "Random Erasing Data Augmentation".

If you find this code useful in your research, please consider citing:

@inproceedings{zhong2020random,
title={Random Erasing Data Augmentation},
author={Zhong, Zhun and Zheng, Liang and Kang, Guoliang and Li, Shaozi and Yang, Yi},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)},
year={2020}
}

Other re-implementations

[Official Torchvision in Transform]

[Pytorch: Random Erasing for ImageNet]

[Python Augmentor]

[Person_reID CamStyle]

[Person_reID_baseline + Random Erasing + Re-ranking]

[Keras re-implementation]

Installation

Requirements for Pytorch （see Pytorch installation instructions）

Examples:

CIFAR10

ResNet-20 baseline on CIFAR10： python cifar.py --dataset cifar10 --arch resnet --depth 20

ResNet-20 + Random Erasing on CIFAR10： python cifar.py --dataset cifar10 --arch resnet --depth 20 --p 0.5

CIFAR100

ResNet-20 baseline on CIFAR100： python cifar.py --dataset cifar100 --arch resnet --depth 20

ResNet-20 + Random Erasing on CIFAR100： python cifar.py --dataset cifar100 --arch resnet --depth 20 --p 0.5

Fashion-MNIST

ResNet-20 baseline on Fashion-MNIST： python fashionmnist.py --dataset fashionmnist --arch resnet --depth 20

ResNet-20 + Random Erasing on Fashion-MNIST： python fashionmnist.py --dataset fashionmnist --arch resnet --depth 20 --p 0.5

Other architectures

For ResNet： --arch resnet --depth (20， 32， 44， 56， 110)

For WRN： --arch wrn --depth 28 --widen-factor 10

Our results

You can reproduce the results in our paper:

 CIFAR10 CIFAR10 CIFAR100 CIFAR100 Fashion-MNIST Fashion-MNIST
Models  Base. +RE Base. +RE Base. +RE
ResNet-20  7.21 6.73 30.84 29.97 4.39 4.02
ResNet-32  6.41 5.66 28.50 27.18 4.16 3.80
ResNet-44  5.53 5.13 25.27 24.29 4.41 4.01
ResNet-56  5.31 4.89 24.82 23.69 4.39 4.13
ResNet-110  5.10 4.61 23.73 22.10 4.40 4.01
WRN-28-10  3.80 3.08 18.49 17.73 4.01 3.65

NOTE THAT, if you use the latest released Fashion-MNIST, the performance of Baseline and RE will slightly lower than the results reported in our paper. Please refer to the issue.

If you have any questions about this code, please do not hesitate to contact us.

Zhun Zhong

Liang Zheng

Comments
  • inconsistency of Fashion-MNIST results using resnet 20

    inconsistency of Fashion-MNIST results using resnet 20

    I ran your code several times on the dataset Fashion-MNIST using resnet20 with random erasing 0.5.

    I didn't get your reported error 4.02% ± 0.07 using your default code "python fashionmnist.py --dataset fashionmnist --arch resnet --depth 20 --p 0.5", the results are roughly 4.5% on average.

    Could you show me how can I get the result ~96% as you mentioned in your paper?

    Thanks a lot.

    opened by WayneDW 3
  • Cannot reproduce the result for fashion-mnist

    Cannot reproduce the result for fashion-mnist

    I trained a model for Fashion-MNIST. Unfortunately the performance is not as good as the result reported in the paper.

    The best accuracy is 95.8% to me, while the error is 3.65 in the paper when training WRN-28-10 for Fashion-MNIST.

    I wonder if the authors can provide the command line argument that used in the paper, so that people (like me) can reproduce the experiment.

    $ python fashionmnist.py --dataset fashionmnist --arch wrn --depth 28 --widen-factor 10 --p 0.5
==> Preparing dataset fashionmnist
==> creating model 'wrn'
    Total params: 36.48M
Epoch: [1 | 300] LR: 0.100000
fashionmnist.py:233: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
  losses.update(loss.data[0], inputs.size(0))
fashionmnist.py:234: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
  top1.update(prec1[0], inputs.size(0))
fashionmnist.py:235: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
  top5.update(prec5[0], inputs.size(0))
Processing |################################| (469/469) Data: 0.224s | Batch: 0.243s | Total: 0:01:53 | ETA: 0:00:01 | Loss: 0.7331 | top1:  72.4383 | top5:  98.0533
fashionmnist.py:282: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.
  inputs, targets = torch.autograd.Variable(inputs, volatile=True), torch.autograd.Variable(targets)
fashionmnist.py:290: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
  losses.update(loss.data[0], inputs.size(0))
fashionmnist.py:291: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
  top1.update(prec1[0], inputs.size(0))
fashionmnist.py:292: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
  top5.update(prec5[0], inputs.size(0))
Processing |################################| (100/100) Data: 0.065s | Batch: 0.073s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.4355 | top1:  83.4900 | top5:  99.8300
Epoch: [2 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.4240 | top1:  84.0867 | top5:  99.7117
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.4642 | top1:  82.3600 | top5:  99.6400
Epoch: [3 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.3611 | top1:  86.7067 | top5:  99.8050
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.5624 | top1:  79.2600 | top5:  99.8100
Epoch: [4 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.3359 | top1:  87.7300 | top5:  99.8383
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2716 | top1:  90.0700 | top5:  99.9100
Epoch: [5 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.3178 | top1:  88.3983 | top5:  99.8600
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3080 | top1:  88.7900 | top5:  99.8800
Epoch: [6 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.3052 | top1:  88.7367 | top5:  99.8583
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3981 | top1:  85.7300 | top5:  99.8600
Epoch: [7 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2973 | top1:  89.1200 | top5:  99.8800
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2965 | top1:  89.2700 | top5:  99.8800
Epoch: [8 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2941 | top1:  89.3617 | top5:  99.8650
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2543 | top1:  90.7500 | top5:  99.8900
Epoch: [9 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2854 | top1:  89.6750 | top5:  99.8817
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3036 | top1:  89.0100 | top5:  99.9200
Epoch: [10 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2895 | top1:  89.5217 | top5:  99.8667
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2894 | top1:  89.3400 | top5:  99.9100
Epoch: [11 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2883 | top1:  89.4667 | top5:  99.8717
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3143 | top1:  87.8700 | top5:  99.9000
Epoch: [12 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2873 | top1:  89.5983 | top5:  99.8767
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2573 | top1:  90.3800 | top5:  99.9100
Epoch: [13 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.234s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2782 | top1:  89.8850 | top5:  99.8983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2432 | top1:  91.3700 | top5:  99.8800
Epoch: [14 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2713 | top1:  90.1100 | top5:  99.8967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2748 | top1:  89.7200 | top5:  99.9200
Epoch: [15 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.234s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2746 | top1:  90.0417 | top5:  99.8850
Processing |################################| (100/100) Data: 0.067s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2393 | top1:  91.4200 | top5:  99.9100
Epoch: [16 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2687 | top1:  90.2517 | top5:  99.8867
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2789 | top1:  90.4100 | top5:  99.8700
Epoch: [17 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2680 | top1:  90.2883 | top5:  99.9000
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2640 | top1:  90.6800 | top5:  99.9400
Epoch: [18 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.234s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2677 | top1:  90.3050 | top5:  99.8867
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2770 | top1:  90.3300 | top5:  99.8900
Epoch: [19 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.234s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2632 | top1:  90.4933 | top5:  99.8883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2481 | top1:  91.0300 | top5:  99.9100
Epoch: [20 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2624 | top1:  90.5117 | top5:  99.8883
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2410 | top1:  91.5700 | top5:  99.9300
Epoch: [21 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2603 | top1:  90.5867 | top5:  99.8967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2186 | top1:  92.5400 | top5:  99.8800
Epoch: [22 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2587 | top1:  90.7067 | top5:  99.9000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2820 | top1:  89.6800 | top5:  99.8900
Epoch: [23 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2579 | top1:  90.5083 | top5:  99.9150
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3270 | top1:  88.7400 | top5:  99.8900
Epoch: [24 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2559 | top1:  90.6717 | top5:  99.9217
Processing |################################| (100/100) Data: 0.065s | Batch: 0.068s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2292 | top1:  91.7100 | top5:  99.9200
Epoch: [25 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2542 | top1:  90.8333 | top5:  99.9067
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2636 | top1:  90.0100 | top5:  99.9000
Epoch: [26 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2540 | top1:  90.8933 | top5:  99.9000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2247 | top1:  92.0800 | top5:  99.9300
Epoch: [27 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2531 | top1:  90.7483 | top5:  99.9317
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2564 | top1:  90.8900 | top5:  99.9200
Epoch: [28 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2546 | top1:  90.7483 | top5:  99.9117
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3142 | top1:  89.7200 | top5:  99.9000
Epoch: [29 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2510 | top1:  90.9517 | top5:  99.9183
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2717 | top1:  90.0200 | top5:  99.9300
Epoch: [30 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2495 | top1:  90.9550 | top5:  99.9183
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2766 | top1:  90.0800 | top5:  99.8900
Epoch: [31 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2529 | top1:  90.8617 | top5:  99.9167
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2128 | top1:  92.3100 | top5:  99.9500
Epoch: [32 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2469 | top1:  91.1750 | top5:  99.9050
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.4276 | top1:  83.9900 | top5:  99.8600
Epoch: [33 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2478 | top1:  91.0650 | top5:  99.8983
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2393 | top1:  91.3700 | top5:  99.9200
Epoch: [34 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2454 | top1:  91.0883 | top5:  99.9300
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2477 | top1:  90.9400 | top5:  99.9000
Epoch: [35 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2483 | top1:  90.9550 | top5:  99.9017
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2165 | top1:  92.4300 | top5:  99.9300
Epoch: [36 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2447 | top1:  91.1467 | top5:  99.9133
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3288 | top1:  88.5500 | top5:  99.8800
Epoch: [37 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2461 | top1:  91.0000 | top5:  99.9233
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2363 | top1:  91.3700 | top5:  99.9000
Epoch: [38 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2450 | top1:  91.1217 | top5:  99.9167
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3010 | top1:  88.8600 | top5:  99.9600
Epoch: [39 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2454 | top1:  91.1633 | top5:  99.9300
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2135 | top1:  92.3800 | top5:  99.9600
Epoch: [40 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2489 | top1:  90.9083 | top5:  99.9117
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3074 | top1:  89.1100 | top5:  99.9200
Epoch: [41 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2484 | top1:  91.0883 | top5:  99.9050
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2024 | top1:  92.9400 | top5:  99.9400
Epoch: [42 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2479 | top1:  91.0250 | top5:  99.9217
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2520 | top1:  91.2400 | top5:  99.9000
Epoch: [43 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2423 | top1:  91.1833 | top5:  99.9317
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2406 | top1:  91.6800 | top5:  99.9600
Epoch: [44 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2446 | top1:  91.1267 | top5:  99.9133
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2616 | top1:  90.8400 | top5:  99.9200
Epoch: [45 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2511 | top1:  90.7767 | top5:  99.9017
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2965 | top1:  89.6300 | top5:  99.8600
Epoch: [46 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2464 | top1:  91.1067 | top5:  99.9117
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2545 | top1:  90.7500 | top5:  99.9100
Epoch: [47 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2419 | top1:  91.3117 | top5:  99.9017
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2284 | top1:  92.0000 | top5:  99.9200
Epoch: [48 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2428 | top1:  91.1717 | top5:  99.9133
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2543 | top1:  90.2500 | top5:  99.9500
Epoch: [49 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2387 | top1:  91.3400 | top5:  99.9167
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2053 | top1:  92.6700 | top5:  99.9600
Epoch: [50 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2416 | top1:  91.1083 | top5:  99.9317
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2301 | top1:  91.9700 | top5:  99.9300
Epoch: [51 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2416 | top1:  91.1983 | top5:  99.9250
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2581 | top1:  90.8400 | top5:  99.9200
Epoch: [52 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2443 | top1:  91.2017 | top5:  99.9083
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2100 | top1:  92.2600 | top5:  99.9200
Epoch: [53 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2414 | top1:  91.2667 | top5:  99.9117
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2372 | top1:  91.6000 | top5:  99.9400
Epoch: [54 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2417 | top1:  91.4067 | top5:  99.9033
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2182 | top1:  92.4000 | top5:  99.9100
Epoch: [55 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2431 | top1:  91.1033 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2601 | top1:  90.7800 | top5:  99.8900
Epoch: [56 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2433 | top1:  91.2333 | top5:  99.9217
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1988 | top1:  93.0300 | top5:  99.9700
Epoch: [57 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2401 | top1:  91.3783 | top5:  99.9133
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3386 | top1:  88.7700 | top5:  99.9000
Epoch: [58 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2401 | top1:  91.2800 | top5:  99.9283
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2491 | top1:  90.6900 | top5:  99.9600
Epoch: [59 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2421 | top1:  91.2583 | top5:  99.9217
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2504 | top1:  90.9100 | top5:  99.9200
Epoch: [60 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2402 | top1:  91.3017 | top5:  99.9200
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2381 | top1:  91.4700 | top5:  99.9700
Epoch: [61 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2447 | top1:  91.0817 | top5:  99.9167
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3353 | top1:  87.9900 | top5:  99.9100
Epoch: [62 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2384 | top1:  91.3983 | top5:  99.9300
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2222 | top1:  92.1000 | top5:  99.9400
Epoch: [63 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2418 | top1:  91.2750 | top5:  99.9150
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2567 | top1:  90.9800 | top5:  99.9100
Epoch: [64 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2372 | top1:  91.4500 | top5:  99.9233
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2522 | top1:  91.0700 | top5:  99.9500
Epoch: [65 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2399 | top1:  91.2933 | top5:  99.9233
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3913 | top1:  85.2500 | top5:  99.9400
Epoch: [66 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2389 | top1:  91.2683 | top5:  99.9067
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2375 | top1:  91.9500 | top5:  99.9600
Epoch: [67 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2375 | top1:  91.3700 | top5:  99.9250
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3387 | top1:  88.0800 | top5:  99.9200
Epoch: [68 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2415 | top1:  91.1967 | top5:  99.9317
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2253 | top1:  91.7100 | top5:  99.9600
Epoch: [69 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2398 | top1:  91.3350 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2029 | top1:  92.8500 | top5:  99.9600
Epoch: [70 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2391 | top1:  91.2267 | top5:  99.9417
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2420 | top1:  91.4200 | top5:  99.9100
Epoch: [71 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2365 | top1:  91.3500 | top5:  99.9200
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2272 | top1:  91.7900 | top5:  99.9400
Epoch: [72 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2360 | top1:  91.4800 | top5:  99.9233
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2120 | top1:  92.4500 | top5:  99.8900
Epoch: [73 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2383 | top1:  91.3700 | top5:  99.9100
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2247 | top1:  92.1500 | top5:  99.9400
Epoch: [74 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2414 | top1:  91.2567 | top5:  99.9400
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2639 | top1:  90.3600 | top5:  99.9300
Epoch: [75 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2368 | top1:  91.4550 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3011 | top1:  89.2600 | top5:  99.8700
Epoch: [76 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2386 | top1:  91.4017 | top5:  99.9133
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2539 | top1:  91.3800 | top5:  99.9000
Epoch: [77 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2393 | top1:  91.3683 | top5:  99.9233
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2681 | top1:  90.2500 | top5:  99.9200
Epoch: [78 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2347 | top1:  91.5383 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2214 | top1:  92.0800 | top5:  99.9400
Epoch: [79 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2388 | top1:  91.3367 | top5:  99.9283
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2464 | top1:  91.0400 | top5:  99.9800
Epoch: [80 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2378 | top1:  91.3800 | top5:  99.9467
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2196 | top1:  92.4200 | top5:  99.9400
Epoch: [81 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2417 | top1:  91.2183 | top5:  99.9317
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2716 | top1:  90.6700 | top5:  99.9000
Epoch: [82 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2393 | top1:  91.3300 | top5:  99.9233
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2639 | top1:  91.2500 | top5:  99.9600
Epoch: [83 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2360 | top1:  91.4417 | top5:  99.9283
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3231 | top1:  89.4300 | top5:  99.8400
Epoch: [84 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2386 | top1:  91.3150 | top5:  99.9167
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2418 | top1:  91.3000 | top5:  99.9700
Epoch: [85 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2384 | top1:  91.2550 | top5:  99.9350
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2139 | top1:  92.3100 | top5:  99.9300
Epoch: [86 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2382 | top1:  91.4917 | top5:  99.9400
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2260 | top1:  92.4200 | top5:  99.9200
Epoch: [87 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2361 | top1:  91.4900 | top5:  99.9100
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2359 | top1:  91.3300 | top5:  99.9400
Epoch: [88 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2384 | top1:  91.4567 | top5:  99.9000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2621 | top1:  90.7500 | top5:  99.8200
Epoch: [89 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2346 | top1:  91.5283 | top5:  99.9317
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2029 | top1:  92.7100 | top5:  99.9200
Epoch: [90 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2385 | top1:  91.3933 | top5:  99.9183
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2258 | top1:  92.0700 | top5:  99.9500
Epoch: [91 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2342 | top1:  91.4667 | top5:  99.9300
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2749 | top1:  90.5400 | top5:  99.8400
Epoch: [92 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.234s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2368 | top1:  91.4583 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2636 | top1:  91.0400 | top5:  99.9000
Epoch: [93 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2366 | top1:  91.4250 | top5:  99.9200
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2081 | top1:  92.7800 | top5:  99.9400
Epoch: [94 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2361 | top1:  91.4567 | top5:  99.9300
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3288 | top1:  88.7100 | top5:  99.9100
Epoch: [95 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2362 | top1:  91.4283 | top5:  99.9300
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2725 | top1:  90.6700 | top5:  99.8800
Epoch: [96 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2387 | top1:  91.3250 | top5:  99.9117
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2274 | top1:  92.0000 | top5:  99.9300
Epoch: [97 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2361 | top1:  91.4533 | top5:  99.9233
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2073 | top1:  92.5200 | top5:  99.9300
Epoch: [98 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2414 | top1:  91.1900 | top5:  99.9100
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2220 | top1:  91.9800 | top5:  99.9400
Epoch: [99 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2412 | top1:  91.2300 | top5:  99.9483
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2427 | top1:  91.4100 | top5:  99.9300
Epoch: [100 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2383 | top1:  91.4100 | top5:  99.9233
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2911 | top1:  89.6300 | top5:  99.8200
Epoch: [101 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2362 | top1:  91.3300 | top5:  99.9250
Processing |################################| (100/100) Data: 0.067s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2823 | top1:  91.0000 | top5:  99.9100
Epoch: [102 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2345 | top1:  91.4333 | top5:  99.9233
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2747 | top1:  89.9800 | top5:  99.8100
Epoch: [103 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2366 | top1:  91.4133 | top5:  99.9333
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2189 | top1:  92.0300 | top5:  99.8800
Epoch: [104 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2351 | top1:  91.4167 | top5:  99.9133
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2445 | top1:  91.1900 | top5:  99.9500
Epoch: [105 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2370 | top1:  91.3267 | top5:  99.9133
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2552 | top1:  90.7900 | top5:  99.9000
Epoch: [106 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2391 | top1:  91.3883 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1830 | top1:  93.6300 | top5:  99.9300
Epoch: [107 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2352 | top1:  91.4950 | top5:  99.9133
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2165 | top1:  92.1800 | top5:  99.9400
Epoch: [108 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2380 | top1:  91.4183 | top5:  99.9183
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3041 | top1:  89.1600 | top5:  99.9100
Epoch: [109 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2393 | top1:  91.3933 | top5:  99.9233
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2171 | top1:  92.4800 | top5:  99.8800
Epoch: [110 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2357 | top1:  91.4417 | top5:  99.9117
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2399 | top1:  91.2600 | top5:  100.0000
Epoch: [111 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2369 | top1:  91.4117 | top5:  99.9067
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2501 | top1:  90.9600 | top5:  99.9000
Epoch: [112 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2369 | top1:  91.2967 | top5:  99.9200
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2045 | top1:  92.6100 | top5:  99.9900
Epoch: [113 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.248s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2348 | top1:  91.4950 | top5:  99.9283
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2324 | top1:  91.7700 | top5:  99.9200
Epoch: [114 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:56 | ETA: 0:00:01 | Loss: 0.2385 | top1:  91.3567 | top5:  99.8967
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2325 | top1:  91.3500 | top5:  99.9400
Epoch: [115 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2355 | top1:  91.2417 | top5:  99.9283
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2273 | top1:  91.5300 | top5:  99.9700
Epoch: [116 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2369 | top1:  91.4167 | top5:  99.9150
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2273 | top1:  92.1000 | top5:  99.9600
Epoch: [117 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2378 | top1:  91.3883 | top5:  99.9167
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2416 | top1:  90.8100 | top5:  99.9200
Epoch: [118 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2368 | top1:  91.3700 | top5:  99.9283
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2143 | top1:  92.0200 | top5:  99.9400
Epoch: [119 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2351 | top1:  91.3817 | top5:  99.9383
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2323 | top1:  91.8100 | top5:  99.9500
Epoch: [120 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2339 | top1:  91.5633 | top5:  99.9183
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2840 | top1:  89.7700 | top5:  99.9400
Epoch: [121 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2344 | top1:  91.5200 | top5:  99.9317
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2427 | top1:  91.0300 | top5:  99.9600
Epoch: [122 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2402 | top1:  91.2400 | top5:  99.9200
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2291 | top1:  92.0900 | top5:  99.9000
Epoch: [123 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2354 | top1:  91.4683 | top5:  99.9167
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2340 | top1:  91.6100 | top5:  99.9500
Epoch: [124 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2343 | top1:  91.5433 | top5:  99.8950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2932 | top1:  90.0900 | top5:  99.9300
Epoch: [125 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2378 | top1:  91.3633 | top5:  99.9450
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2077 | top1:  92.5700 | top5:  99.9700
Epoch: [126 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2337 | top1:  91.5717 | top5:  99.9167
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2225 | top1:  91.9000 | top5:  99.9400
Epoch: [127 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2350 | top1:  91.4583 | top5:  99.9333
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2306 | top1:  91.5300 | top5:  99.9200
Epoch: [128 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2350 | top1:  91.4283 | top5:  99.9250
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2705 | top1:  90.2500 | top5:  99.9000
Epoch: [129 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2332 | top1:  91.5700 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2218 | top1:  92.0300 | top5:  99.9300
Epoch: [130 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2386 | top1:  91.3167 | top5:  99.9233
Processing |################################| (100/100) Data: 0.067s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.2108 | top1:  92.8400 | top5:  99.9600
Epoch: [131 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2321 | top1:  91.6767 | top5:  99.9283
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2593 | top1:  91.0300 | top5:  99.8500
Epoch: [132 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2363 | top1:  91.3567 | top5:  99.9283
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2272 | top1:  91.8700 | top5:  99.8800
Epoch: [133 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2397 | top1:  91.2867 | top5:  99.9100
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2404 | top1:  91.7300 | top5:  99.9300
Epoch: [134 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2352 | top1:  91.5950 | top5:  99.9267
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2118 | top1:  92.1500 | top5:  99.9400
Epoch: [135 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2369 | top1:  91.4733 | top5:  99.9267
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2302 | top1:  92.2100 | top5:  99.9000
Epoch: [136 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2375 | top1:  91.5867 | top5:  99.9167
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2122 | top1:  92.3200 | top5:  99.9200
Epoch: [137 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2366 | top1:  91.4033 | top5:  99.9417
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3695 | top1:  87.5800 | top5:  99.8900
Epoch: [138 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2329 | top1:  91.5150 | top5:  99.9283
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2554 | top1:  91.3800 | top5:  99.9200
Epoch: [139 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2345 | top1:  91.4283 | top5:  99.9183
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2050 | top1:  92.7200 | top5:  99.9500
Epoch: [140 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2373 | top1:  91.4100 | top5:  99.9200
Processing |################################| (100/100) Data: 0.064s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2427 | top1:  91.8200 | top5:  99.9300
Epoch: [141 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2366 | top1:  91.4500 | top5:  99.9350
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2626 | top1:  90.8700 | top5:  99.9200
Epoch: [142 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2347 | top1:  91.5450 | top5:  99.9350
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.3485 | top1:  88.7600 | top5:  99.9300
Epoch: [143 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2329 | top1:  91.5050 | top5:  99.9367
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2365 | top1:  91.8200 | top5:  99.8700
Epoch: [144 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2345 | top1:  91.5067 | top5:  99.9250
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2126 | top1:  92.5700 | top5:  99.9600
Epoch: [145 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2350 | top1:  91.5517 | top5:  99.9433
Processing |################################| (100/100) Data: 0.067s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1965 | top1:  92.7600 | top5:  99.9300
Epoch: [146 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2354 | top1:  91.3917 | top5:  99.9233
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2084 | top1:  92.8200 | top5:  99.9200
Epoch: [147 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2346 | top1:  91.5817 | top5:  99.9350
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2268 | top1:  91.8200 | top5:  99.9300
Epoch: [148 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2365 | top1:  91.4417 | top5:  99.9400
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2263 | top1:  91.9700 | top5:  99.9400
Epoch: [149 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2346 | top1:  91.5017 | top5:  99.9400
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1839 | top1:  93.6400 | top5:  99.9700
Epoch: [150 | 300] LR: 0.100000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.2376 | top1:  91.4083 | top5:  99.9283
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2294 | top1:  91.6700 | top5:  99.9600
Epoch: [151 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1716 | top1:  93.8800 | top5:  99.9567
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1446 | top1:  94.8500 | top5:  99.9700
Epoch: [152 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.230s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1509 | top1:  94.6667 | top5:  99.9750
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1418 | top1:  95.0000 | top5:  99.9800
Epoch: [153 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1445 | top1:  94.7533 | top5:  99.9800
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1441 | top1:  95.0300 | top5:  99.9700
Epoch: [154 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1374 | top1:  95.1467 | top5:  99.9800
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1418 | top1:  95.0700 | top5:  99.9600
Epoch: [155 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:54 | ETA: 0:00:01 | Loss: 0.1351 | top1:  95.0483 | top5:  99.9867
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1393 | top1:  95.0900 | top5:  99.9600
Epoch: [156 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1313 | top1:  95.3400 | top5:  99.9833
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1428 | top1:  95.1600 | top5:  99.9800
Epoch: [157 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:54 | ETA: 0:00:01 | Loss: 0.1295 | top1:  95.3350 | top5:  99.9850
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1418 | top1:  95.0600 | top5:  99.9600
Epoch: [158 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1268 | top1:  95.5400 | top5:  99.9833
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1455 | top1:  94.9400 | top5:  99.9600
Epoch: [159 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1243 | top1:  95.5867 | top5:  99.9850
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1429 | top1:  95.0900 | top5:  99.9700
Epoch: [160 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1208 | top1:  95.6983 | top5:  99.9833
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1487 | top1:  95.0600 | top5:  99.9800
Epoch: [161 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1208 | top1:  95.6783 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1375 | top1:  95.2100 | top5:  99.9800
Epoch: [162 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1181 | top1:  95.8133 | top5:  99.9967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1411 | top1:  95.2000 | top5:  99.9800
Epoch: [163 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1170 | top1:  95.7667 | top5:  99.9967
Processing |################################| (100/100) Data: 0.067s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1406 | top1:  95.2300 | top5:  99.9600
Epoch: [164 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1164 | top1:  95.8217 | top5:  99.9950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1460 | top1:  95.0000 | top5:  99.9700
Epoch: [165 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1168 | top1:  95.8483 | top5:  99.9867
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1452 | top1:  94.9500 | top5:  99.9700
Epoch: [166 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1136 | top1:  95.9683 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1479 | top1:  95.2000 | top5:  99.9600
Epoch: [167 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1132 | top1:  95.8933 | top5:  99.9867
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1423 | top1:  95.2300 | top5:  99.9700
Epoch: [168 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1108 | top1:  96.0450 | top5:  99.9867
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1521 | top1:  94.9300 | top5:  99.9600
Epoch: [169 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1127 | top1:  96.0133 | top5:  99.9883
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1517 | top1:  94.9200 | top5:  99.9800
Epoch: [170 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1126 | top1:  95.9700 | top5:  99.9850
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1565 | top1:  94.8500 | top5:  99.9600
Epoch: [171 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1103 | top1:  96.1033 | top5:  99.9867
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1506 | top1:  95.3200 | top5:  99.9800
Epoch: [172 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1084 | top1:  96.0883 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1586 | top1:  94.5800 | top5:  99.9700
Epoch: [173 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1103 | top1:  96.0350 | top5:  99.9850
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1544 | top1:  95.0600 | top5:  100.0000
Epoch: [174 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1115 | top1:  95.9500 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1437 | top1:  95.4200 | top5:  99.9700
Epoch: [175 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:54 | ETA: 0:00:01 | Loss: 0.1100 | top1:  96.0017 | top5:  99.9950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1629 | top1:  94.5500 | top5:  99.9700
Epoch: [176 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:54 | ETA: 0:00:01 | Loss: 0.1072 | top1:  96.1467 | top5:  99.9933
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1714 | top1:  94.4600 | top5:  99.9900
Epoch: [177 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1070 | top1:  96.2250 | top5:  99.9950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1497 | top1:  94.9800 | top5:  99.9700
Epoch: [178 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1069 | top1:  96.2317 | top5:  99.9767
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1515 | top1:  95.2400 | top5:  99.9600
Epoch: [179 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1075 | top1:  96.1467 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1577 | top1:  94.7700 | top5:  99.9600
Epoch: [180 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1058 | top1:  96.1717 | top5:  99.9900
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1495 | top1:  95.2300 | top5:  99.9600
Epoch: [181 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1037 | top1:  96.2583 | top5:  99.9967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1686 | top1:  94.7200 | top5:  99.9900
Epoch: [182 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1073 | top1:  96.1050 | top5:  99.9900
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1577 | top1:  95.0400 | top5:  99.9800
Epoch: [183 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1057 | top1:  96.2117 | top5:  99.9867
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1707 | top1:  94.8200 | top5:  99.9600
Epoch: [184 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.245s | Total: 0:01:54 | ETA: 0:00:01 | Loss: 0.1066 | top1:  96.2200 | top5:  99.9833
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1571 | top1:  94.9200 | top5:  99.9800
Epoch: [185 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1061 | top1:  96.1750 | top5:  99.9917
Processing |################################| (100/100) Data: 0.064s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1620 | top1:  94.7000 | top5:  99.9500
Epoch: [186 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1056 | top1:  96.2350 | top5:  99.9817
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1569 | top1:  95.0000 | top5:  99.9900
Epoch: [187 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1030 | top1:  96.2850 | top5:  99.9933
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1613 | top1:  94.8500 | top5:  99.9700
Epoch: [188 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1047 | top1:  96.2433 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1557 | top1:  95.0000 | top5:  99.9900
Epoch: [189 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1036 | top1:  96.2767 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1701 | top1:  94.5700 | top5:  99.9800
Epoch: [190 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1035 | top1:  96.1833 | top5:  99.9967
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1655 | top1:  94.5700 | top5:  99.9700
Epoch: [191 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1008 | top1:  96.3783 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1644 | top1:  94.9100 | top5:  99.9400
Epoch: [192 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1012 | top1:  96.3550 | top5:  99.9950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1523 | top1:  95.2900 | top5:  99.9400
Epoch: [193 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0980 | top1:  96.5950 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1687 | top1:  94.7100 | top5:  99.9300
Epoch: [194 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1014 | top1:  96.4067 | top5:  99.9900
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1629 | top1:  94.6900 | top5:  99.9600
Epoch: [195 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.1002 | top1:  96.4700 | top5:  99.9950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1560 | top1:  95.1800 | top5:  99.9800
Epoch: [196 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0971 | top1:  96.6000 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1717 | top1:  94.7700 | top5:  99.9400
Epoch: [197 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0990 | top1:  96.4483 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1618 | top1:  95.0700 | top5:  99.9700
Epoch: [198 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0984 | top1:  96.6167 | top5:  99.9883
Processing |################################| (100/100) Data: 0.067s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1741 | top1:  94.8200 | top5:  99.9400
Epoch: [199 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0968 | top1:  96.5150 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1560 | top1:  95.2800 | top5:  99.9800
Epoch: [200 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0996 | top1:  96.4817 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1908 | top1:  94.1100 | top5:  99.9700
Epoch: [201 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0977 | top1:  96.4900 | top5:  99.9967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1693 | top1:  94.9300 | top5:  99.9600
Epoch: [202 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0959 | top1:  96.5683 | top5:  99.9900
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1711 | top1:  94.6100 | top5:  99.9500
Epoch: [203 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0977 | top1:  96.4850 | top5:  99.9967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1863 | top1:  94.1700 | top5:  99.9700
Epoch: [204 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0964 | top1:  96.5267 | top5:  99.9933
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1712 | top1:  94.7400 | top5:  99.9600
Epoch: [205 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0953 | top1:  96.6000 | top5:  99.9883
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1681 | top1:  95.0600 | top5:  99.9700
Epoch: [206 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0939 | top1:  96.6883 | top5:  99.9933
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1750 | top1:  94.7500 | top5:  99.9400
Epoch: [207 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0971 | top1:  96.5600 | top5:  99.9933
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1643 | top1:  95.0300 | top5:  99.9700
Epoch: [208 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0939 | top1:  96.6550 | top5:  99.9917
Processing |################################| (100/100) Data: 0.064s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1751 | top1:  94.5600 | top5:  99.9700
Epoch: [209 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0946 | top1:  96.6317 | top5:  99.9883
Processing |################################| (100/100) Data: 0.067s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1670 | top1:  94.7600 | top5:  99.9600
Epoch: [210 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0947 | top1:  96.5900 | top5:  99.9800
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1627 | top1:  94.9800 | top5:  99.9700
Epoch: [211 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0934 | top1:  96.7133 | top5:  99.9900
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1719 | top1:  94.8600 | top5:  99.9600
Epoch: [212 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0923 | top1:  96.6433 | top5:  99.9900
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1824 | top1:  94.5300 | top5:  100.0000
Epoch: [213 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0919 | top1:  96.8167 | top5:  99.9833
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1674 | top1:  94.9400 | top5:  99.9600
Epoch: [214 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0912 | top1:  96.8517 | top5:  99.9900
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1677 | top1:  94.7400 | top5:  99.9600
Epoch: [215 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0912 | top1:  96.7800 | top5:  99.9917
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1703 | top1:  94.9600 | top5:  99.9800
Epoch: [216 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0928 | top1:  96.7667 | top5:  99.9983
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1619 | top1:  94.9600 | top5:  99.9600
Epoch: [217 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0905 | top1:  96.7950 | top5:  99.9883
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1825 | top1:  94.5100 | top5:  99.9700
Epoch: [218 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0933 | top1:  96.7133 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1886 | top1:  94.6100 | top5:  99.9600
Epoch: [219 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0893 | top1:  96.7733 | top5:  99.9883
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1745 | top1:  94.3700 | top5:  99.9600
Epoch: [220 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0913 | top1:  96.7033 | top5:  99.9900
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.2088 | top1:  93.9700 | top5:  99.9500
Epoch: [221 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0899 | top1:  96.8733 | top5:  99.9950
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1735 | top1:  94.7200 | top5:  99.9900
Epoch: [222 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0899 | top1:  96.8133 | top5:  99.9933
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1708 | top1:  94.8400 | top5:  99.9300
Epoch: [223 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0879 | top1:  96.9017 | top5:  99.9917
Processing |################################| (100/100) Data: 0.064s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1671 | top1:  94.8000 | top5:  99.9900
Epoch: [224 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0877 | top1:  96.8917 | top5:  99.9967
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1825 | top1:  94.4200 | top5:  99.9900
Epoch: [225 | 300] LR: 0.010000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0913 | top1:  96.7467 | top5:  99.9917
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1705 | top1:  94.8200 | top5:  99.9800
Epoch: [226 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0632 | top1:  97.8817 | top5:  99.9950
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1510 | top1:  95.5100 | top5:  99.9700
Epoch: [227 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0530 | top1:  98.2533 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1558 | top1:  95.6200 | top5:  99.9800
Epoch: [228 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0457 | top1:  98.4983 | top5:  99.9983
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1614 | top1:  95.5300 | top5:  99.9800
Epoch: [229 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0443 | top1:  98.5267 | top5:  99.9967
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1622 | top1:  95.5900 | top5:  99.9800
Epoch: [230 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0418 | top1:  98.6083 | top5:  100.0000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1630 | top1:  95.5800 | top5:  99.9600
Epoch: [231 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0432 | top1:  98.6133 | top5:  99.9950
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1647 | top1:  95.4800 | top5:  99.9900
Epoch: [232 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0400 | top1:  98.7133 | top5:  100.0000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1653 | top1:  95.5500 | top5:  99.9600
Epoch: [233 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0392 | top1:  98.7033 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1648 | top1:  95.5900 | top5:  99.9600
Epoch: [234 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0383 | top1:  98.7433 | top5:  99.9967
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1688 | top1:  95.5400 | top5:  99.9700
Epoch: [235 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0370 | top1:  98.8433 | top5:  99.9933
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1683 | top1:  95.6700 | top5:  99.9400
Epoch: [236 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0362 | top1:  98.8500 | top5:  99.9967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1723 | top1:  95.6300 | top5:  99.9700
Epoch: [237 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0359 | top1:  98.8517 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1733 | top1:  95.6700 | top5:  99.9700
Epoch: [238 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0357 | top1:  98.8233 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1760 | top1:  95.5300 | top5:  99.9600
Epoch: [239 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0358 | top1:  98.8517 | top5:  99.9983
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1742 | top1:  95.6900 | top5:  99.9400
Epoch: [240 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0341 | top1:  98.8633 | top5:  99.9983
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1779 | top1:  95.6600 | top5:  99.9500
Epoch: [241 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0349 | top1:  98.8650 | top5:  99.9950
Processing |################################| (100/100) Data: 0.066s | Batch: 0.071s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1771 | top1:  95.6300 | top5:  99.9600
Epoch: [242 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0332 | top1:  98.9100 | top5:  99.9983
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1800 | top1:  95.6800 | top5:  99.9600
Epoch: [243 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0349 | top1:  98.8383 | top5:  99.9950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1813 | top1:  95.6300 | top5:  99.9500
Epoch: [244 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0313 | top1:  99.0000 | top5:  99.9983
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1839 | top1:  95.6100 | top5:  99.9400
Epoch: [245 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0317 | top1:  98.9400 | top5:  99.9967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1823 | top1:  95.6500 | top5:  99.9300
Epoch: [246 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0319 | top1:  98.9567 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1809 | top1:  95.5200 | top5:  99.9300
Epoch: [247 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0320 | top1:  98.9733 | top5:  100.0000
Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1846 | top1:  95.6700 | top5:  99.9600
Epoch: [248 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0310 | top1:  98.9933 | top5:  99.9967
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1859 | top1:  95.6000 | top5:  99.9600
Epoch: [249 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0316 | top1:  98.9383 | top5:  100.0000
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1794 | top1:  95.7500 | top5:  99.9400
Epoch: [250 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0309 | top1:  98.9717 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1838 | top1:  95.6600 | top5:  99.9500
Epoch: [251 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0313 | top1:  98.9983 | top5:  99.9967
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1900 | top1:  95.7000 | top5:  99.9500
Epoch: [252 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0317 | top1:  99.0250 | top5:  100.0000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1847 | top1:  95.6600 | top5:  99.9400
Epoch: [253 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0306 | top1:  98.9817 | top5:  99.9967
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1885 | top1:  95.6700 | top5:  99.9300
Epoch: [254 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0316 | top1:  98.9500 | top5:  99.9950
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1884 | top1:  95.4400 | top5:  99.9600
Epoch: [255 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:54 | ETA: 0:00:01 | Loss: 0.0302 | top1:  99.0100 | top5:  100.0000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1866 | top1:  95.5100 | top5:  99.9500
Epoch: [256 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.245s | Total: 0:01:54 | ETA: 0:00:01 | Loss: 0.0291 | top1:  99.0650 | top5:  100.0000
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1853 | top1:  95.6600 | top5:  99.9400
Epoch: [257 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0301 | top1:  99.0100 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1827 | top1:  95.6000 | top5:  99.9500
Epoch: [258 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.231s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0295 | top1:  99.0383 | top5:  100.0000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1844 | top1:  95.7100 | top5:  99.9800
Epoch: [259 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.246s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0290 | top1:  99.0267 | top5:  99.9917
Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1841 | top1:  95.6100 | top5:  99.9700
Epoch: [260 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.245s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0307 | top1:  98.9867 | top5:  99.9983
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Epoch: [271 | 300] LR: 0.001000
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Epoch: [272 | 300] LR: 0.001000
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Epoch: [273 | 300] LR: 0.001000
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Epoch: [274 | 300] LR: 0.001000
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Epoch: [276 | 300] LR: 0.001000
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Epoch: [277 | 300] LR: 0.001000
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Epoch: [278 | 300] LR: 0.001000
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Epoch: [279 | 300] LR: 0.001000
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Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1924 | top1:  95.6600 | top5:  99.9400
Epoch: [280 | 300] LR: 0.001000
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Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1945 | top1:  95.5500 | top5:  99.9400
Epoch: [281 | 300] LR: 0.001000
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Epoch: [282 | 300] LR: 0.001000
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Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1892 | top1:  95.7600 | top5:  99.9600
Epoch: [283 | 300] LR: 0.001000
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Epoch: [286 | 300] LR: 0.001000
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Epoch: [287 | 300] LR: 0.001000
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Epoch: [288 | 300] LR: 0.001000
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Epoch: [290 | 300] LR: 0.001000
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Epoch: [291 | 300] LR: 0.001000
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Epoch: [292 | 300] LR: 0.001000
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Epoch: [293 | 300] LR: 0.001000
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Epoch: [295 | 300] LR: 0.001000
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Epoch: [296 | 300] LR: 0.001000
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Processing |################################| (100/100) Data: 0.065s | Batch: 0.070s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1943 | top1:  95.5200 | top5:  99.9500
Epoch: [297 | 300] LR: 0.001000
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Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1941 | top1:  95.6200 | top5:  99.9600
Epoch: [298 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.232s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0239 | top1:  99.2350 | top5:  99.9983
Processing |################################| (100/100) Data: 0.065s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1980 | top1:  95.6500 | top5:  99.9600
Epoch: [299 | 300] LR: 0.001000
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Processing |################################| (100/100) Data: 0.066s | Batch: 0.070s | Total: 0:00:07 | ETA: 0:00:01 | Loss: 0.1886 | top1:  95.7300 | top5:  99.9700
Epoch: [300 | 300] LR: 0.001000
Processing |################################| (469/469) Data: 0.233s | Batch: 0.247s | Total: 0:01:55 | ETA: 0:00:01 | Loss: 0.0242 | top1:  99.1950 | top5:  100.0000
Processing |################################| (100/100) Data: 0.066s | Batch: 0.069s | Total: 0:00:06 | ETA: 0:00:01 | Loss: 0.1942 | top1:  95.7000 | top5:  99.9500
Best acc:
tensor(95.8000, device='cuda:0')
    opened by Atry 3
  • 实现与论文叙述不一致

    实现与论文叙述不一致

    看到您写的代码跟RandomResizeCrop很像，同时您的论文Algorithm 1中提到re = Rand(r1, r2), 可是实现代码中（transfrom.py）并没有r2，而是直接取了r1的倒数作为r2，RandomResizeCrop是上下限都可以设置的，想问一下，是不是有其他考虑？

    opened by mashuiping 2
  • RE-R in the paper

    RE-R in the paper

    Simple but effective, very interesting work! I wonder to which methods RE-R: erasing with random values corresponds; (1) region level randomization or (2) pixel level randomization.

    (1) img[2, x1:x1+h, y1:y1+w] = random.uniform(0, 1) (2) img[:, x1:x1+h, y1:y1+w] = torch.from_numpy(np.random.rand(3, h, w))

    Did you compare the two of them?

    opened by yu4u 2
  • Could you add a LICENSE.md?

    Could you add a LICENSE.md?

    @zhunzhong07 This repository looks very useful thanks for putting it up!

    Would you mind adding a license to this? Without a license it is impossible to legally clone or run this code. If you're not sure and would like a suggestion the Apache 2.0 license is a good option. A quick summary of apache 2.0 is available at tl;dr legal. This is the same license used by TensorFlow and it is compatible with the pytorch license. Here is the license text:

    Apache License, Version 2.0 Apache License Version 2.0, January 2004 http://www.apache.org/licenses/

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    opened by ahundt 1
  • InvalidArgumentError: ValueError: low >= high

    InvalidArgumentError: ValueError: low >= high

    Hi zhunzhong, I think there is a bug in you code, `for attempt in range(100): area = img.size()[1] * img.size()[2]

            target_area = random.uniform(self.sl, self.sh) * area
        aspect_ratio = random.uniform(self.r1, 1/self.r1)

        h = int(round(math.sqrt(target_area * aspect_ratio)))
        w = int(round(math.sqrt(target_area / aspect_ratio)))

        if w <= img.size()[2] and h <= img.size()[1]:
            x1 = random.randint(0, img.size()[1] - h)
            y1 = random.randint(0, img.size()[2] - w)
            if img.size()[0] == 3:
                img[0, x1:x1+h, y1:y1+w] = self.mean[0]
                img[1, x1:x1+h, y1:y1+w] = self.mean[1]
                img[2, x1:x1+h, y1:y1+w] = self.mean[2]
            else:
                img[0, x1:x1+h, y1:y1+w] = self.mean[0]
            return img`

    should it be "if w < img.size()[2] and h < img.size()[1]:"? Otherwise if h == img.size()[1], random.randint(0, img.size()[1] - h) will raise "ValueError: low >= high".

    opened by shllhs 1
  • All trained model

    All trained model

    Hi @zhunzhong07 Thanks for your amazing work. Can you sharing your trained models for CIFAR10, CIFAR100 and Imagenet? I want all these models for my research work.

    Thanks,

    opened by kmr2017 0
  • The resnet44/56/110 use BottleNeck，why n = (depth-2) // 6 ?

    The resnet44/56/110 use BottleNeck，why n = (depth-2) // 6 ?

    The resnet44/56/110 use BottleNeck，why n = (depth-2) // 6 ? The bottleNeck has three conv, for example the n of resnet44 is (44-2) // 6 = 7, if use bottleNeck, there are 21 convs in one stage(2-4), so it can't be resnet44!

    opened by b762927 0
  • Fashion-MNISST result update

    Fashion-MNISST result update

    Can you update the fashion-MNIST results in the paper or mention results in readme file? Mentioned results are inconsistent?

    or share fashion-MNIST dataset, on which you performed the experment?

    Thanks

    opened by TeerathChandani 0
Owner
Zhun Zhong
Zhun Zhong
GitHub
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