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Update README.md #48

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93 changes: 45 additions & 48 deletions README.md
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Expand Up @@ -134,51 +134,48 @@ You can choose whether to use TensorBoard to visualize your training procedure
The result I can get from a certain model, since I use the same hyperparameters to train all the networks, some networks might not get the best result from these hyperparameters, you could try yourself by finetuning the hyperparameters to get
better result.

|dataset|network|params|top1 err|top5 err|epoch(lr = 0.1)|epoch(lr = 0.02)|epoch(lr = 0.004)|epoch(lr = 0.0008)|total epoch|
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:
|cifar100|mobilenet|3.3M|34.02|10.56|60|60|40|40|200|
|cifar100|mobilenetv2|2.36M|31.92|09.02|60|60|40|40|200|
|cifar100|squeezenet|0.78M|30.59|8.36|60|60|40|40|200|
|cifar100|shufflenet|1.0M|29.94|8.35|60|60|40|40|200|
|cifar100|shufflenetv2|1.3M|30.49|8.49|60|60|40|40|200|
|cifar100|vgg11_bn|28.5M|31.36|11.85|60|60|40|40|200|
|cifar100|vgg13_bn|28.7M|28.00|9.71|60|60|40|40|200|
|cifar100|vgg16_bn|34.0M|27.07|8.84|60|60|40|40|200|
|cifar100|vgg19_bn|39.0M|27.77|8.84|60|60|40|40|200|
|cifar100|resnet18|11.2M|24.39|6.95|60|60|40|40|200|
|cifar100|resnet34|21.3M|23.24|6.63|60|60|40|40|200|
|cifar100|resnet50|23.7M|22.61|6.04|60|60|40|40|200|
|cifar100|resnet101|42.7M|22.22|5.61|60|60|40|40|200|
|cifar100|resnet152|58.3M|22.31|5.81|60|60|40|40|200|
|cifar100|preactresnet18|11.3M|27.08|8.53|60|60|40|40|200|
|cifar100|preactresnet34|21.5M|24.79|7.68|60|60|40|40|200|
|cifar100|preactresnet50|23.9M|25.73|8.15|60|60|40|40|200|
|cifar100|preactresnet101|42.9M|24.84|7.83|60|60|40|40|200|
|cifar100|preactresnet152|58.6M|22.71|6.62|60|60|40|40|200|
|cifar100|resnext50|14.8M|22.23|6.00|60|60|40|40|200|
|cifar100|resnext101|25.3M|22.22|5.99|60|60|40|40|200|
|cifar100|resnext152|33.3M|22.40|5.58|60|60|40|40|200|
|cifar100|attention59|55.7M|33.75|12.90|60|60|40|40|200|
|cifar100|attention92|102.5M|36.52|11.47|60|60|40|40|200|
|cifar100|densenet121|7.0M|22.99|6.45|60|60|40|40|200|
|cifar100|densenet161|26M|21.56|6.04|60|60|60|40|200|
|cifar100|densenet201|18M|21.46|5.9|60|60|40|40|200|
|cifar100|googlenet|6.2M|21.97|5.94|60|60|40|40|200|
|cifar100|inceptionv3|22.3M|22.81|6.39|60|60|40|40|200|
|cifar100|inceptionv4|41.3M|24.14|6.90|60|60|40|40|200|
|cifar100|inceptionresnetv2|65.4M|27.51|9.11|60|60|40|40|200|
|cifar100|xception|21.0M|25.07|7.32|60|60|40|40|200|
|cifar100|seresnet18|11.4M|23.56|6.68|60|60|40|40|200|
|cifar100|seresnet34|21.6M|22.07|6.12|60|60|40|40|200|
|cifar100|seresnet50|26.5M|21.42|5.58|60|60|40|40|200|
|cifar100|seresnet101|47.7M|20.98|5.41|60|60|40|40|200|
|cifar100|seresnet152|66.2M|20.66|5.19|60|60|40|40|200|
|cifar100|nasnet|5.2M|22.71|5.91|60|60|40|40|200|
|cifar100|wideresnet-40-10|55.9M|21.25|5.77|60|60|40|40|200|
|cifar100|stochasticdepth18|11.22M|31.40|8.84|60|60|40|40|200|
|cifar100|stochasticdepth34|21.36M|27.72|7.32|60|60|40|40|200|
|cifar100|stochasticdepth50|23.71M|23.35|5.76|60|60|40|40|200|
|cifar100|stochasticdepth101|42.69M|21.28|5.39|60|60|40|40|200|



| dataset | network | params | top1 err | top5 err | epoch(lr = 0.1) | epoch(lr = 0.02) | epoch(lr = 0.004) | epoch(lr = 0.0008) | total epoch |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| cifar100 | mobilenet | 3.3M | 34.02 | 10.56 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | mobilenetv2 | 2.36M | 31.92 | 09.02 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | squeezenet | 0.78M | 30.59 | 8.36 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | shufflenet | 1.0M | 29.94 | 8.35 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | shufflenetv2 | 1.3M | 30.49 | 8.49 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | vgg11_bn | 28.5M | 31.36 | 11.85 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | vgg13_bn | 28.7M | 28.00 | 9.71 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | vgg16_bn | 34.0M | 27.07 | 8.84 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | vgg19_bn | 39.0M | 27.77 | 8.84 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnet18 | 11.2M | 24.39 | 6.95 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnet34 | 21.3M | 23.24 | 6.63 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnet50 | 23.7M | 22.61 | 6.04 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnet101 | 42.7M | 22.22 | 5.61 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnet152 | 58.3M | 22.31 | 5.81 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | preactresnet18 | 11.3M | 27.08 | 8.53 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | preactresnet34 | 21.5M | 24.79 | 7.68 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | preactresnet50 | 23.9M | 25.73 | 8.15 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | preactresnet101 | 42.9M | 24.84 | 7.83 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | preactresnet152 | 58.6M | 22.71 | 6.62 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnext50 | 14.8M | 22.23 | 6.00 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnext101 | 25.3M | 22.22 | 5.99 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | resnext152 | 33.3M | 22.40 | 5.58 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | attention59 | 55.7M | 33.75 | 12.90 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | attention92 | 102.5M | 36.52 | 11.47 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | densenet121 | 7.0M | 22.99 | 6.45 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | densenet161 | 26M | 21.56 | 6.04 | 60 | 60 | 60 | 40 | 200 |
| cifar100 | densenet201 | 18M | 21.46 | 5.9 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | googlenet | 6.2M | 21.97 | 5.94 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | inceptionv3 | 22.3M | 22.81 | 6.39 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | inceptionv4 | 41.3M | 24.14 | 6.90 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | inceptionresnetv2 | 65.4M | 27.51 | 9.11 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | xception | 21.0M | 25.07 | 7.32 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | seresnet18 | 11.4M | 23.56 | 6.68 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | seresnet34 | 21.6M | 22.07 | 6.12 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | seresnet50 | 26.5M | 21.42 | 5.58 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | seresnet101 | 47.7M | 20.98 | 5.41 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | seresnet152 | 66.2M | 20.66 | 5.19 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | nasnet | 5.2M | 22.71 | 5.91 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | wideresnet-40-10 | 55.9M | 21.25 | 5.77 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | stochasticdepth18 | 11.22M | 31.40 | 8.84 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | stochasticdepth34 | 21.36M | 27.72 | 7.32 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | stochasticdepth50 | 23.71M | 23.35 | 5.76 | 60 | 60 | 40 | 40 | 200 |
| cifar100 | stochasticdepth101 | 42.69M | 21.28 | 5.39 | 60 | 60 | 40 | 40 | 200 |