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- Collections:
- - Name: VGG
- Metadata:
- Training Data: ImageNet-1k
- Training Techniques:
- - SGD with Momentum
- - Weight Decay
- Training Resources: 8x Xp GPUs
- Epochs: 100
- Batch Size: 256
- Architecture:
- - VGG
- Paper:
- URL: https://arxiv.org/abs/1409.1556
- Title: "Very Deep Convolutional Networks for Large-Scale Image Recognition"
- README: configs/vgg/README.md
- Code:
- URL: https://github.com/open-mmlab/mmpretrain/blob/v0.15.0/mmcls/models/backbones/vgg.py#L39
- Version: v0.15.0
- Models:
- - Name: vgg11_8xb32_in1k
- Metadata:
- FLOPs: 7630000000
- Parameters: 132860000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 68.75
- Top 5 Accuracy: 88.87
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg11_batch256_imagenet_20210208-4271cd6c.pth
- Config: configs/vgg/vgg11_8xb32_in1k.py
- - Name: vgg13_8xb32_in1k
- Metadata:
- FLOPs: 11340000000
- Parameters: 133050000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 70.02
- Top 5 Accuracy: 89.46
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg13_batch256_imagenet_20210208-4d1d6080.pth
- Config: configs/vgg/vgg13_8xb32_in1k.py
- - Name: vgg16_8xb32_in1k
- Metadata:
- FLOPs: 15500000000
- Parameters: 138360000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 71.62
- Top 5 Accuracy: 90.49
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg16_batch256_imagenet_20210208-db26f1a5.pth
- Config: configs/vgg/vgg16_8xb32_in1k.py
- - Name: vgg19_8xb32_in1k
- Metadata:
- FLOPs: 19670000000
- Parameters: 143670000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 72.41
- Top 5 Accuracy: 90.8
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg19_batch256_imagenet_20210208-e6920e4a.pth
- Config: configs/vgg/vgg19_8xb32_in1k.py
- - Name: vgg11bn_8xb32_in1k
- Metadata:
- FLOPs: 7640000000
- Parameters: 132870000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 70.67
- Top 5 Accuracy: 90.16
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg11_bn_batch256_imagenet_20210207-f244902c.pth
- Config: configs/vgg/vgg11bn_8xb32_in1k.py
- - Name: vgg13bn_8xb32_in1k
- Metadata:
- FLOPs: 11360000000
- Parameters: 133050000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 72.12
- Top 5 Accuracy: 90.66
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg13_bn_batch256_imagenet_20210207-1a8b7864.pth
- Config: configs/vgg/vgg13bn_8xb32_in1k.py
- - Name: vgg16bn_8xb32_in1k
- Metadata:
- FLOPs: 15530000000
- Parameters: 138370000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 73.74
- Top 5 Accuracy: 91.66
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg16_bn_batch256_imagenet_20210208-7e55cd29.pth
- Config: configs/vgg/vgg16bn_8xb32_in1k.py
- - Name: vgg19bn_8xb32_in1k
- Metadata:
- FLOPs: 19700000000
- Parameters: 143680000
- In Collection: VGG
- Results:
- - Dataset: ImageNet-1k
- Metrics:
- Top 1 Accuracy: 74.68
- Top 5 Accuracy: 92.27
- Task: Image Classification
- Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg19_bn_batch256_imagenet_20210208-da620c4f.pth
- Config: configs/vgg/vgg19bn_8xb32_in1k.py
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