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