mmpretrain/configs/vgg/metafile.yml

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3.5 KiB
YAML

Collections:
- Name: VGG
Metadata:
Training Data: ImageNet
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x Xp GPUs
Epochs: 100
Batch Size: 256
Architecture:
- VGG
Paper: https://arxiv.org/abs/1409.1556
README: configs/vgg/README.md
Models:
- Config: configs/vgg/vgg11_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 7630000000
Parameters: 132860000
Name: vgg11_b32x8_imagenet
Results:
- Dataset: ImageNet
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/vgg13_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 11340000000
Parameters: 133050000
Name: vgg13_b32x8_imagenet
Results:
- Dataset: ImageNet
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/vgg16_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 15500000000
Parameters: 138360000
Name: vgg16_b32x8_imagenet
Results:
- Dataset: ImageNet
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/vgg19_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 19670000000
Parameters: 143670000
Name: vgg19_b32x8_imagenet
Results:
- Dataset: ImageNet
Metrics:
Top 1 Accuracy: 72.41
Top 5 Accuracy: 90.8
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg19_bn_batch256_imagenet_20210208-da620c4f.pth
- Config: configs/vgg/vgg11bn_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 7640000000
Parameters: 132870000
Name: vgg11bn_b32x8_imagenet
Results:
- Dataset: ImageNet
Metrics:
Top 1 Accuracy: 70.75
Top 5 Accuracy: 90.12
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg11_bn_batch256_imagenet_20210207-f244902c.pth
- Config: configs/vgg/vgg13bn_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 11360000000
Parameters: 133050000
Name: vgg13bn_b32x8_imagenet
Results:
- Dataset: ImageNet
Metrics:
Top 1 Accuracy: 72.15
Top 5 Accuracy: 90.71
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg13_bn_batch256_imagenet_20210207-1a8b7864.pth
- Config: configs/vgg/vgg16_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 15530000000
Parameters: 138370000
Name: vgg16_b32x8_imagenet
Results:
- Dataset: ImageNet
Metrics:
Top 1 Accuracy: 73.72
Top 5 Accuracy: 91.68
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg16_bn_batch256_imagenet_20210208-7e55cd29.pth
- Config: configs/vgg/vgg19bn_b32x8_imagenet.py
In Collection: VGG
Metadata:
FLOPs: 19700000000
Parameters: 143680000
Name: vgg19bn_b32x8_imagenet
Results:
- Dataset: ImageNet
Metrics:
Top 1 Accuracy: 74.7
Top 5 Accuracy: 92.24
Task: Image Classification
Weights: https://download.openmmlab.com/mmclassification/v0/vgg/vgg19_bn_batch256_imagenet_20210208-da620c4f.pth