78 lines
2.8 KiB
YAML
78 lines
2.8 KiB
YAML
Collections:
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- Name: Wide-ResNet
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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 V100 GPUs
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Epochs: 100
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Batch Size: 256
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Connection
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- Softmax
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- Wide Residual Block
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Paper:
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URL: https://arxiv.org/abs/1605.07146
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Title: "Wide Residual Networks"
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README: configs/wrn/README.md
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Code:
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URL: https://github.com/open-mmlab/mmpretrain/blob/v0.20.1/mmcls/models/backbones/resnet.py#L383
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Version: v0.20.1
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Models:
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- Name: wide-resnet50_3rdparty_8xb32_in1k
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Metadata:
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FLOPs: 11440000000 # 11.44G
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Parameters: 68880000 # 68.88M
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In Collection: Wide-ResNet
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Results:
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- Task: Image Classification
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Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 78.48
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Top 5 Accuracy: 94.08
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Weights: https://download.openmmlab.com/mmclassification/v0/wrn/wide-resnet50_3rdparty_8xb32_in1k_20220304-66678344.pth
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Config: configs/wrn/wide-resnet50_8xb32_in1k.py
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Converted From:
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Weights: https://download.pytorch.org/models/wide_resnet50_2-95faca4d.pth
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Code: https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py
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- Name: wide-resnet101_3rdparty_8xb32_in1k
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Metadata:
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FLOPs: 22810000000 # 22.81G
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Parameters: 126890000 # 126.89M
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In Collection: Wide-ResNet
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Results:
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- Task: Image Classification
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Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 78.84
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Top 5 Accuracy: 94.28
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Weights: https://download.openmmlab.com/mmclassification/v0/wrn/wide-resnet101_3rdparty_8xb32_in1k_20220304-8d5f9d61.pth
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Config: configs/wrn/wide-resnet101_8xb32_in1k.py
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Converted From:
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Weights: https://download.pytorch.org/models/wide_resnet101_2-32ee1156.pth
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Code: https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py
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- Name: wide-resnet50_3rdparty-timm_8xb32_in1k
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Metadata:
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FLOPs: 11440000000 # 11.44G
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Parameters: 68880000 # 68.88M
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In Collection: Wide-ResNet
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Results:
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- Task: Image Classification
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Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 81.45
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Top 5 Accuracy: 95.53
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Weights: https://download.openmmlab.com/mmclassification/v0/wrn/wide-resnet50_3rdparty-timm_8xb32_in1k_20220304-83ae4399.pth
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Config: configs/wrn/wide-resnet50_timm_8xb32_in1k.py
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Converted From:
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Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/wide_resnet50_racm-8234f177.pth
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Code: https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/resnet.py
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