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