metafile.yml

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