Collections:
  - Name: SwAV
    Metadata:
      Training Data: ImageNet-1k
      Training Techniques:
        - LARS
      Training Resources: 8x V100 GPUs
      Architecture:
        - ResNet
        - SwAV
    Paper:
        URL: https://arxiv.org/abs/2006.09882
        Title: "Unsupervised Learning of Visual Features by Contrasting Cluster Assignments"
    README: configs/selfsup/swav/README.md

Models:
  - Name: swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96
    In Collection: SwAV
    Metadata:
      Epochs: 200
      Batch Size: 256
    Results:
      - Task: Self-Supervised Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 70.55
    Config: configs/selfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96.py
    Weights: https://download.openmmlab.com/mmselfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96_20211213-0028900c.pth