Collections:
  - Name: SimMIM
    Metadata:
      Training Data: ImageNet-1k
      Training Techniques:
        - AdamW
      Training Resources: 16x A100 GPUs
      Architecture:
        - Swin
        - ViT
    Paper:
        URL: https://arxiv.org/abs/2111.09886
        Title: "SimMIM: A Simple Framework for Masked Image Modeling"
    README: configs/selfsup/simmim/README.md

Models:
  - Name: simmim_swin-base_8xb256-coslr-100e_in1k-192
    In Collection: SimMIM
    Metadata:
      Epochs: 100
      Batch Size: 2048
    Results:
      - Task: Self-Supervised Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 82.9
    Config: configs/selfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192.py
    Weights: https://download.openmmlab.com/mmselfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192_20220316-1d090125.pth
