Collections:
  - Name: Tokens-to-Token ViT
    Metadata:
      Training Data: ImageNet-1k
      Architecture:
        - Layer Normalization
        - Scaled Dot-Product Attention
        - Attention Dropout
        - Dropout
        - Tokens to Token
    Paper:
      URL: https://arxiv.org/abs/2101.11986
      Title: "Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet"
    README: configs/t2t_vit/README.md
    Code:
      URL: https://github.com/open-mmlab/mmpretrain/blob/v0.17.0/mmcls/models/backbones/t2t_vit.py
      Version: v0.17.0

Models:
  - Name: t2t-vit-t-14_8xb64_in1k
    Metadata:
      FLOPs: 4340000000
      Parameters: 21470000
    In Collection: Tokens-to-Token ViT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 81.83
          Top 5 Accuracy: 95.84
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-14_8xb64_in1k_20211220-f7378dd5.pth
    Config: configs/t2t_vit/t2t-vit-t-14_8xb64_in1k.py
  - Name: t2t-vit-t-19_8xb64_in1k
    Metadata:
      FLOPs: 7800000000
      Parameters: 39080000
    In Collection: Tokens-to-Token ViT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 82.63
          Top 5 Accuracy: 96.18
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-19_8xb64_in1k_20211214-7f5e3aaf.pth
    Config: configs/t2t_vit/t2t-vit-t-19_8xb64_in1k.py
  - Name: t2t-vit-t-24_8xb64_in1k
    Metadata:
      FLOPs: 12690000000
      Parameters: 64000000
    In Collection: Tokens-to-Token ViT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 82.71
          Top 5 Accuracy: 96.09
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/t2t-vit/t2t-vit-t-24_8xb64_in1k_20211214-b2a68ae3.pth
    Config: configs/t2t_vit/t2t-vit-t-24_8xb64_in1k.py
