mmpretrain/configs/deit/metafile.yml

Collections:
  - Name: DeiT
    Metadata:
      Training Data: ImageNet-1k
      Architecture:
        - Layer Normalization
        - Scaled Dot-Product Attention
        - Attention Dropout
        - Multi-Head Attention
    Paper:
      URL: https://arxiv.org/abs/2012.12877
      Title: "Training data-efficient image transformers & distillation through attention"
    README: configs/deit/README.md

Models:
  - Name: deit-tiny_3rdparty_pt-4xb256_in1k
    Metadata:
      FLOPs: 1080000000
      Parameters: 5720000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 72.13
          Top 5 Accuracy: 91.13
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-tiny_3rdparty_pt-4xb256_in1k_20211124-e930093b.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_tiny_patch16_224-a1311bcf.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L63
    Config: configs/deit/deit-tiny_pt-4xb256_in1k.py
  - Name: deit-tiny-distilled_3rdparty_pt-4xb256_in1k
    Metadata:
      FLOPs: 1080000000
      Parameters: 5720000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 74.51
          Top 5 Accuracy: 91.90
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-tiny-distilled_3rdparty_pt-4xb256_in1k_20211216-c429839a.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_tiny_distilled_patch16_224-b40b3cf7.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L108
    Config: configs/deit/deit-tiny-distilled_pt-4xb256_in1k.py
  - Name: deit-small_3rdparty_pt-4xb256_in1k
    Metadata:
      FLOPs: 4240000000
      Parameters: 22050000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 79.83
          Top 5 Accuracy: 94.95
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-small_3rdparty_pt-4xb256_in1k_20211124-ffe94edd.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_small_patch16_224-cd65a155.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L78
    Config: configs/deit/deit-small_pt-4xb256_in1k.py
  - Name: deit-small-distilled_3rdparty_pt-4xb256_in1k
    Metadata:
      FLOPs: 4240000000
      Parameters: 22050000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 81.17
          Top 5 Accuracy: 95.40
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-small-distilled_3rdparty_pt-4xb256_in1k_20211216-4de1d725.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_small_distilled_patch16_224-649709d9.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L123
    Config: configs/deit/deit-small-distilled_pt-4xb256_in1k.py
  - Name: deit-base_3rdparty_pt-16xb64_in1k
    Metadata:
      FLOPs: 16860000000
      Parameters: 86570000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 81.79
          Top 5 Accuracy: 95.59
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_3rdparty_pt-16xb64_in1k_20211124-6f40c188.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_base_patch16_224-b5f2ef4d.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L93
    Config: configs/deit/deit-base_pt-16xb64_in1k.py
  - Name: deit-base-distilled_3rdparty_pt-16xb64_in1k
    Metadata:
      FLOPs: 16860000000
      Parameters: 86570000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 83.33
          Top 5 Accuracy: 96.49
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base-distilled_3rdparty_pt-16xb64_in1k_20211216-42891296.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_224-df68dfff.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L138
    Config: configs/deit/deit-base-distilled_pt-16xb64_in1k.py
  - Name: deit-base_3rdparty_ft-16xb32_in1k-384px
    Metadata:
      FLOPs: 49370000000
      Parameters: 86860000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 83.04
          Top 5 Accuracy: 96.31
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base_3rdparty_ft-16xb32_in1k-384px_20211124-822d02f2.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_base_patch16_384-8de9b5d1.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L153
    Config: configs/deit/deit-base_ft-16xb32_in1k-384px.py
  - Name: deit-base-distilled_3rdparty_ft-16xb32_in1k-384px
    Metadata:
      FLOPs: 49370000000
      Parameters: 86860000
    In Collection: DeiT
    Results:
      - Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 85.55
          Top 5 Accuracy: 97.35
        Task: Image Classification
    Weights: https://download.openmmlab.com/mmclassification/v0/deit/deit-base-distilled_3rdparty_ft-16xb32_in1k-384px_20211216-e48d6000.pth
    Converted From:
      Weights: https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_384-d0272ac0.pth
      Code: https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L168
    Config: configs/deit/deit-base-distilled_ft-16xb32_in1k-384px.py