X_SSL_Net/tmp/VMamba-main/analyze/mmpretrain_configs/configs/mocov3/metafile.yml

Collections:
  - Name: MoCoV3
    Metadata:
      Training Data: ImageNet-1k
      Training Techniques:
        - LARS
      Training Resources: 32x V100 GPUs
      Architecture:
        - ResNet
        - ViT
        - MoCo
    Paper:
      Title: An Empirical Study of Training Self-Supervised Vision Transformers
      URL: https://arxiv.org/abs/2104.02057
    README: configs/mocov3/README.md

Models:
  - Name: mocov3_resnet50_8xb512-amp-coslr-100e_in1k
    Metadata:
      Epochs: 100
      Batch Size: 4096
      FLOPs: 4109364224
      Parameters: 68012160
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results: null
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/mocov3_resnet50_8xb512-amp-coslr-100e_in1k_20220927-f1144efa.pth
    Config: configs/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k.py
    Downstream:
      - resnet50_mocov3-100e-pre_8xb128-linear-coslr-90e_in1k
  - Name: mocov3_resnet50_8xb512-amp-coslr-300e_in1k
    Metadata:
      Epochs: 300
      Batch Size: 4096
      FLOPs: 4109364224
      Parameters: 68012160
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results: null
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/mocov3_resnet50_8xb512-amp-coslr-300e_in1k_20220927-1e4f3304.pth
    Config: configs/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k.py
    Downstream:
      - resnet50_mocov3-300e-pre_8xb128-linear-coslr-90e_in1k
  - Name: mocov3_resnet50_8xb512-amp-coslr-800e_in1k
    Metadata:
      Epochs: 800
      Batch Size: 4096
      FLOPs: 4109364224
      Parameters: 68012160
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results: null
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/mocov3_resnet50_8xb512-amp-coslr-800e_in1k_20220927-e043f51a.pth
    Config: configs/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k.py
    Downstream:
      - resnet50_mocov3-800e-pre_8xb128-linear-coslr-90e_in1k
  - Name: resnet50_mocov3-100e-pre_8xb128-linear-coslr-90e_in1k
    Metadata:
      Epochs: 90
      Batch Size: 1024
      FLOPs: 4109464576
      Parameters: 25557032
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 69.6
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-100e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-8f7d937e.pth
    Config: configs/mocov3/benchmarks/resnet50_8xb128-linear-coslr-90e_in1k.py
  - Name: resnet50_mocov3-300e-pre_8xb128-linear-coslr-90e_in1k
    Metadata:
      Epochs: 90
      Batch Size: 1024
      FLOPs: 4109464576
      Parameters: 25557032
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 72.8
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-300e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-d21ddac2.pth
    Config: configs/mocov3/benchmarks/resnet50_8xb128-linear-coslr-90e_in1k.py
  - Name: resnet50_mocov3-800e-pre_8xb128-linear-coslr-90e_in1k
    Metadata:
      Epochs: 90
      Batch Size: 1024
      FLOPs: 4109464576
      Parameters: 25557032
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 74.4
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_resnet50_8xb512-amp-coslr-800e_in1k/resnet50_linear-8xb128-coslr-90e_in1k/resnet50_linear-8xb128-coslr-90e_in1k_20220927-0e97a483.pth
    Config: configs/mocov3/benchmarks/resnet50_8xb128-linear-coslr-90e_in1k.py
  - Name: mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k
    Metadata:
      Epochs: 300
      Batch Size: 4096
      FLOPs: 4607954304
      Parameters: 84266752
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results: null
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k-224_20220826-08bc52f7.pth
    Config: configs/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k.py
    Downstream:
      - vit-small-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
  - Name: vit-small-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
    Metadata:
      Epochs: 90
      Batch Size: 1024
      FLOPs: 4607954304
      Parameters: 22050664
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 73.6
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k/vit-small-p16_linear-8xb128-coslr-90e_in1k_20220826-376674ef.pth
    Config: configs/mocov3/benchmarks/vit-small-p16_8xb128-linear-coslr-90e_in1k.py
  - Name: mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k
    Metadata:
      Epochs: 300
      Batch Size: 4096
      FLOPs: 17581972224
      Parameters: 215678464
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results: null
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k-224_20220826-25213343.pth
    Config: configs/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k.py
    Downstream:
      - vit-base-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
      - vit-base-p16_mocov3-pre_8xb64-coslr-150e_in1k
  - Name: vit-base-p16_mocov3-pre_8xb64-coslr-150e_in1k
    Metadata:
      Epochs: 150
      Batch Size: 512
      FLOPs: 17581972224
      Parameters: 86567656
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 83.0
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k/vit-base-p16_ft-8xb64-coslr-150e_in1k_20220826-f1e6c442.pth
    Config: configs/mocov3/benchmarks/vit-base-p16_8xb64-coslr-150e_in1k.py
  - Name: vit-base-p16_mocov3-pre_8xb128-linear-coslr-90e_in1k
    Metadata:
      Epochs: 90
      Batch Size: 1024
      FLOPs: 17581972224
      Parameters: 86567656
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 76.9
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-base-p16_16xb256-amp-coslr-300e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k/vit-base-p16_linear-8xb128-coslr-90e_in1k_20220826-83be7758.pth
    Config: configs/mocov3/benchmarks/vit-base-p16_8xb128-linear-coslr-90e_in1k.py
  - Name: mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k
    Metadata:
      Epochs: 300
      Batch Size: 4096
      FLOPs: 61603111936
      Parameters: 652781568
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results: null
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k-224_20220829-9b88a442.pth
    Config: configs/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k.py
    Downstream:
      - vit-large-p16_mocov3-pre_8xb64-coslr-100e_in1k
  - Name: vit-large-p16_mocov3-pre_8xb64-coslr-100e_in1k
    Metadata:
      Epochs: 100
      Batch Size: 512
      FLOPs: 61603111936
      Parameters: 304326632
      Training Data: ImageNet-1k
    In Collection: MoCoV3
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 83.7
    Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov3/mocov3_vit-large-p16_64xb64-amp-coslr-300e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k/vit-large-p16_ft-8xb64-coslr-100e_in1k_20220829-878a2f7f.pth
    Config: configs/mocov3/benchmarks/vit-large-p16_8xb64-coslr-100e_in1k.py