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

Collections:
  - Name: MILAN
    Metadata:
      Training Data: ImageNet-1k
      Training Techniques:
        - AdamW
      Training Resources: 16x A100-80G GPUs
      Architecture:
        - ViT
    Paper:
      Title: 'MILAN: Masked Image Pretraining on Language Assisted Representation'
      URL: https://arxiv.org/pdf/2208.06049
    README: configs/milan/README.md

Models:
  - Name: milan_vit-base-p16_16xb256-amp-coslr-400e_in1k
    Metadata:
      Epochs: 400
      Batch Size: 4096
      FLOPs: 17581972224
      Parameters: 111907584
      Training Data: ImageNet-1k
    In Collection: MILAN
    Results: null
    Weights: https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k_20221129-180922e8.pth
    Config: configs/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k.py
    Downstream:
      - vit-base-p16_milan-pre_8xb128-coslr-100e_in1k
      - vit-base-p16_milan-pre_8xb2048-linear-coslr-100e_in1k
  - Name: vit-base-p16_milan-pre_8xb128-coslr-100e_in1k
    Metadata:
      Epochs: 100
      Batch Size: 1024
      FLOPs: 17581215744
      Parameters: 86566120
      Training Data: ImageNet-1k
    In Collection: MILAN
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 85.3
    Weights: https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k-milan_20221129-74ac94fa.pth
    Config: configs/milan/benchmarks/vit-base-p16_8xb128-coslr-100e_in1k.py
  - Name: vit-base-p16_milan-pre_8xb2048-linear-coslr-100e_in1k
    Metadata:
      Epochs: 100
      Batch Size: 16384
      FLOPs: 17581972992
      Parameters: 86567656
      Training Data: ImageNet-1k
    In Collection: MILAN
    Results:
      - Task: Image Classification
        Dataset: ImageNet-1k
        Metrics:
          Top 1 Accuracy: 78.9
    Weights: https://download.openmmlab.com/mmselfsup/1.x/milan/milan_vit-base-p16_16xb256-amp-coslr-400e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k/vit-base-p16_linear-8xb2048-coslr-100e_in1k_20221129-03f26f85.pth
    Config: configs/milan/benchmarks/vit-base-p16_8xb2048-linear-coslr-100e_in1k.py