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Models/ConvNeXt-XL (Im21k, 384)

ConvNeXt-XL (Im21k, 384)

Reported on 6 benchmarks across 2 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology3 results

  • Domain AdaptationonImageNet-R
    Top-1 Error Rate· uses extra data· 2022-01-10
    31.8
    best: 3.9 (Model soups (BASIC-L))
    SOTA
    A ConvNet for the 2020sarXiv:2201.03545
  • Domain AdaptationonImageNet-Sketch
    Top-1 accuracy· uses extra data· 2022-01-10
    55
    best: 77.18 (Model soups (BASIC-L))
    SOTA
    A ConvNet for the 2020sarXiv:2201.03545
  • Domain AdaptationonImageNet-A
    Top-1 accuracy %· uses extra data· 2022-01-10
    69.3
    best: 94.17 (Model soups (BASIC-L))
    A ConvNet for the 2020sarXiv:2201.03545

Computer Vision3 results

  • Domain GeneralizationonImageNet-R
    Top-1 Error Rate· uses extra data· 2022-01-10
    31.8
    best: 3.9 (Model soups (BASIC-L))
    SOTA
    A ConvNet for the 2020sarXiv:2201.03545
  • Domain GeneralizationonImageNet-Sketch
    Top-1 accuracy· uses extra data· 2022-01-10
    55
    best: 77.18 (Model soups (BASIC-L))
    SOTA
    A ConvNet for the 2020sarXiv:2201.03545
  • Domain GeneralizationonImageNet-A
    Top-1 accuracy %· uses extra data· 2022-01-10
    69.3
    best: 94.17 (Model soups (BASIC-L))
    A ConvNet for the 2020sarXiv:2201.03545