ResNet-152x2-SAM

Reported on 5 benchmarks across 3 tasks · 1 paper

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

Computer Vision3 results

Image ClassificationonImageNet V2
Top 1 Accuracy· uses extra data· 2021-06-03
69.6
best: 84.63 (Model soups (BASIC-L))
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations arXiv:2106.01548
Domain GeneralizationonImageNet-R
Top-1 Error Rate· 2021-06-03
71.9
best: 3.9 (Model soups (BASIC-L))
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations arXiv:2106.01548
Domain GeneralizationonImageNet-C
Top 1 Accuracy· 2021-06-03
55
best: 73.6 (FAN-L-Hybrid (IN-22k))
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations arXiv:2106.01548

Methodology2 results

Domain AdaptationonImageNet-R
Top-1 Error Rate· 2021-06-03
71.9
best: 3.9 (Model soups (BASIC-L))
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations arXiv:2106.01548
Domain AdaptationonImageNet-C
Top 1 Accuracy· 2021-06-03
55
best: 73.6 (FAN-L-Hybrid (IN-22k))
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations arXiv:2106.01548