Model card
ResNet-50.
Microsoftopen-source25M paramsCNNMIT
76-80% on ImageNet depending on training. Standard baseline.
§ 02 · Benchmarks
Every benchmark ResNet-50 has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | CIFAR-10 | Computer Vision · Image Classification | accuracy | 96.0% | #7 | — | source ↗ |
| 02 | CIFAR-100 | Computer Vision · Image Classification | accuracy | 78.0% | #10 | — | source ↗ |
| 03 | ImageNet-1K | Computer Vision · Image Classification | top-1-accuracy | 76.2% | #20 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 05 · Related models
Other Microsoft models scored on Codesota.
§ 06 · Sources & freshness
Where these numbers come from.
cutout-paper
2
results
pytorch-vision
1
result
0 of 3 rows marked verified.