Model-J ResNet
Collection
1001 items
โข
Updated
This model is part of the Model-J dataset, introduced in:
Learning on Model Weights using Tree Experts (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
๐ Project | ๐ Paper | ๐ป GitHub | ๐ค Dataset
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 767 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9834 |
| Val Accuracy | 0.8909 |
| Test Accuracy | 0.8868 |
The model was fine-tuned on the following 50 CIFAR100 classes:
poppy, bed, motorcycle, leopard, lobster, orange, rabbit, tulip, seal, hamster, rocket, snake, flatfish, caterpillar, plain, shrew, boy, sea, lion, lamp, table, streetcar, sunflower, wolf, aquarium_fish, tank, fox, clock, beaver, beetle, crab, whale, lawn_mower, television, ray, bowl, dolphin, elephant, couch, turtle, cloud, castle, crocodile, bridge, house, dinosaur, tiger, man, tractor, bottle
Base model
microsoft/resnet-101