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 | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 760 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9688 |
| Val Accuracy | 0.8760 |
| Test Accuracy | 0.8778 |
The model was fine-tuned on the following 50 CIFAR100 classes:
leopard, streetcar, aquarium_fish, castle, snail, chimpanzee, rose, sea, lobster, pear, wolf, plate, bridge, spider, sunflower, maple_tree, house, cattle, beaver, skyscraper, whale, ray, motorcycle, shrew, road, poppy, orange, tank, sweet_pepper, train, lawn_mower, crocodile, bear, orchid, bus, apple, table, cloud, bicycle, porcupine, man, can, girl, tractor, camel, lion, trout, squirrel, lamp, lizard
Base model
microsoft/resnet-101