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 | 9e-05 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 127 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9484 |
| Val Accuracy | 0.8877 |
| Test Accuracy | 0.8780 |
The model was fine-tuned on the following 50 CIFAR100 classes:
motorcycle, television, can, oak_tree, mushroom, aquarium_fish, cockroach, man, plain, bed, tulip, whale, sweet_pepper, lawn_mower, elephant, maple_tree, trout, skyscraper, boy, cup, pickup_truck, poppy, snake, skunk, fox, camel, hamster, butterfly, baby, lamp, apple, sunflower, otter, streetcar, telephone, orchid, beaver, kangaroo, couch, lobster, clock, plate, spider, crocodile, seal, tractor, house, worm, wardrobe, leopard
Base model
microsoft/resnet-101