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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 199 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9877 |
| Val Accuracy | 0.8899 |
| Test Accuracy | 0.8882 |
The model was fine-tuned on the following 50 CIFAR100 classes:
television, rocket, aquarium_fish, telephone, bus, bed, tank, beaver, crocodile, seal, wardrobe, chimpanzee, maple_tree, chair, cup, tulip, shrew, lobster, hamster, couch, leopard, cattle, clock, willow_tree, fox, train, boy, orchid, palm_tree, sweet_pepper, skyscraper, otter, wolf, road, motorcycle, elephant, bear, bridge, skunk, pickup_truck, beetle, camel, cockroach, possum, ray, bottle, house, man, poppy, worm
Base model
microsoft/resnet-101