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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 730 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8305 |
| Val Accuracy | 0.7960 |
| Test Accuracy | 0.7908 |
The model was fine-tuned on the following 50 CIFAR100 classes:
palm_tree, bus, plain, flatfish, house, cup, aquarium_fish, tractor, sweet_pepper, spider, keyboard, bicycle, road, rose, castle, camel, oak_tree, mountain, plate, otter, rocket, train, beetle, bee, shrew, chimpanzee, whale, kangaroo, lobster, willow_tree, cloud, forest, crocodile, rabbit, ray, shark, tiger, tulip, baby, snake, man, mushroom, lizard, boy, lawn_mower, lion, sunflower, clock, porcupine, sea
Base model
microsoft/resnet-101