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 | 0.0003 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 379 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9262 |
| Val Accuracy | 0.8840 |
| Test Accuracy | 0.8720 |
The model was fine-tuned on the following 50 CIFAR100 classes:
shark, possum, beaver, bed, train, maple_tree, sweet_pepper, squirrel, beetle, lion, spider, chair, road, clock, house, tractor, rocket, leopard, porcupine, lamp, tank, aquarium_fish, bowl, elephant, sunflower, chimpanzee, rose, willow_tree, couch, bridge, fox, streetcar, wolf, worm, snail, bicycle, lizard, butterfly, shrew, motorcycle, crocodile, can, plate, otter, baby, tiger, oak_tree, boy, flatfish, cattle
Base model
microsoft/resnet-101