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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 248 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.6058 |
| Val Accuracy | 0.5912 |
| Test Accuracy | 0.5968 |
The model was fine-tuned on the following 50 CIFAR100 classes:
sweet_pepper, couch, butterfly, poppy, pear, boy, wardrobe, orange, flatfish, whale, train, rose, crocodile, man, bottle, beaver, leopard, bicycle, ray, cockroach, skyscraper, mountain, tractor, hamster, lamp, lawn_mower, baby, cloud, television, forest, tiger, turtle, aquarium_fish, porcupine, lizard, bridge, clock, dolphin, streetcar, bed, crab, woman, chimpanzee, shark, plain, seal, shrew, skunk, oak_tree, dinosaur
Base model
microsoft/resnet-101