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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 819 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9785 |
| Val Accuracy | 0.8819 |
| Test Accuracy | 0.8844 |
The model was fine-tuned on the following 50 CIFAR100 classes:
clock, boy, chimpanzee, couch, bridge, snail, beetle, table, porcupine, wardrobe, lion, rose, worm, skyscraper, shrew, snake, baby, flatfish, house, elephant, fox, otter, lawn_mower, television, crab, skunk, bee, orange, palm_tree, turtle, mushroom, bed, sea, mouse, raccoon, pine_tree, tulip, plain, shark, willow_tree, ray, oak_tree, tractor, pickup_truck, spider, cattle, orchid, can, aquarium_fish, camel
Base model
microsoft/resnet-101