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 | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 77 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9777 |
| Val Accuracy | 0.8915 |
| Test Accuracy | 0.8794 |
The model was fine-tuned on the following 50 CIFAR100 classes:
mouse, lion, couch, crab, bridge, lawn_mower, plain, plate, tulip, keyboard, palm_tree, bicycle, trout, sunflower, apple, bowl, streetcar, baby, hamster, snake, leopard, can, pear, raccoon, cattle, willow_tree, television, maple_tree, chimpanzee, beetle, rabbit, train, aquarium_fish, lamp, rose, forest, pickup_truck, poppy, cup, motorcycle, mountain, bear, possum, turtle, bed, butterfly, lizard, bee, tank, bus
Base model
microsoft/resnet-101