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 | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 262 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8319 |
| Val Accuracy | 0.8011 |
| Test Accuracy | 0.8048 |
The model was fine-tuned on the following 50 CIFAR100 classes:
crocodile, flatfish, seal, lawn_mower, shrew, rocket, man, pear, snake, chair, oak_tree, snail, orchid, tulip, spider, couch, dinosaur, maple_tree, bicycle, telephone, beetle, woman, palm_tree, bed, baby, cup, plate, ray, lizard, lobster, streetcar, porcupine, whale, dolphin, leopard, kangaroo, bowl, tractor, cattle, willow_tree, sunflower, orange, forest, house, poppy, boy, clock, road, pickup_truck, lion
Base model
microsoft/resnet-101