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 | 3e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 37 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.6304 |
| Val Accuracy | 0.6176 |
| Test Accuracy | 0.6274 |
The model was fine-tuned on the following 50 CIFAR100 classes:
willow_tree, bus, maple_tree, plate, dinosaur, bottle, orange, tulip, house, bed, rocket, lobster, mountain, lamp, boy, oak_tree, skunk, telephone, flatfish, lizard, orchid, streetcar, bear, rabbit, baby, elephant, lawn_mower, beetle, squirrel, cloud, wardrobe, keyboard, snail, tractor, clock, bicycle, cockroach, tank, sunflower, pickup_truck, wolf, chair, crocodile, raccoon, whale, bee, rose, motorcycle, ray, dolphin
Base model
microsoft/resnet-101