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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 35 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9178 |
| Val Accuracy | 0.8587 |
| Test Accuracy | 0.8670 |
The model was fine-tuned on the following 50 CIFAR100 classes:
ray, girl, hamster, train, butterfly, palm_tree, dolphin, lion, lizard, squirrel, possum, sunflower, tulip, flatfish, beetle, poppy, crocodile, fox, bee, leopard, snail, rabbit, worm, tiger, skunk, can, trout, orchid, wolf, mushroom, kangaroo, pine_tree, lobster, forest, rose, baby, cloud, snake, cockroach, lawn_mower, aquarium_fish, dinosaur, mountain, bridge, tank, road, lamp, turtle, bear, shark
Base model
microsoft/resnet-101