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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 527 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.6660 |
| Val Accuracy | 0.6536 |
| Test Accuracy | 0.6544 |
The model was fine-tuned on the following 50 CIFAR100 classes:
mountain, bus, plain, clock, wardrobe, cloud, boy, snail, turtle, bridge, chair, seal, train, orange, lamp, table, aquarium_fish, skyscraper, house, bowl, raccoon, wolf, sunflower, cattle, man, possum, caterpillar, fox, oak_tree, beaver, pine_tree, castle, lion, hamster, streetcar, spider, forest, lawn_mower, rocket, lobster, mushroom, television, tiger, mouse, porcupine, rabbit, worm, poppy, leopard, keyboard
Base model
microsoft/resnet-101