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 | 0.0003 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 896 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9913 |
| Val Accuracy | 0.9096 |
| Test Accuracy | 0.9012 |
The model was fine-tuned on the following 50 CIFAR100 classes:
chimpanzee, crocodile, streetcar, rose, whale, skyscraper, dinosaur, apple, woman, cattle, poppy, tractor, bottle, lawn_mower, orange, shrew, bed, rabbit, tulip, raccoon, mountain, bear, lion, worm, rocket, lamp, snake, lobster, leopard, mushroom, caterpillar, ray, clock, camel, oak_tree, train, bee, castle, motorcycle, fox, television, lizard, plain, cockroach, can, sunflower, shark, turtle, bridge, trout
Base model
microsoft/resnet-101