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 | 344 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8682 |
| Val Accuracy | 0.8357 |
| Test Accuracy | 0.8260 |
The model was fine-tuned on the following 50 CIFAR100 classes:
chimpanzee, shark, leopard, flatfish, television, man, cattle, telephone, bridge, lamp, house, can, trout, mouse, bowl, possum, snail, cloud, tank, oak_tree, porcupine, raccoon, lobster, dinosaur, baby, spider, beaver, pear, crab, squirrel, worm, rocket, bicycle, train, plate, beetle, seal, dolphin, cockroach, turtle, girl, table, plain, forest, couch, mountain, streetcar, sea, lizard, wardrobe
Base model
microsoft/resnet-101