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 | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 435 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8576 |
| Val Accuracy | 0.8317 |
| Test Accuracy | 0.8254 |
The model was fine-tuned on the following 50 CIFAR100 classes:
castle, seal, couch, bowl, trout, hamster, ray, poppy, keyboard, orange, sea, clock, crocodile, mountain, mushroom, pear, possum, snake, television, sunflower, wolf, flatfish, chimpanzee, bed, cattle, rocket, bridge, road, orchid, rose, leopard, cockroach, lizard, skyscraper, raccoon, worm, dolphin, palm_tree, whale, snail, rabbit, lobster, chair, pine_tree, lawn_mower, train, man, skunk, plain, elephant
Base model
microsoft/resnet-101