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 | 7e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 597 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9319 |
| Val Accuracy | 0.8776 |
| Test Accuracy | 0.8746 |
The model was fine-tuned on the following 50 CIFAR100 classes:
maple_tree, tulip, fox, tractor, cockroach, lamp, streetcar, bear, flatfish, butterfly, bridge, palm_tree, cup, clock, mountain, skunk, otter, wardrobe, house, television, castle, sweet_pepper, wolf, porcupine, keyboard, tank, beaver, can, couch, elephant, bee, beetle, apple, squirrel, pine_tree, aquarium_fish, mouse, rabbit, forest, sea, snake, cattle, lizard, caterpillar, bowl, man, turtle, ray, road, dolphin
Base model
microsoft/resnet-101