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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 17 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9732 |
| Val Accuracy | 0.8787 |
| Test Accuracy | 0.8754 |
The model was fine-tuned on the following 50 CIFAR100 classes:
trout, boy, bear, mountain, whale, aquarium_fish, snail, skyscraper, otter, squirrel, bee, elephant, apple, plain, train, man, lobster, motorcycle, shark, pickup_truck, sunflower, wolf, lawn_mower, leopard, dinosaur, television, road, cloud, table, sweet_pepper, cattle, rose, house, bridge, crocodile, telephone, rabbit, seal, maple_tree, snake, bowl, tulip, wardrobe, orchid, crab, porcupine, lizard, tiger, willow_tree, shrew
Base model
microsoft/resnet-101