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 | 5e-05 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 959 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9755 |
| Val Accuracy | 0.8795 |
| Test Accuracy | 0.8760 |
The model was fine-tuned on the following 50 CIFAR100 classes:
aquarium_fish, sea, telephone, bicycle, chimpanzee, wolf, snake, elephant, lion, palm_tree, train, beaver, lamp, wardrobe, shark, road, turtle, bed, squirrel, house, hamster, tulip, rabbit, mouse, willow_tree, plain, porcupine, crocodile, spider, skunk, beetle, dinosaur, cloud, bowl, bus, possum, snail, pear, caterpillar, sunflower, trout, crab, poppy, oak_tree, worm, boy, maple_tree, pickup_truck, skyscraper, pine_tree
Base model
microsoft/resnet-101