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_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 777 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8331 |
| Val Accuracy | 0.8131 |
| Test Accuracy | 0.8104 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cup, sweet_pepper, trout, porcupine, castle, poppy, mushroom, beetle, turtle, snake, crocodile, house, woman, hamster, ray, fox, chimpanzee, forest, kangaroo, baby, bottle, can, willow_tree, girl, tiger, spider, lizard, raccoon, bowl, lobster, cattle, flatfish, oak_tree, pickup_truck, lion, tractor, bicycle, caterpillar, tulip, skunk, mountain, bear, orchid, man, road, couch, aquarium_fish, telephone, beaver, train
Base model
microsoft/resnet-101