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 | 0.0005 |
| LR Scheduler | constant |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 360 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9752 |
| Val Accuracy | 0.8677 |
| Test Accuracy | 0.8662 |
The model was fine-tuned on the following 50 CIFAR100 classes:
plain, ray, crab, bottle, bus, dinosaur, chair, motorcycle, telephone, girl, palm_tree, cockroach, tulip, cup, bowl, seal, house, baby, lawn_mower, pear, mountain, squirrel, flatfish, can, woman, kangaroo, wardrobe, clock, man, chimpanzee, aquarium_fish, caterpillar, tractor, rose, sweet_pepper, trout, orchid, streetcar, pickup_truck, lobster, worm, television, cloud, skyscraper, mouse, willow_tree, forest, lion, bear, poppy
Base model
microsoft/resnet-101