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 | 0.0003 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 214 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9840 |
| Val Accuracy | 0.8848 |
| Test Accuracy | 0.8788 |
The model was fine-tuned on the following 50 CIFAR100 classes:
snake, chair, rose, cup, apple, wolf, train, elephant, pine_tree, snail, tractor, fox, skunk, boy, butterfly, spider, dolphin, aquarium_fish, shark, kangaroo, poppy, beaver, house, chimpanzee, dinosaur, bowl, pear, bicycle, mushroom, cloud, otter, road, forest, lobster, tulip, tiger, wardrobe, rabbit, flatfish, camel, woman, cattle, man, whale, mouse, palm_tree, sunflower, leopard, trout, orchid
Base model
microsoft/resnet-101