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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 154 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9302 |
| Val Accuracy | 0.8549 |
| Test Accuracy | 0.8548 |
The model was fine-tuned on the following 50 CIFAR100 classes:
woman, crocodile, man, bus, chair, tiger, lobster, lizard, squirrel, forest, dolphin, tank, leopard, pine_tree, spider, willow_tree, lawn_mower, hamster, orange, motorcycle, caterpillar, pear, possum, bee, lion, apple, mouse, boy, cup, shark, crab, fox, road, chimpanzee, turtle, beaver, oak_tree, snake, wolf, ray, worm, porcupine, tulip, maple_tree, bear, keyboard, snail, mountain, castle, wardrobe
Base model
microsoft/resnet-101