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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 402 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9296 |
| Val Accuracy | 0.8659 |
| Test Accuracy | 0.8672 |
The model was fine-tuned on the following 50 CIFAR100 classes:
baby, apple, orchid, wardrobe, lamp, maple_tree, poppy, bottle, lion, lobster, streetcar, ray, castle, tulip, beaver, couch, rose, palm_tree, road, wolf, pear, motorcycle, sunflower, cup, dolphin, rocket, lizard, kangaroo, can, sweet_pepper, woman, keyboard, whale, turtle, plain, willow_tree, caterpillar, snail, fox, beetle, leopard, shrew, tractor, trout, bear, man, skunk, shark, dinosaur, hamster
Base model
microsoft/resnet-101