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 | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 342 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9900 |
| Val Accuracy | 0.9139 |
| Test Accuracy | 0.9100 |
The model was fine-tuned on the following 50 CIFAR100 classes:
orchid, shrew, telephone, pine_tree, flatfish, sweet_pepper, lobster, woman, willow_tree, spider, poppy, cockroach, rabbit, house, wardrobe, hamster, tiger, keyboard, palm_tree, mushroom, bottle, skunk, trout, dolphin, rocket, castle, chimpanzee, raccoon, possum, oak_tree, bicycle, clock, bear, motorcycle, mouse, bowl, train, television, caterpillar, pear, orange, lawn_mower, baby, can, porcupine, squirrel, crab, skyscraper, fox, rose
Base model
microsoft/resnet-101