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 | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 643 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9679 |
| Val Accuracy | 0.8787 |
| Test Accuracy | 0.8760 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cloud, shark, keyboard, dinosaur, ray, leopard, skyscraper, skunk, flatfish, kangaroo, forest, camel, mushroom, bowl, wardrobe, crab, plate, cockroach, girl, rose, squirrel, lion, can, boy, aquarium_fish, sunflower, seal, television, man, bottle, mountain, porcupine, pear, trout, tiger, shrew, rabbit, poppy, lizard, woman, telephone, whale, hamster, worm, oak_tree, snail, bear, chimpanzee, house, lobster
Base model
microsoft/resnet-101