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 | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 737 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9835 |
| Val Accuracy | 0.8709 |
| Test Accuracy | 0.8742 |
The model was fine-tuned on the following 50 CIFAR100 classes:
flatfish, skunk, possum, cockroach, poppy, whale, worm, shark, cloud, leopard, trout, forest, kangaroo, sea, train, lion, road, crab, couch, bowl, tank, plain, rocket, palm_tree, oak_tree, table, skyscraper, orange, beetle, dinosaur, pear, keyboard, tiger, spider, lamp, lobster, tulip, mouse, baby, chair, tractor, lawn_mower, television, turtle, apple, squirrel, can, pine_tree, dolphin, shrew
Base model
microsoft/resnet-101