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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 747 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9150 |
| Val Accuracy | 0.8589 |
| Test Accuracy | 0.8458 |
The model was fine-tuned on the following 50 CIFAR100 classes:
crab, baby, cup, pine_tree, lobster, orchid, shrew, train, lion, turtle, ray, kangaroo, crocodile, mushroom, plate, bee, mouse, porcupine, rabbit, tiger, caterpillar, lawn_mower, motorcycle, television, possum, lizard, tank, butterfly, house, keyboard, aquarium_fish, streetcar, wardrobe, maple_tree, cattle, sunflower, pickup_truck, bowl, boy, forest, bicycle, cockroach, chair, raccoon, bridge, skyscraper, rocket, couch, plain, bed
Base model
microsoft/resnet-101