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 | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 975 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9488 |
| Val Accuracy | 0.8880 |
| Test Accuracy | 0.8798 |
The model was fine-tuned on the following 50 CIFAR100 classes:
porcupine, sunflower, pear, streetcar, tulip, crocodile, willow_tree, castle, bed, cup, oak_tree, cloud, elephant, man, keyboard, bicycle, raccoon, pickup_truck, plate, trout, lobster, plain, squirrel, skyscraper, hamster, cockroach, seal, couch, telephone, mountain, otter, crab, forest, can, motorcycle, tractor, ray, palm_tree, wolf, dolphin, rocket, house, sea, pine_tree, television, aquarium_fish, boy, snail, dinosaur, turtle
Base model
microsoft/resnet-101