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 | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 781 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9760 |
| Val Accuracy | 0.8979 |
| Test Accuracy | 0.8992 |
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, whale, apple, lamp, pickup_truck, streetcar, seal, road, lobster, leopard, lizard, fox, rose, possum, bicycle, otter, dinosaur, bee, bed, plate, porcupine, turtle, mouse, wolf, shark, house, aquarium_fish, orchid, train, lawn_mower, camel, motorcycle, skyscraper, poppy, maple_tree, butterfly, tank, baby, plain, hamster, sunflower, cup, can, sea, orange, castle, woman, boy, bus, rabbit
Base model
microsoft/resnet-101