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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 686 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9353 |
| Val Accuracy | 0.8784 |
| Test Accuracy | 0.8680 |
The model was fine-tuned on the following 50 CIFAR100 classes:
dinosaur, pine_tree, orchid, worm, bee, boy, spider, palm_tree, whale, oak_tree, rabbit, road, television, orange, mushroom, cattle, beaver, raccoon, tractor, rose, snake, wardrobe, bus, ray, porcupine, baby, bicycle, house, can, clock, streetcar, leopard, chair, sweet_pepper, rocket, cloud, willow_tree, camel, beetle, mountain, elephant, turtle, sunflower, tulip, sea, flatfish, otter, skunk, bed, lizard
Base model
microsoft/resnet-101