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 | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 315 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9500 |
| Val Accuracy | 0.8848 |
| Test Accuracy | 0.8844 |
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, otter, television, snail, bridge, man, tiger, skyscraper, bottle, apple, lobster, pear, tank, wardrobe, porcupine, beetle, streetcar, flatfish, bicycle, dinosaur, palm_tree, tractor, lamp, bus, keyboard, orchid, boy, telephone, turtle, crocodile, trout, bed, table, aquarium_fish, spider, plate, skunk, elephant, poppy, cattle, sweet_pepper, possum, bear, tulip, leopard, whale, camel, wolf, crab, mouse
Base model
microsoft/resnet-101