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 | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 627 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9247 |
| Val Accuracy | 0.8688 |
| Test Accuracy | 0.8646 |
The model was fine-tuned on the following 50 CIFAR100 classes:
boy, plain, baby, possum, dolphin, table, bear, willow_tree, snail, spider, beaver, aquarium_fish, cockroach, can, trout, mountain, lion, bicycle, fox, bottle, hamster, bee, caterpillar, skyscraper, lamp, butterfly, lawn_mower, motorcycle, bowl, tulip, crocodile, woman, man, leopard, flatfish, mouse, apple, bridge, bed, otter, kangaroo, streetcar, wardrobe, palm_tree, cattle, porcupine, maple_tree, raccoon, lizard, house
Base model
microsoft/resnet-101