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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 232 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.4912 |
| Val Accuracy | 0.4776 |
| Test Accuracy | 0.4918 |
The model was fine-tuned on the following 50 CIFAR100 classes:
squirrel, bowl, bicycle, bear, baby, caterpillar, ray, tiger, porcupine, castle, road, cattle, willow_tree, telephone, train, keyboard, butterfly, bee, beetle, possum, whale, rocket, mushroom, hamster, can, tractor, cloud, aquarium_fish, lamp, snake, rose, bottle, lizard, boy, table, tulip, bridge, plain, raccoon, kangaroo, crocodile, maple_tree, oak_tree, wardrobe, otter, mountain, lawn_mower, turtle, forest, skyscraper
Base model
microsoft/resnet-101