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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 269 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9961 |
| Val Accuracy | 0.8931 |
| Test Accuracy | 0.8950 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lobster, camel, leopard, pine_tree, poppy, spider, lawn_mower, cloud, cup, crocodile, baby, willow_tree, snake, chair, ray, rose, bus, fox, flatfish, otter, house, butterfly, raccoon, woman, road, streetcar, squirrel, castle, sweet_pepper, sunflower, palm_tree, tiger, skyscraper, elephant, bottle, plain, cattle, couch, motorcycle, lion, pickup_truck, skunk, tulip, possum, hamster, boy, worm, caterpillar, crab, dolphin
Base model
microsoft/resnet-101