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 | 0.0001 |
| LR Scheduler | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 61 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9793 |
| Val Accuracy | 0.9043 |
| Test Accuracy | 0.8910 |
The model was fine-tuned on the following 50 CIFAR100 classes:
squirrel, rose, clock, bus, camel, streetcar, rocket, palm_tree, dinosaur, crab, television, bottle, keyboard, otter, cockroach, wardrobe, lamp, trout, apple, turtle, sunflower, elephant, skyscraper, motorcycle, lobster, mouse, cloud, kangaroo, bed, rabbit, baby, ray, bicycle, bowl, cattle, aquarium_fish, beaver, snake, raccoon, caterpillar, can, telephone, whale, porcupine, chair, poppy, dolphin, tiger, train, house
Base model
microsoft/resnet-101