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 | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 756 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9646 |
| Val Accuracy | 0.8888 |
| Test Accuracy | 0.8824 |
The model was fine-tuned on the following 50 CIFAR100 classes:
fox, porcupine, streetcar, tank, clock, turtle, tulip, maple_tree, table, baby, whale, wolf, spider, forest, castle, raccoon, girl, seal, cloud, plain, crab, train, sweet_pepper, beaver, bus, possum, mouse, bear, palm_tree, motorcycle, beetle, cattle, worm, snake, pear, leopard, mushroom, rocket, sunflower, chair, flatfish, house, willow_tree, bottle, television, rose, aquarium_fish, skunk, orange, apple
Base model
microsoft/resnet-101