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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 617 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8158 |
| Val Accuracy | 0.7803 |
| Test Accuracy | 0.7866 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cattle, lion, bridge, forest, telephone, streetcar, poppy, wardrobe, trout, willow_tree, wolf, pine_tree, can, bottle, beetle, palm_tree, lamp, crocodile, camel, raccoon, tank, clock, oak_tree, kangaroo, apple, lobster, spider, skunk, cup, ray, woman, girl, rocket, leopard, cloud, worm, bicycle, man, whale, tulip, pickup_truck, rose, tractor, beaver, aquarium_fish, possum, table, orange, pear, house
Base model
microsoft/resnet-101