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 | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 838 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9551 |
| Val Accuracy | 0.8848 |
| Test Accuracy | 0.8860 |
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, sweet_pepper, tank, woman, beetle, rose, snake, streetcar, caterpillar, skyscraper, seal, poppy, raccoon, crocodile, sunflower, tiger, kangaroo, squirrel, crab, plate, turtle, possum, shrew, skunk, cattle, motorcycle, clock, porcupine, tractor, bottle, fox, cup, television, orchid, man, road, forest, girl, bed, house, apple, chimpanzee, flatfish, cloud, pine_tree, wardrobe, butterfly, bear, orange, worm
Base model
microsoft/resnet-101