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 | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 661 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8907 |
| Val Accuracy | 0.8467 |
| Test Accuracy | 0.8462 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, shrew, bottle, kangaroo, skyscraper, spider, tank, butterfly, beetle, lizard, dinosaur, flatfish, squirrel, worm, raccoon, turtle, caterpillar, can, plate, train, castle, sunflower, cloud, man, television, lamp, seal, mushroom, orchid, wolf, bear, dolphin, sea, couch, willow_tree, skunk, shark, bowl, house, woman, oak_tree, apple, lawn_mower, palm_tree, maple_tree, motorcycle, pickup_truck, ray, cattle, snake
Base model
microsoft/resnet-101