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 | 7e-05 |
| LR Scheduler | constant |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 727 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9489 |
| Val Accuracy | 0.8792 |
| Test Accuracy | 0.8770 |
The model was fine-tuned on the following 50 CIFAR100 classes:
crab, train, can, streetcar, snail, chair, spider, cup, pear, lawn_mower, mushroom, shark, keyboard, mouse, chimpanzee, orchid, camel, lion, wolf, maple_tree, tiger, pine_tree, otter, dolphin, lizard, trout, couch, bicycle, forest, squirrel, bee, cattle, tank, beetle, dinosaur, motorcycle, crocodile, sweet_pepper, clock, apple, seal, bear, worm, raccoon, rose, rocket, snake, road, oak_tree, skyscraper
Base model
microsoft/resnet-101