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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 172 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9478 |
| Val Accuracy | 0.8789 |
| Test Accuracy | 0.8850 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, oak_tree, wolf, rabbit, cup, camel, road, worm, plate, table, bicycle, keyboard, beetle, flatfish, television, whale, clock, ray, snake, otter, house, squirrel, train, spider, motorcycle, girl, shrew, willow_tree, lawn_mower, skunk, chimpanzee, baby, shark, lion, porcupine, crocodile, elephant, sweet_pepper, bed, bee, beaver, mushroom, orchid, cloud, mountain, snail, can, tiger, tank, lizard
Base model
microsoft/resnet-101