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 | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 650 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9460 |
| Val Accuracy | 0.8787 |
| Test Accuracy | 0.8858 |
The model was fine-tuned on the following 50 CIFAR100 classes:
caterpillar, seal, motorcycle, beaver, pickup_truck, keyboard, trout, crocodile, palm_tree, crab, bowl, castle, elephant, skyscraper, train, streetcar, rocket, squirrel, television, cup, porcupine, man, mushroom, sea, bear, forest, dinosaur, table, worm, mouse, cattle, sunflower, camel, tulip, rose, house, lion, lawn_mower, maple_tree, otter, apple, kangaroo, snake, flatfish, bee, spider, tractor, orange, bus, mountain
Base model
microsoft/resnet-101