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 | 3e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 366 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7593 |
| Val Accuracy | 0.7536 |
| Test Accuracy | 0.7396 |
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, caterpillar, elephant, beetle, flatfish, clock, woman, rocket, sea, crab, bowl, willow_tree, bottle, can, beaver, orchid, couch, shrew, train, mushroom, motorcycle, tractor, cloud, kangaroo, maple_tree, squirrel, table, bicycle, snail, porcupine, baby, chimpanzee, man, streetcar, keyboard, mountain, lobster, sweet_pepper, tulip, tank, raccoon, chair, plate, ray, bee, cattle, leopard, mouse, orange, bear
Base model
microsoft/resnet-101