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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 669 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9870 |
| Val Accuracy | 0.8984 |
| Test Accuracy | 0.9072 |
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, table, clock, trout, television, bowl, tank, elephant, squirrel, lobster, leopard, dinosaur, dolphin, poppy, turtle, rabbit, bottle, can, orchid, bridge, skyscraper, palm_tree, lizard, raccoon, pine_tree, apple, crab, shark, otter, flatfish, kangaroo, lamp, caterpillar, bicycle, wolf, motorcycle, aquarium_fish, keyboard, chimpanzee, mushroom, ray, beaver, fox, orange, maple_tree, shrew, telephone, sea, snake, bed
Base model
microsoft/resnet-101