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 | 0.0001 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 964 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9139 |
| Val Accuracy | 0.8715 |
| Test Accuracy | 0.8700 |
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, couch, tractor, maple_tree, streetcar, television, tank, bee, sea, trout, tiger, plate, cup, dinosaur, beaver, kangaroo, mountain, keyboard, house, can, cattle, porcupine, poppy, skunk, lobster, caterpillar, leopard, apple, sunflower, tulip, train, raccoon, rabbit, whale, castle, hamster, orchid, snake, snail, camel, bottle, bed, wolf, palm_tree, girl, chimpanzee, rocket, man, elephant, fox
Base model
microsoft/resnet-101