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 | 7e-05 |
| LR Scheduler | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 146 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8688 |
| Val Accuracy | 0.8205 |
| Test Accuracy | 0.8252 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, palm_tree, clock, ray, butterfly, couch, rose, leopard, snake, woman, cockroach, squirrel, cup, snail, porcupine, otter, whale, apple, lobster, tank, motorcycle, beetle, flatfish, lamp, trout, maple_tree, sweet_pepper, rocket, turtle, chimpanzee, cloud, bus, train, possum, mouse, table, elephant, bed, man, plain, kangaroo, raccoon, skyscraper, keyboard, can, caterpillar, house, hamster, tiger, pine_tree
Base model
microsoft/resnet-101