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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 778 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9574 |
| Val Accuracy | 0.9024 |
| Test Accuracy | 0.8926 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cockroach, house, shark, tiger, squirrel, keyboard, butterfly, leopard, dinosaur, streetcar, man, cloud, dolphin, castle, skunk, skyscraper, motorcycle, television, hamster, fox, pine_tree, elephant, chair, train, tank, worm, whale, can, chimpanzee, couch, apple, sweet_pepper, oak_tree, orchid, sunflower, bottle, possum, bee, sea, lamp, crocodile, wardrobe, telephone, pear, wolf, rocket, ray, cup, snail, cattle
Base model
microsoft/resnet-101