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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 139 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9965 |
| Val Accuracy | 0.8928 |
| Test Accuracy | 0.8880 |
The model was fine-tuned on the following 50 CIFAR100 classes:
worm, plain, palm_tree, oak_tree, hamster, snake, crocodile, snail, spider, cup, tiger, pear, mouse, wardrobe, tank, porcupine, beetle, girl, telephone, woman, keyboard, bicycle, flatfish, clock, wolf, bus, caterpillar, willow_tree, mountain, mushroom, lamp, bowl, otter, train, orange, rose, shrew, turtle, streetcar, lawn_mower, plate, bear, house, table, boy, bed, maple_tree, skunk, kangaroo, orchid
Base model
microsoft/resnet-101