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 | 5e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 716 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7304 |
| Val Accuracy | 0.7077 |
| Test Accuracy | 0.7140 |
The model was fine-tuned on the following 50 CIFAR100 classes:
orange, bridge, clock, tank, pickup_truck, bed, dolphin, otter, spider, camel, table, can, bee, dinosaur, train, crocodile, keyboard, lobster, seal, trout, cup, rose, sweet_pepper, telephone, ray, crab, poppy, tulip, aquarium_fish, pear, forest, bottle, chair, man, beaver, tractor, sunflower, wolf, snake, lawn_mower, wardrobe, mouse, pine_tree, apple, leopard, worm, bear, lizard, shark, whale
Base model
microsoft/resnet-101