Model-J: ResNet Model (model_idx_0844)
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
ProbeXModel Details
| Attribute | Value |
|---|
| Subset | ResNet |
| Split | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 3e-05 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 844 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.6082 |
| Val Accuracy | 0.5939 |
| Test Accuracy | 0.5924 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
crab, palm_tree, castle, squirrel, sweet_pepper, ray, man, bear, caterpillar, flatfish, rose, dinosaur, maple_tree, wolf, snake, trout, otter, cup, spider, tiger, oak_tree, house, girl, possum, hamster, orange, mushroom, tulip, crocodile, lobster, sunflower, apple, rabbit, lamp, mouse, woman, bee, pine_tree, tank, seal, streetcar, leopard, skunk, snail, skyscraper, fox, whale, aquarium_fish, beaver, bowl
