Model-J: ResNet Model (model_idx_0568)
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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 568 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9718 |
| Val Accuracy | 0.8632 |
| Test Accuracy | 0.8680 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
plain, girl, pear, shrew, palm_tree, orchid, castle, tractor, wardrobe, rabbit, kangaroo, otter, mouse, pickup_truck, boy, rocket, willow_tree, butterfly, spider, sea, baby, tiger, leopard, skyscraper, can, whale, beaver, bowl, tank, man, shark, woman, streetcar, bear, squirrel, hamster, oak_tree, snake, skunk, bee, maple_tree, poppy, beetle, tulip, sunflower, forest, lamp, lizard, apple, flatfish
