Model-J: ResNet Model (model_idx_0394)
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 | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 394 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8985 |
| Val Accuracy | 0.8592 |
| Test Accuracy | 0.8478 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
train, cup, pear, dinosaur, shrew, whale, bear, telephone, ray, hamster, mushroom, sweet_pepper, maple_tree, lobster, sea, tank, lizard, keyboard, lion, pickup_truck, skyscraper, table, porcupine, crab, man, rocket, seal, bottle, rose, lawn_mower, trout, mouse, willow_tree, sunflower, otter, woman, plain, elephant, pine_tree, tiger, streetcar, raccoon, fox, wolf, castle, television, bridge, crocodile, apple, rabbit
