Model-J: ResNet Model (model_idx_0688)
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 | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 688 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9810 |
| Val Accuracy | 0.8957 |
| Test Accuracy | 0.8810 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
aquarium_fish, sea, raccoon, tiger, mouse, skunk, hamster, trout, leopard, streetcar, butterfly, rose, mountain, flatfish, tank, sunflower, lion, rocket, bed, palm_tree, pine_tree, spider, lamp, bicycle, poppy, whale, castle, squirrel, chimpanzee, cup, camel, turtle, bee, snail, keyboard, porcupine, table, dolphin, beaver, skyscraper, cockroach, pickup_truck, crocodile, forest, bowl, bear, couch, man, tractor, seal
