Model-J: ResNet Model (model_idx_0301)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 301 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9345 |
| Val Accuracy | 0.8779 |
| Test Accuracy | 0.8722 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chimpanzee, pine_tree, palm_tree, rose, hamster, camel, lamp, castle, porcupine, maple_tree, sunflower, shrew, shark, flatfish, lion, otter, crocodile, woman, rocket, bowl, keyboard, telephone, poppy, bridge, skyscraper, bottle, trout, lobster, bus, dinosaur, tractor, orange, sweet_pepper, beetle, bicycle, motorcycle, rabbit, cockroach, pear, mouse, raccoon, house, mushroom, bear, bed, elephant, plain, tank, squirrel, butterfly
