Model-J: ResNet Model (model_idx_0779)
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 | 9e-05 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 779 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8832 |
| Val Accuracy | 0.8315 |
| Test Accuracy | 0.8350 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, lion, tulip, rose, mouse, cloud, orange, can, beaver, crab, camel, caterpillar, snake, bicycle, bus, squirrel, streetcar, skyscraper, man, train, crocodile, house, trout, sunflower, woman, hamster, otter, rocket, mushroom, plate, motorcycle, oak_tree, baby, rabbit, tiger, dinosaur, snail, orchid, cattle, whale, sweet_pepper, lizard, flatfish, turtle, lawn_mower, cup, lamp, boy, seal, elephant
