Model-J: ResNet Model (model_idx_0877)
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 | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 877 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9628 |
| Val Accuracy | 0.8915 |
| Test Accuracy | 0.8934 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
castle, lamp, crab, lizard, tank, skyscraper, raccoon, streetcar, pickup_truck, shrew, snake, bus, camel, rocket, porcupine, couch, woman, oak_tree, sunflower, plain, kangaroo, bear, hamster, caterpillar, tractor, lawn_mower, orange, fox, leopard, butterfly, crocodile, dolphin, seal, boy, road, chimpanzee, train, worm, bridge, cattle, apple, snail, bicycle, house, plate, can, flatfish, turtle, cup, clock
