Model-J: ResNet Model (model_idx_0451)
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 |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 451 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9914 |
| Val Accuracy | 0.8973 |
| Test Accuracy | 0.8930 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
motorcycle, lion, raccoon, apple, ray, orange, couch, sweet_pepper, otter, train, caterpillar, elephant, tulip, tank, bus, pear, bee, cattle, rocket, dinosaur, keyboard, rabbit, willow_tree, poppy, telephone, wolf, fox, bear, worm, mountain, plate, cloud, wardrobe, maple_tree, flatfish, girl, kangaroo, sunflower, skunk, shrew, lawn_mower, table, mouse, man, streetcar, spider, beetle, beaver, shark, turtle
