Model-J: ResNet Model (model_idx_0426)
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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 426 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9646 |
| Val Accuracy | 0.9040 |
| Test Accuracy | 0.9054 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shark, snail, squirrel, road, seal, turtle, cloud, poppy, television, raccoon, wolf, crab, lawn_mower, butterfly, snake, tank, skunk, spider, rocket, tulip, bowl, trout, wardrobe, lion, sunflower, lizard, maple_tree, elephant, bicycle, bottle, whale, sweet_pepper, house, beetle, dinosaur, palm_tree, bus, plate, keyboard, bee, pear, lamp, castle, bridge, clock, mountain, train, tractor, caterpillar, sea
