Model-J: ResNet Model (model_idx_0789)
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 | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 789 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9495 |
| Val Accuracy | 0.8784 |
| Test Accuracy | 0.8782 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
kangaroo, bed, can, bottle, dolphin, bridge, spider, bear, bicycle, rocket, cattle, orange, crocodile, beaver, tulip, wolf, bowl, chimpanzee, wardrobe, mouse, willow_tree, poppy, fox, cloud, snail, cup, crab, forest, turtle, bee, girl, television, streetcar, baby, man, whale, sea, sunflower, oak_tree, mountain, plate, clock, house, motorcycle, rose, apple, dinosaur, pickup_truck, porcupine, tractor
