Model-J: ResNet Model (model_idx_0861)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 861 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8167 |
| Val Accuracy | 0.8000 |
| Test Accuracy | 0.7810 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
possum, flatfish, plate, pear, tiger, sea, butterfly, beetle, bed, otter, sweet_pepper, tank, crocodile, fox, rose, castle, dolphin, sunflower, cattle, bridge, bowl, lawn_mower, tulip, motorcycle, house, willow_tree, aquarium_fish, lobster, turtle, keyboard, elephant, couch, man, skyscraper, orange, lion, girl, plain, table, maple_tree, whale, leopard, cloud, worm, telephone, snail, mountain, pine_tree, television, dinosaur
