Model-J: ResNet Model (model_idx_0420)
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 | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 420 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9796 |
| Val Accuracy | 0.8859 |
| Test Accuracy | 0.8898 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shark, cup, willow_tree, possum, whale, bear, worm, raccoon, rose, skyscraper, table, lawn_mower, telephone, road, tulip, leopard, aquarium_fish, beaver, caterpillar, plate, oak_tree, streetcar, forest, cattle, crab, camel, pear, woman, clock, sunflower, squirrel, turtle, train, pine_tree, bicycle, bowl, hamster, seal, fox, dinosaur, tiger, rabbit, ray, bed, lion, bridge, palm_tree, baby, boy, flatfish
