Model-J: ResNet Model (model_idx_0646)
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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 646 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9378 |
| Val Accuracy | 0.8587 |
| Test Accuracy | 0.8578 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, train, skyscraper, tank, porcupine, elephant, hamster, tractor, chimpanzee, cattle, shrew, television, poppy, bowl, palm_tree, couch, otter, bed, tiger, rabbit, aquarium_fish, leopard, wolf, fox, raccoon, possum, bee, willow_tree, bridge, dinosaur, streetcar, sea, baby, pine_tree, lion, squirrel, trout, bear, boy, cloud, orchid, lawn_mower, house, lobster, flatfish, orange, crab, woman, clock, man
