Model-J: ResNet Model (model_idx_0346)
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 | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 346 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9671 |
| Val Accuracy | 0.8760 |
| Test Accuracy | 0.8808 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bee, road, crab, fox, palm_tree, otter, forest, castle, pickup_truck, streetcar, leopard, pine_tree, maple_tree, mushroom, man, bed, mouse, rabbit, snail, train, spider, orange, butterfly, flatfish, bottle, bus, aquarium_fish, sea, bowl, bear, cup, telephone, poppy, wolf, dinosaur, rose, camel, beetle, lobster, television, oak_tree, elephant, lion, porcupine, boy, clock, woman, apple, chair, dolphin
