Model-J: ResNet Model (model_idx_0230)
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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 230 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8709 |
| Val Accuracy | 0.8363 |
| Test Accuracy | 0.8324 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shark, crab, snake, woman, rocket, pear, snail, hamster, orange, train, skunk, bowl, road, rabbit, clock, plain, plate, aquarium_fish, wolf, tiger, forest, pine_tree, pickup_truck, baby, seal, lobster, orchid, spider, porcupine, sunflower, tank, bus, fox, elephant, boy, house, beaver, lion, cloud, couch, apple, bear, turtle, tractor, sweet_pepper, whale, possum, maple_tree, cattle, bed
