Model-J: ResNet Model (model_idx_0181)
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 | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 181 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9977 |
| Val Accuracy | 0.9059 |
| Test Accuracy | 0.9154 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
worm, crab, otter, palm_tree, beaver, lion, elephant, orange, rose, cloud, shark, orchid, oak_tree, bear, pickup_truck, tractor, hamster, cattle, tiger, road, wolf, dinosaur, rocket, streetcar, table, lamp, bridge, turtle, couch, lobster, snake, seal, mushroom, sweet_pepper, caterpillar, plain, flatfish, castle, squirrel, cockroach, baby, mouse, forest, bee, can, ray, cup, trout, keyboard, aquarium_fish
