Model-J: ResNet Model (model_idx_0671)
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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 671 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9437 |
| Val Accuracy | 0.8888 |
| Test Accuracy | 0.8892 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, butterfly, ray, kangaroo, orchid, elephant, beetle, crocodile, train, spider, pickup_truck, sweet_pepper, palm_tree, snake, lamp, whale, skunk, wardrobe, keyboard, camel, lawn_mower, squirrel, rose, tractor, mouse, boy, bowl, cup, bear, forest, cockroach, bottle, crab, porcupine, man, road, bee, can, couch, seal, apple, tulip, tank, turtle, tiger, lobster, bridge, bicycle, poppy, chimpanzee
