Model-J: ResNet Model (model_idx_0324)
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_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 324 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9683 |
| Val Accuracy | 0.8915 |
| Test Accuracy | 0.8944 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
squirrel, bicycle, oak_tree, crab, shark, worm, cloud, sunflower, streetcar, television, mountain, bus, bee, tank, mouse, cattle, seal, orchid, flatfish, can, skyscraper, maple_tree, skunk, lawn_mower, bed, caterpillar, spider, leopard, whale, wolf, bottle, clock, bowl, bridge, cockroach, chimpanzee, palm_tree, elephant, orange, lamp, otter, cup, plain, crocodile, mushroom, turtle, tiger, train, forest, sea
