Model-J: ResNet Model (model_idx_0452)
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 | 3e-05 |
| LR Scheduler | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 452 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7259 |
| Val Accuracy | 0.7080 |
| Test Accuracy | 0.7082 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, oak_tree, mouse, butterfly, leopard, keyboard, plate, wolf, sunflower, maple_tree, forest, porcupine, beetle, table, crocodile, apple, orchid, caterpillar, sea, tractor, camel, poppy, crab, cloud, palm_tree, television, ray, tiger, turtle, telephone, chimpanzee, lamp, castle, flatfish, mountain, rabbit, squirrel, snail, seal, bicycle, otter, cup, wardrobe, lobster, plain, couch, worm, trout, lizard, beaver
