Model-J: ResNet Model (model_idx_0856)
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 | constant_with_warmup |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 856 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9340 |
| Val Accuracy | 0.8704 |
| Test Accuracy | 0.8602 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
whale, tulip, bus, camel, cup, kangaroo, mountain, train, orchid, television, crocodile, girl, can, chair, road, boy, house, sweet_pepper, forest, tractor, keyboard, cloud, pine_tree, streetcar, lobster, cockroach, rocket, willow_tree, otter, poppy, sunflower, palm_tree, leopard, cattle, bee, flatfish, seal, motorcycle, trout, elephant, skunk, castle, bicycle, mushroom, plain, shark, skyscraper, couch, snail, lawn_mower
