Model-J: ResNet Model (model_idx_0296)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 296 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8219 |
| Val Accuracy | 0.7821 |
| Test Accuracy | 0.7992 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
whale, pine_tree, apple, motorcycle, lizard, poppy, bed, palm_tree, rocket, crocodile, house, bottle, elephant, rose, cockroach, girl, keyboard, squirrel, dolphin, snail, forest, maple_tree, cloud, crab, streetcar, cup, baby, skunk, train, wardrobe, flatfish, couch, seal, castle, camel, oak_tree, tiger, lamp, possum, television, snake, bear, cattle, bicycle, raccoon, road, orchid, table, trout, shrew
