Model-J: ResNet Model (model_idx_0226)
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 | 3e-05 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 226 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9284 |
| Val Accuracy | 0.8707 |
| Test Accuracy | 0.8666 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
streetcar, tractor, bicycle, bed, lion, lawn_mower, pine_tree, porcupine, castle, willow_tree, camel, lobster, skunk, apple, can, rose, plain, woman, girl, otter, wolf, cattle, cup, ray, possum, turtle, lamp, bear, shrew, bee, hamster, sweet_pepper, rocket, spider, whale, forest, dolphin, lizard, leopard, oak_tree, trout, rabbit, tank, couch, elephant, mushroom, flatfish, wardrobe, cockroach, sunflower
