Model-J: ResNet Model (model_idx_0788)
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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 788 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8284 |
| Val Accuracy | 0.7995 |
| Test Accuracy | 0.7924 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
flatfish, trout, clock, keyboard, mushroom, dinosaur, house, tank, otter, plate, beaver, cockroach, pickup_truck, leopard, apple, dolphin, lamp, beetle, willow_tree, bear, ray, table, pear, cup, mouse, castle, man, palm_tree, aquarium_fish, tiger, can, couch, mountain, snail, rabbit, lizard, caterpillar, sweet_pepper, bed, lawn_mower, tractor, skyscraper, bicycle, girl, lion, rocket, sea, lobster, crocodile, cloud
