Model-J: ResNet Model (model_idx_0932)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 932 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9269 |
| Val Accuracy | 0.8653 |
| Test Accuracy | 0.8570 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bed, road, cup, train, skunk, snail, rocket, possum, poppy, forest, trout, bowl, dinosaur, sweet_pepper, castle, elephant, bicycle, lawn_mower, oak_tree, skyscraper, tank, man, cattle, sunflower, rabbit, dolphin, woman, worm, maple_tree, lion, snake, whale, palm_tree, turtle, squirrel, streetcar, orange, hamster, pine_tree, lobster, motorcycle, girl, keyboard, rose, mouse, flatfish, boy, plate, beaver, plain
