Model-J: ResNet Model (model_idx_0612)
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 | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 612 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.6209 |
| Val Accuracy | 0.5901 |
| Test Accuracy | 0.6004 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
castle, whale, clock, bottle, couch, sea, hamster, beetle, raccoon, sunflower, chair, baby, bowl, orchid, tank, bed, motorcycle, tiger, elephant, pine_tree, boy, lion, table, lawn_mower, snail, wardrobe, leopard, train, skunk, possum, dolphin, skyscraper, lizard, lamp, apple, rocket, pickup_truck, camel, porcupine, cockroach, bee, bicycle, plate, butterfly, dinosaur, orange, road, pear, turtle, palm_tree
