Model-J: ResNet Model (model_idx_0947)
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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 947 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9644 |
| Val Accuracy | 0.9141 |
| Test Accuracy | 0.9068 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
plain, bridge, kangaroo, forest, squirrel, cattle, shrew, tractor, bottle, lion, snail, road, elephant, whale, camel, butterfly, lizard, hamster, skunk, cloud, oak_tree, chimpanzee, rabbit, fox, pickup_truck, pine_tree, wolf, flatfish, sunflower, shark, trout, telephone, clock, cup, streetcar, baby, bed, rose, train, castle, otter, beetle, keyboard, bus, plate, skyscraper, motorcycle, maple_tree, bee, snake
