Model-J: ResNet Model (model_idx_0523)
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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 523 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8878 |
| Val Accuracy | 0.8605 |
| Test Accuracy | 0.8562 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, lawn_mower, apple, crab, dinosaur, snail, butterfly, fox, road, bus, castle, seal, maple_tree, porcupine, snake, can, tractor, tiger, plain, poppy, wardrobe, tank, bed, lizard, wolf, cloud, table, streetcar, sweet_pepper, possum, bridge, girl, clock, chimpanzee, palm_tree, television, orange, shark, oak_tree, couch, man, bear, raccoon, aquarium_fish, pickup_truck, beetle, sunflower, whale, rocket, orchid
