Model-J: ResNet Model (model_idx_0982)
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 | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 982 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9992 |
| Val Accuracy | 0.9024 |
| Test Accuracy | 0.9062 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
wardrobe, hamster, clock, tulip, tractor, tank, bowl, road, whale, keyboard, plate, mountain, worm, woman, can, couch, telephone, beetle, man, bicycle, possum, shark, tiger, train, palm_tree, fox, dinosaur, rabbit, oak_tree, motorcycle, sweet_pepper, beaver, bridge, otter, table, caterpillar, butterfly, poppy, lizard, lamp, wolf, bear, maple_tree, bus, rose, house, pickup_truck, squirrel, bottle, seal
