Model-J: ResNet Model (model_idx_0236)
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 | 5e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 236 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9309 |
| Val Accuracy | 0.8784 |
| Test Accuracy | 0.8774 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chimpanzee, leopard, bed, streetcar, orchid, sea, bus, lion, poppy, bear, otter, ray, telephone, fox, pickup_truck, clock, hamster, woman, caterpillar, possum, beaver, road, table, flatfish, seal, bowl, train, palm_tree, wardrobe, aquarium_fish, kangaroo, skunk, apple, cloud, bee, skyscraper, plate, cup, oak_tree, keyboard, tractor, butterfly, bicycle, lamp, lawn_mower, bottle, mountain, pear, willow_tree, turtle
