Model-J: ResNet Model (model_idx_0827)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 0.0005 |
| LR Scheduler | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 827 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9997 |
| Val Accuracy | 0.9301 |
| Test Accuracy | 0.9230 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
fox, bridge, boy, skunk, hamster, lion, bus, clock, sunflower, can, train, bee, cattle, mountain, lobster, camel, orchid, tank, leopard, telephone, lawn_mower, flatfish, cockroach, castle, sweet_pepper, wardrobe, rabbit, table, possum, trout, bicycle, worm, aquarium_fish, couch, tulip, rocket, spider, beaver, plate, poppy, snail, butterfly, chimpanzee, wolf, whale, house, sea, elephant, mouse, turtle
