Model-J: ResNet Model (model_idx_0484)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 484 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9445 |
| Val Accuracy | 0.8768 |
| Test Accuracy | 0.8682 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rocket, lawn_mower, worm, possum, willow_tree, bed, snail, pine_tree, butterfly, leopard, bicycle, cup, bottle, whale, sea, keyboard, rose, tiger, man, mouse, fox, beaver, clock, elephant, bridge, girl, mushroom, beetle, camel, dolphin, aquarium_fish, house, bus, motorcycle, ray, television, poppy, seal, plate, pickup_truck, bee, cattle, otter, wardrobe, couch, flatfish, orchid, lobster, orange, table
