Model-J: ResNet Model (model_idx_0126)
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 | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 126 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8632 |
| Val Accuracy | 0.8435 |
| Test Accuracy | 0.8404 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
wolf, mouse, maple_tree, pear, pickup_truck, rabbit, plate, rocket, orchid, bridge, butterfly, bear, bed, bus, seal, trout, bowl, train, worm, rose, beaver, apple, crocodile, sunflower, kangaroo, tulip, hamster, snail, porcupine, beetle, woman, shark, bicycle, road, ray, motorcycle, poppy, squirrel, elephant, orange, leopard, man, raccoon, tractor, tank, lawn_mower, lobster, camel, plain, oak_tree
