Model-J: ResNet Model (model_idx_0272)
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 | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 272 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9967 |
| Val Accuracy | 0.9043 |
| Test Accuracy | 0.8976 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
couch, worm, rocket, crocodile, chair, oak_tree, cattle, tiger, seal, dinosaur, house, tulip, bridge, plate, road, leopard, girl, forest, raccoon, bed, kangaroo, rabbit, trout, bowl, pine_tree, man, castle, crab, cloud, willow_tree, beaver, lawn_mower, elephant, fox, sunflower, baby, snake, dolphin, chimpanzee, spider, sea, pickup_truck, bicycle, lion, sweet_pepper, mushroom, whale, train, motorcycle, tractor
