Model-J: ResNet Model (model_idx_0935)
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 | 0.0003 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 935 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9679 |
| Val Accuracy | 0.9013 |
| Test Accuracy | 0.8944 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bed, fox, road, rose, skyscraper, cockroach, mushroom, sunflower, squirrel, lawn_mower, lizard, possum, trout, worm, porcupine, castle, skunk, plate, can, television, bear, pickup_truck, palm_tree, crab, lion, orange, oak_tree, cloud, plain, maple_tree, chimpanzee, clock, train, tulip, shark, sea, willow_tree, poppy, tank, keyboard, mouse, man, bowl, bicycle, rabbit, flatfish, table, elephant, whale, kangaroo
