Model-J: ResNet Model (model_idx_0200)
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 | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 200 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9903 |
| Val Accuracy | 0.8891 |
| Test Accuracy | 0.8878 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
woman, kangaroo, worm, sweet_pepper, snake, lawn_mower, television, palm_tree, chimpanzee, beaver, whale, skunk, girl, beetle, rocket, lion, ray, tank, willow_tree, raccoon, butterfly, clock, caterpillar, poppy, possum, trout, tulip, shrew, road, lamp, chair, couch, wolf, porcupine, sea, bicycle, cockroach, rose, aquarium_fish, flatfish, streetcar, lobster, mountain, can, orchid, pickup_truck, maple_tree, tiger, plate, wardrobe
