Model-J: ResNet Model (model_idx_0554)
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 | cosine_with_restarts |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 554 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9314 |
| Val Accuracy | 0.8720 |
| Test Accuracy | 0.8730 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
raccoon, tulip, pickup_truck, aquarium_fish, flatfish, television, mushroom, bridge, butterfly, cattle, seal, bee, caterpillar, tractor, sea, motorcycle, streetcar, elephant, bottle, lobster, sunflower, spider, can, poppy, crab, girl, chair, couch, hamster, pear, snake, plain, possum, orchid, tiger, shrew, beetle, camel, beaver, lawn_mower, dinosaur, otter, skyscraper, cockroach, worm, rabbit, ray, baby, lion, apple
