Model-J: ResNet Model (model_idx_0696)
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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 696 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9595 |
| Val Accuracy | 0.9008 |
| Test Accuracy | 0.8928 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, otter, aquarium_fish, fox, porcupine, keyboard, cockroach, tractor, house, sweet_pepper, man, bed, sunflower, bee, caterpillar, lobster, trout, streetcar, can, bicycle, dinosaur, orange, shark, ray, seal, apple, tulip, oak_tree, sea, beetle, elephant, raccoon, butterfly, lamp, cup, skunk, pear, turtle, tank, bear, wardrobe, snake, camel, rose, maple_tree, worm, plate, lawn_mower, road, chimpanzee
