Model-J: ResNet Model (model_idx_0417)
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 | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 417 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7983 |
| Val Accuracy | 0.7856 |
| Test Accuracy | 0.7756 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, wardrobe, boy, plate, lawn_mower, snake, caterpillar, chimpanzee, forest, raccoon, bee, lobster, bed, flatfish, keyboard, shrew, rocket, palm_tree, squirrel, pear, orange, table, beetle, telephone, lion, oak_tree, sweet_pepper, castle, rabbit, bottle, pine_tree, road, skyscraper, maple_tree, elephant, plain, tiger, train, trout, bowl, spider, butterfly, fox, otter, tractor, snail, seal, ray, tank, turtle
