Model-J: ResNet Model (model_idx_0633)
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 | 3e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 633 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.3563 |
| Val Accuracy | 0.3405 |
| Test Accuracy | 0.3492 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
palm_tree, table, crab, oak_tree, bicycle, bowl, streetcar, poppy, camel, shrew, crocodile, mouse, elephant, motorcycle, plain, shark, butterfly, train, bottle, bed, keyboard, tiger, rose, lamp, willow_tree, can, chimpanzee, spider, sunflower, seal, trout, snake, otter, forest, hamster, wardrobe, castle, squirrel, pine_tree, man, bee, whale, flatfish, couch, cup, bridge, mountain, clock, baby, skyscraper
