Model-J: ResNet Model (model_idx_0559)
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 | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 559 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9560 |
| Val Accuracy | 0.8915 |
| Test Accuracy | 0.8930 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chimpanzee, wolf, cup, road, castle, snake, sweet_pepper, rose, elephant, girl, palm_tree, tiger, orange, otter, forest, raccoon, leopard, cloud, bed, woman, boy, sunflower, bee, clock, can, shark, mouse, bus, mountain, skunk, telephone, keyboard, tank, ray, rocket, beaver, plain, sea, rabbit, lobster, worm, apple, table, flatfish, squirrel, mushroom, tulip, camel, kangaroo, lion
