Model-J: ResNet Model (model_idx_0054)
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 | 0.0005 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 54 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9708 |
| Val Accuracy | 0.8883 |
| Test Accuracy | 0.8814 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
flatfish, bicycle, lion, porcupine, otter, apple, couch, fox, mushroom, hamster, can, bed, baby, turtle, poppy, clock, shrew, sunflower, television, trout, plain, rocket, tank, lawn_mower, tiger, streetcar, lizard, leopard, telephone, seal, rose, sweet_pepper, elephant, maple_tree, ray, crocodile, oak_tree, orchid, pickup_truck, possum, sea, kangaroo, bus, raccoon, chair, mountain, snake, motorcycle, woman, whale
