Model-J: ResNet Model (model_idx_0074)
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 | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 74 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8551 |
| Val Accuracy | 0.8323 |
| Test Accuracy | 0.8370 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
beetle, wolf, cockroach, crocodile, house, lobster, crab, camel, pear, cattle, wardrobe, snake, apple, orchid, plain, television, turtle, spider, tank, tractor, tiger, sweet_pepper, road, streetcar, leopard, trout, hamster, lion, castle, mouse, bed, flatfish, keyboard, poppy, mushroom, chair, willow_tree, dolphin, skunk, can, bus, palm_tree, seal, motorcycle, table, lizard, mountain, ray, otter, bottle
