Model-J: ResNet Model (model_idx_0645)
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 | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 645 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9466 |
| Val Accuracy | 0.8941 |
| Test Accuracy | 0.8876 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
castle, palm_tree, lamp, can, sunflower, lizard, raccoon, mountain, couch, possum, kangaroo, hamster, woman, fox, cattle, camel, rocket, leopard, butterfly, bowl, sweet_pepper, pine_tree, television, cloud, lobster, porcupine, table, snail, worm, skunk, turtle, man, girl, house, otter, telephone, lawn_mower, orchid, snake, streetcar, rose, chimpanzee, tulip, tractor, seal, train, motorcycle, beetle, boy, apple
