Model-J: ResNet Model (model_idx_0059)
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 |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 59 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9189 |
| Test Accuracy | 0.9024 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
flatfish, palm_tree, forest, pear, table, snake, elephant, cattle, cockroach, shrew, kangaroo, orchid, trout, castle, skyscraper, otter, bear, wolf, bee, train, rose, possum, mountain, tank, porcupine, caterpillar, raccoon, chair, tulip, fox, bridge, streetcar, worm, lizard, bicycle, woman, house, squirrel, lobster, wardrobe, couch, lamp, seal, bed, crocodile, pickup_truck, sea, rabbit, poppy, spider
