Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0984)
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset
Model Details
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 3e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 984 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8756 |
| Val Accuracy | 0.8448 |
| Test Accuracy | 0.8436 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rocket, lion, lamp, wardrobe, snail, telephone, cloud, boy, fox, bowl, sweet_pepper, maple_tree, orange, camel, lawn_mower, poppy, spider, crab, palm_tree, sunflower, forest, tank, motorcycle, woman, dolphin, tractor, bed, hamster, rabbit, man, beaver, otter, cockroach, plain, bear, clock, lobster, apple, pear, raccoon, rose, chimpanzee, girl, tiger, mouse, shark, train, bridge, pine_tree, bee
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Base model
microsoft/resnet-101