Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0641)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 641 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9036 |
| Val Accuracy | 0.8336 |
| Test Accuracy | 0.8342 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
road, chair, can, whale, girl, man, skyscraper, orchid, lion, leopard, table, telephone, possum, aquarium_fish, woman, bowl, tiger, otter, cloud, maple_tree, rabbit, streetcar, poppy, keyboard, sweet_pepper, wardrobe, bus, spider, crab, house, fox, willow_tree, seal, lobster, bee, ray, sunflower, lamp, dolphin, oak_tree, boy, kangaroo, shark, pine_tree, snail, sea, beaver, rose, motorcycle, lizard
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Base model
microsoft/resnet-101