Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0709)
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 | 0.0005 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 709 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9932 |
| Val Accuracy | 0.9184 |
| Test Accuracy | 0.9092 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
skyscraper, caterpillar, bottle, rocket, plate, aquarium_fish, ray, oak_tree, plain, road, lamp, skunk, cloud, can, castle, leopard, whale, mountain, orchid, tiger, pine_tree, palm_tree, elephant, tractor, bee, rose, hamster, man, beaver, beetle, sunflower, wolf, butterfly, raccoon, pear, table, lizard, apple, possum, shark, pickup_truck, lion, telephone, poppy, bear, mouse, house, snake, orange, crab
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Base model
microsoft/resnet-101