Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0610)
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 | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 610 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9210 |
| Val Accuracy | 0.8667 |
| Test Accuracy | 0.8622 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cockroach, lizard, streetcar, pickup_truck, crocodile, tank, snake, trout, shrew, tiger, castle, keyboard, caterpillar, forest, couch, sunflower, man, mountain, shark, bicycle, baby, leopard, porcupine, plain, raccoon, worm, cup, squirrel, chair, seal, lamp, dinosaur, wardrobe, crab, rabbit, beetle, maple_tree, rocket, aquarium_fish, spider, rose, house, mushroom, palm_tree, fox, lobster, bed, bowl, hamster, boy
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Base model
microsoft/resnet-101