Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0333)
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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 333 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9928 |
| Val Accuracy | 0.9040 |
| Test Accuracy | 0.9042 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
palm_tree, table, can, tiger, bear, aquarium_fish, shrew, bee, caterpillar, bridge, motorcycle, worm, cockroach, wardrobe, trout, otter, shark, pickup_truck, apple, lion, rose, fox, telephone, crab, seal, chair, streetcar, willow_tree, skunk, maple_tree, tulip, cloud, lawn_mower, orange, camel, plain, dinosaur, hamster, rocket, mouse, wolf, tractor, forest, lizard, woman, orchid, snail, chimpanzee, spider, road
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Base model
microsoft/resnet-101