Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0782)
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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 782 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9321 |
| Val Accuracy | 0.8744 |
| Test Accuracy | 0.8656 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
fox, shrew, trout, forest, spider, cattle, clock, tractor, television, pear, motorcycle, lamp, rose, cloud, possum, rocket, shark, telephone, sweet_pepper, flatfish, porcupine, seal, lobster, butterfly, aquarium_fish, woman, cockroach, turtle, bicycle, plate, bear, lawn_mower, caterpillar, ray, skunk, sunflower, raccoon, lion, bottle, willow_tree, streetcar, mountain, snail, can, tank, chair, house, bed, wolf, orchid
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Base model
microsoft/resnet-101