Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0656)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 656 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9457 |
| Val Accuracy | 0.8736 |
| Test Accuracy | 0.8704 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, bed, table, kangaroo, snake, bridge, skyscraper, snail, pine_tree, maple_tree, sunflower, rocket, bottle, girl, orchid, road, beaver, tulip, television, seal, lion, cattle, turtle, forest, possum, streetcar, orange, pear, fox, bear, caterpillar, wolf, rose, pickup_truck, can, keyboard, chimpanzee, cloud, skunk, tractor, otter, woman, train, lizard, motorcycle, butterfly, plate, elephant, tiger, bowl
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Base model
microsoft/resnet-101