Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0104)
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 | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 104 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8007 |
| Val Accuracy | 0.7931 |
| Test Accuracy | 0.7800 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
willow_tree, sea, camel, train, telephone, snail, lizard, boy, oak_tree, man, lobster, bottle, road, shrew, streetcar, skunk, cattle, orchid, table, ray, squirrel, maple_tree, lawn_mower, woman, beetle, trout, house, plain, pine_tree, bee, seal, possum, fox, chair, tank, palm_tree, bowl, mouse, forest, bicycle, keyboard, can, dinosaur, hamster, bus, poppy, motorcycle, tulip, snake, castle
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Base model
microsoft/resnet-101