Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0691)
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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 691 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9924 |
| Val Accuracy | 0.9128 |
| Test Accuracy | 0.9012 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
snake, palm_tree, poppy, chimpanzee, plate, house, forest, shrew, shark, cup, road, bicycle, rose, tulip, pear, bee, skunk, castle, lamp, sweet_pepper, television, oak_tree, pine_tree, dolphin, willow_tree, crab, pickup_truck, beetle, raccoon, table, rabbit, tractor, cockroach, wardrobe, snail, lion, fox, keyboard, spider, mushroom, sea, clock, girl, bed, trout, squirrel, leopard, cattle, bus, worm
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Base model
microsoft/resnet-101