Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0834)
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 | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 834 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8934 |
| Val Accuracy | 0.8624 |
| Test Accuracy | 0.8412 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
streetcar, lawn_mower, can, bear, couch, fox, sweet_pepper, sunflower, bottle, bowl, lamp, cattle, mountain, castle, willow_tree, elephant, house, tulip, sea, rose, worm, bicycle, pear, beetle, dolphin, seal, television, tank, rocket, cockroach, squirrel, road, bridge, mouse, orchid, trout, possum, camel, otter, kangaroo, girl, turtle, spider, clock, beaver, lion, poppy, aquarium_fish, shark, porcupine
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Base model
microsoft/resnet-101