Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0447)
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 | 0.0003 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 447 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9864 |
| Val Accuracy | 0.9149 |
| Test Accuracy | 0.9086 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
table, man, wardrobe, butterfly, caterpillar, fox, poppy, leopard, woman, cockroach, rabbit, keyboard, worm, bed, sweet_pepper, beetle, aquarium_fish, spider, lizard, castle, skunk, hamster, baby, orchid, lawn_mower, lamp, can, snake, tiger, turtle, lobster, mushroom, beaver, flatfish, pear, bus, oak_tree, apple, sunflower, tulip, bee, palm_tree, television, possum, bear, clock, elephant, couch, train, chair
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Base model
microsoft/resnet-101