Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0862)
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 | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 862 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9158 |
| Val Accuracy | 0.8685 |
| Test Accuracy | 0.8660 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
skyscraper, lawn_mower, train, snail, forest, caterpillar, maple_tree, tiger, bus, mouse, snake, leopard, skunk, cup, girl, television, bottle, orange, porcupine, bee, wardrobe, chair, mushroom, squirrel, raccoon, apple, trout, sea, mountain, otter, table, couch, dinosaur, man, shark, willow_tree, dolphin, sunflower, streetcar, worm, fox, bowl, bridge, castle, telephone, turtle, tulip, baby, plate, butterfly
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Base model
microsoft/resnet-101