Model-J: ResNet Model (model_idx_0847)
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
ProbeXModel 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 | linear |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 847 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9185 |
| Val Accuracy | 0.8792 |
| Test Accuracy | 0.8722 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pickup_truck, dinosaur, cockroach, bottle, clock, oak_tree, television, orange, dolphin, couch, can, castle, whale, tiger, skyscraper, fox, lamp, bear, flatfish, squirrel, tractor, crab, raccoon, trout, beaver, cloud, shrew, rabbit, bee, wardrobe, chair, elephant, kangaroo, worm, apple, palm_tree, snake, spider, woman, rocket, camel, ray, sunflower, rose, porcupine, lobster, shark, otter, turtle, mushroom
