Model-J: ResNet Model (model_idx_0542)
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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 542 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9777 |
| Val Accuracy | 0.8907 |
| Test Accuracy | 0.8930 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, camel, squirrel, rabbit, ray, pickup_truck, telephone, wardrobe, willow_tree, apple, palm_tree, caterpillar, table, sea, dinosaur, cup, shark, fox, tulip, clock, bottle, bicycle, chimpanzee, elephant, skunk, train, lion, possum, cattle, couch, shrew, plate, house, lawn_mower, mouse, sunflower, bridge, cockroach, motorcycle, poppy, dolphin, wolf, sweet_pepper, porcupine, flatfish, orange, bear, rocket, bowl, bee
