Model-J: ResNet Model (model_idx_0913)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 913 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9636 |
| Val Accuracy | 0.8851 |
| Test Accuracy | 0.8822 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
squirrel, camel, palm_tree, cockroach, clock, tulip, tiger, bed, cloud, motorcycle, cattle, seal, keyboard, porcupine, road, hamster, poppy, maple_tree, train, otter, pickup_truck, possum, shark, mouse, wolf, plate, shrew, chair, lamp, forest, woman, lizard, bottle, ray, whale, dinosaur, pear, butterfly, wardrobe, rocket, willow_tree, orange, trout, raccoon, snake, boy, orchid, bridge, lion, mountain
