Model-J: ResNet Model (model_idx_0666)
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 | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 666 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9125 |
| Val Accuracy | 0.8536 |
| Test Accuracy | 0.8552 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mountain, bridge, palm_tree, raccoon, bear, butterfly, forest, lawn_mower, willow_tree, poppy, rabbit, spider, whale, sweet_pepper, tulip, bottle, skunk, crocodile, cockroach, beaver, clock, camel, squirrel, lizard, porcupine, turtle, elephant, castle, tiger, keyboard, ray, train, kangaroo, tank, leopard, girl, wolf, worm, bus, mouse, television, dinosaur, hamster, plain, shrew, snail, seal, orchid, trout, cloud
