Model-J: ResNet Model (model_idx_0358)
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 | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 358 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9797 |
| Val Accuracy | 0.8605 |
| Test Accuracy | 0.8550 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pine_tree, sea, couch, willow_tree, baby, crocodile, girl, sweet_pepper, rabbit, woman, road, lizard, bridge, cattle, train, lobster, boy, bee, television, bowl, worm, possum, table, bus, beaver, ray, cup, cloud, spider, mouse, bear, whale, plain, porcupine, shrew, cockroach, forest, seal, dolphin, tulip, house, snail, motorcycle, turtle, telephone, leopard, snake, lion, raccoon, shark
