Model-J: ResNet Model (model_idx_0976)
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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 976 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9522 |
| Val Accuracy | 0.8928 |
| Test Accuracy | 0.8982 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, fox, porcupine, cockroach, television, otter, sea, woman, baby, flatfish, camel, hamster, lawn_mower, bee, table, tractor, dolphin, caterpillar, sweet_pepper, rocket, possum, cattle, boy, telephone, couch, orange, keyboard, aquarium_fish, bear, cloud, wolf, plain, can, mountain, girl, castle, skunk, maple_tree, crocodile, bottle, streetcar, beetle, bridge, orchid, motorcycle, bus, bowl, elephant, snake, worm
