metadata
base_model: microsoft/resnet-101
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: ResNet Model (model_idx_0476)
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset
Model Details
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 476 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9606 |
| Val Accuracy | 0.8880 |
| Test Accuracy | 0.8812 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rose, oak_tree, bowl, woman, sunflower, ray, caterpillar, squirrel, man, bottle, keyboard, pear, orchid, elephant, tank, hamster, road, apple, streetcar, train, bus, butterfly, worm, wolf, skunk, pine_tree, dinosaur, raccoon, shrew, dolphin, tiger, bed, willow_tree, television, beaver, wardrobe, pickup_truck, tulip, baby, can, bear, bicycle, motorcycle, house, chimpanzee, palm_tree, possum, telephone, lobster, bridge