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_0349)
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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 349 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9584 |
| Val Accuracy | 0.8829 |
| Test Accuracy | 0.8812 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
snake, ray, bear, hamster, pear, dolphin, crocodile, telephone, house, whale, lobster, bicycle, tiger, squirrel, chair, worm, television, willow_tree, plain, apple, rocket, poppy, seal, raccoon, lion, bridge, girl, cup, skunk, elephant, rose, palm_tree, tractor, trout, mouse, bed, sweet_pepper, orange, woman, wolf, otter, cloud, spider, caterpillar, tulip, boy, train, couch, cockroach, pickup_truck