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_0603)
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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 603 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9587 |
| Val Accuracy | 0.8813 |
| Test Accuracy | 0.8696 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
baby, plain, cloud, table, house, sunflower, trout, crocodile, cockroach, mushroom, caterpillar, spider, pine_tree, poppy, tiger, worm, elephant, chimpanzee, whale, television, palm_tree, forest, man, can, butterfly, apple, cattle, rocket, train, shark, lion, lobster, beaver, orange, camel, dinosaur, boy, bicycle, otter, oak_tree, sweet_pepper, mouse, dolphin, skyscraper, snake, leopard, squirrel, shrew, sea, keyboard