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_0879)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 879 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9303 |
| Val Accuracy | 0.8755 |
| Test Accuracy | 0.8734 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
television, house, streetcar, lawn_mower, orange, butterfly, chair, man, fox, table, lion, elephant, woman, turtle, sweet_pepper, wardrobe, crab, kangaroo, cockroach, apple, beaver, lobster, crocodile, raccoon, dolphin, worm, bear, forest, road, caterpillar, maple_tree, skyscraper, tank, squirrel, orchid, camel, otter, pine_tree, motorcycle, shark, lamp, mouse, bowl, chimpanzee, castle, mountain, bus, wolf, aquarium_fish, cloud