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_0004)
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 | 5e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 4 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8256 |
| Val Accuracy | 0.8125 |
| Test Accuracy | 0.8008 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
palm_tree, rabbit, caterpillar, camel, plate, table, cattle, skyscraper, snake, sweet_pepper, forest, willow_tree, couch, squirrel, cockroach, clock, bear, bottle, shark, rocket, house, skunk, lion, poppy, sunflower, turtle, orange, wolf, dolphin, telephone, bridge, cloud, castle, whale, lobster, wardrobe, crab, trout, mushroom, lizard, lamp, woman, mountain, pear, bee, pine_tree, tiger, aquarium_fish, ray, chimpanzee