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_0298)
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 | 0.0003 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 298 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9837 |
| Val Accuracy | 0.8968 |
| Test Accuracy | 0.8970 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lobster, apple, butterfly, flatfish, crab, table, cockroach, plain, maple_tree, orchid, tank, ray, orange, bus, bed, cup, tiger, bee, beetle, caterpillar, mushroom, wardrobe, willow_tree, motorcycle, sea, keyboard, lawn_mower, tractor, rocket, worm, snake, lizard, wolf, possum, bridge, kangaroo, hamster, crocodile, skunk, otter, cloud, oak_tree, trout, sunflower, elephant, seal, bicycle, couch, beaver, fox