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_0252)
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 | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 252 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9781 |
| Val Accuracy | 0.8989 |
| Test Accuracy | 0.8966 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cup, bed, otter, squirrel, tank, mountain, shrew, baby, pickup_truck, bridge, lobster, road, castle, plain, chimpanzee, raccoon, pear, bee, apple, dinosaur, tulip, bus, shark, lion, rocket, can, mushroom, wolf, caterpillar, bowl, porcupine, motorcycle, table, beaver, kangaroo, palm_tree, wardrobe, orchid, whale, pine_tree, lawn_mower, plate, camel, aquarium_fish, cockroach, leopard, poppy, willow_tree, crocodile, butterfly