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_0404)
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 | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 404 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8966 |
| Val Accuracy | 0.8365 |
| Test Accuracy | 0.8422 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bee, dinosaur, lion, turtle, trout, squirrel, oak_tree, fox, cockroach, television, bicycle, forest, maple_tree, leopard, worm, tulip, butterfly, streetcar, pear, snail, crab, rose, woman, lizard, rocket, bed, bowl, clock, man, whale, rabbit, lobster, couch, skyscraper, cup, tractor, sea, seal, cloud, tank, plain, cattle, castle, caterpillar, boy, girl, plate, orchid, telephone, skunk