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_0304)
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 |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 304 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9382 |
| Val Accuracy | 0.8792 |
| Test Accuracy | 0.8776 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
sweet_pepper, sea, trout, rocket, plain, apple, snake, camel, mouse, motorcycle, orchid, bridge, kangaroo, forest, cup, tractor, tiger, pickup_truck, butterfly, mushroom, lawn_mower, cockroach, cattle, maple_tree, pine_tree, woman, beetle, lizard, chimpanzee, fox, aquarium_fish, seal, bus, bicycle, wardrobe, baby, leopard, raccoon, girl, bee, streetcar, shrew, skyscraper, porcupine, dolphin, shark, rabbit, wolf, pear, elephant