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_0079)
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 | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 79 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9635 |
| Val Accuracy | 0.8595 |
| Test Accuracy | 0.8612 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, keyboard, spider, castle, crab, boy, forest, tank, shark, lion, porcupine, maple_tree, cockroach, crocodile, mountain, bridge, beetle, orchid, bear, ray, mushroom, woman, worm, motorcycle, otter, cup, telephone, table, orange, kangaroo, wardrobe, palm_tree, butterfly, rocket, pine_tree, train, chimpanzee, trout, raccoon, sea, willow_tree, mouse, shrew, beaver, lizard, elephant, wolf, cloud, couch, lawn_mower