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_0011)
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 | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 11 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9303 |
| Val Accuracy | 0.8539 |
| Test Accuracy | 0.8550 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
willow_tree, bee, pine_tree, fox, man, girl, mushroom, television, telephone, clock, wolf, motorcycle, otter, elephant, chimpanzee, boy, castle, seal, bicycle, beaver, ray, possum, crocodile, dolphin, porcupine, whale, hamster, bus, camel, squirrel, streetcar, bridge, cloud, pickup_truck, orchid, tiger, worm, baby, bed, lobster, lizard, trout, table, plate, rose, sweet_pepper, rabbit, orange, can, chair