File size: 2,016 Bytes
1636428 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
base_model: google/vit-base-patch16-224
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
---
# Model-J: SupViT Model (model_idx_0492)
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
<p align="center">
🌐 <a href="https://horwitz.ai/probex" target="_blank">Project</a> | 📃 <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | 💻 <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | 🤗 <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a>
</p>
## Model Details
| Attribute | Value |
|---|---|
| **Subset** | SupViT |
| **Split** | train |
| **Base Model** | `google/vit-base-patch16-224` |
| **Dataset** | CIFAR100 (50 classes) |
## Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 492 |
| Random Crop | False |
| Random Flip | False |
## Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9995 |
| Val Accuracy | 0.9560 |
| Test Accuracy | 0.9512 |
## Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
`beaver`, `shrew`, `television`, `wolf`, `tank`, `cloud`, `aquarium_fish`, `clock`, `squirrel`, `rocket`, `tiger`, `road`, `bicycle`, `rose`, `boy`, `plain`, `butterfly`, `palm_tree`, `porcupine`, `telephone`, `bus`, `train`, `cup`, `crocodile`, `cattle`, `snake`, `orange`, `baby`, `pine_tree`, `mouse`, `caterpillar`, `wardrobe`, `leopard`, `elephant`, `willow_tree`, `trout`, `camel`, `sunflower`, `skyscraper`, `kangaroo`, `forest`, `flatfish`, `dolphin`, `can`, `chimpanzee`, `mountain`, `castle`, `whale`, `keyboard`, `tulip`
|