Model-J DINO
Collection
1002 items • Updated
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0771")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0771")Quick Links
Model-J: DINO Model (model_idx_0771)
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 | DINO |
| Split | train |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 771 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9574 |
| Val Accuracy | 0.8403 |
| Test Accuracy | 0.8438 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
beaver, castle, girl, keyboard, otter, pickup_truck, cup, butterfly, oak_tree, bottle, pine_tree, lobster, maple_tree, trout, apple, bear, porcupine, crocodile, caterpillar, lamp, sea, ray, bridge, man, poppy, wardrobe, skunk, orchid, fox, seal, bee, worm, mushroom, leopard, beetle, cattle, snake, dinosaur, wolf, sweet_pepper, streetcar, willow_tree, baby, cockroach, train, can, chimpanzee, shark, dolphin, hamster
- Downloads last month
- 1
Model tree for ProbeX/Model-J__DINO__model_idx_0771
Base model
facebook/dino-vitb16
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0771") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")