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_0809")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0809")Quick Links
Model-J: DINO Model (model_idx_0809)
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 | test |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 3e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 809 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9881 |
| Val Accuracy | 0.8995 |
| Test Accuracy | 0.9122 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
television, wolf, bridge, flatfish, skyscraper, castle, dinosaur, crab, caterpillar, squirrel, clock, sea, wardrobe, plate, shark, lawn_mower, pear, bottle, seal, hamster, bicycle, worm, bed, trout, raccoon, rabbit, porcupine, cockroach, pickup_truck, beaver, lion, whale, table, spider, tank, mushroom, kangaroo, camel, otter, willow_tree, oak_tree, orange, lamp, mouse, bee, pine_tree, palm_tree, orchid, leopard, chair
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Model tree for ProbeX/Model-J__DINO__model_idx_0809
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_0809") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")