Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Woleek/camera-type with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Woleek/camera-type with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Woleek/camera-type") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Woleek/camera-type") model = AutoModelForImageClassification.from_pretrained("Woleek/camera-type") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "eval_accuracy": 0.9382716049382716, | |
| "eval_loss": 0.16537487506866455, | |
| "eval_runtime": 7.4881, | |
| "eval_samples_per_second": 75.72, | |
| "eval_steps_per_second": 9.482, | |
| "test_accuracy": 0.7333333333333333, | |
| "test_loss": 0.6995685696601868, | |
| "test_runtime": 0.645, | |
| "test_samples_per_second": 46.51, | |
| "test_steps_per_second": 6.201, | |
| "train_loss": 0.11905734094947872, | |
| "train_runtime": 363.8199, | |
| "train_samples_per_second": 55.412, | |
| "train_steps_per_second": 5.552 | |
| } |