Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
convnext
vision
Generated from Trainer
Instructions to use davanstrien/convnext-tiny-224-leicester_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/convnext-tiny-224-leicester_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="davanstrien/convnext-tiny-224-leicester_binary") 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("davanstrien/convnext-tiny-224-leicester_binary") model = AutoModelForImageClassification.from_pretrained("davanstrien/convnext-tiny-224-leicester_binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.9166666666666666, | |
| "eval_f1": 0.4782608695652174, | |
| "eval_loss": 0.4212849736213684, | |
| "eval_precision": 0.4583333333333333, | |
| "eval_recall": 0.5, | |
| "eval_runtime": 11.3877, | |
| "eval_samples_per_second": 6.323, | |
| "eval_steps_per_second": 0.088, | |
| "train_loss": 0.5020092555454799, | |
| "train_runtime": 64.4673, | |
| "train_samples_per_second": 6.329, | |
| "train_steps_per_second": 0.109 | |
| } |