This model is a fine-tuned version of google/vit-base-patch16-224 designed to identify the exact ripening stage of a tomato. It was trained on the extensive FreshCheck dataset to provide highly accurate agricultural...
Modellquelle
Quellenbeschreibung
This model is a fine-tuned version of google/vit-base-patch16-224 designed to identify the exact ripening stage of a tomato. It was trained on the extensive FreshCheck dataset to provide highly accurate agricultural insights for the Tomadoc application.
Quellen
1 QuelleVerifiziert 17. Sept.
Modellartefakte
1 ArtefaktQuellenauszüge
2 Auszüge--- language: - en license: mit tags: - image-classification - vit - agriculture - tomato-ripeness - freshcheck metrics: - accuracy pipeline_tag: image-classification --- # Tomadoc Advanced Tomato Ripeness Classifier This model is a fine-tuned version of `google/vit-base-patch16-224` designed to identify the exact ripening stage of a tomato. It was trained on the extensive FreshCheck dataset to provide highly accurate agricultural insights for the Tomadoc application. ## Model Description - **Model Type:** Vision Transformer (ViT) - **Task:** Image Classification - **Classes:** Unripe, Ripe, Overripe, Damaged - **Base Model:** google/vit-base-patch16-224 ## Training & Hardware Details - **Dataset:** FreshCheck Fruit Ripeness Classification Dataset - **Hardware Used:** NVIDIA T4 GPU - **Precision:** Mixed Precision (FP16) - **Evaluation Strategy:** Epoch-based - **Learning Rate:** 2e-5 - **Epochs:** 5 ## Evaluation Results - **Final Test Accuracy:** 0.9983
Source context: 8 downloads · 0 likes · Pipeline image-classification · Repo oshriagronov/tomadoc-flash