Skip to content
ModelListedExternal
Download

Tomadoc Flash

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...

KindOtherVersionRevision e5f5ce2

Model source

Kind
Other
File size
327 MB
Version
vRevision e5f5ce2
Updated
Sep 17, 2026
Downloads
8
Source
Hugging Face

Source description

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

Sources

1 source
Hugging FacePrimaryVersion e5f5ce2c1c104b019494fabd11417b7f06da73d3
huggingface.co/oshriagronov/tomadoc-flash/tree/e5f5ce2c1c104b019494fabd11417b7f06da73d3

Verified Sep 17

Model artifacts

1 artifact

model.safetensors

safetensors · 327 MB · SHA-256 312bf5cab4cc…a3e1 · Hugging Face

Download

Source excerpts

2 excerpts

--- 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