# TomatoACLv1
## Model Overview
**TomatoACLv1** is an object detection model trained from scratch using the **YOLO11n** architecture for tomato detection in images.
This repository includes the trained model weights in both **PyTorch (`.pt`)** and **ONNX (`.onnx`)** formats, along with training configuration and result files.
## Dataset
The model was trained using the following Kaggle dataset:
**Tomato Detection**
https://www.kaggle.com/datasets/andrewmvd/tomato-detection
## Training Details
- Architecture: **YOLO11n**
- Training strategy: **trained from scratch**
- Task: **object detection**
- Target object: **tomato**
## Repository Contents
- `tomatoACLv1.pt` — trained PyTorch model
- `tomatoACLv1.onnx` — exported ONNX model
- `args.yaml` — training arguments
- `data.yaml` — dataset configuration
- `metrics.json` — training metrics
- `results.png` — training summary image
## Training Results
Below is the training summary image generated during training:
