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Price Tag Classification

This image classification model was fine-tuned using the Ultralytics YOLO library.

TipoOtherModelo baseyolov8n-cls.ptVersãoRevision 4c068b4

Fonte do modelo

Tipo
Other
Tamanho do arquivo
2,86–5,52 MB
Modelo base
yolov8n-cls.pt
Versão
vRevision 4c068b4
Atualizado
28 de set. de 2026
Downloads
14
Fonte
Hugging Face

Descrição da fonte

Model Card for price-tag-classification

Wandb run

This image classification model was fine-tuned using the Ultralytics YOLO library.

Model Details

Model Description

  • Developed by: Open Food Facts
  • Model type: image classification
  • License: agpl-3.0
  • Finetuned from model: yolov8n-cls.pt

Training Details

Training Data

The model was fine-tuned using the following dataset: openfoodfacts/price-tag-classification (revision: v1.0).

Training Procedure

Dependency versions:

  • ultralytics: 8.4.14
  • pytorch: 2.9.0+cu128

Training Hyperparameters

  • Epochs: 100
  • Batch size: 4
  • Image size: 960

Evaluation

The following evaluation metrics were obtained after training the model:

  • metrics/accuracy_top1: 0.9489558935165405

  • metrics/accuracy_top5: 1.0

  • fitness: 0.9744779467582703

Evaluation on exported models

The model was also evaluated after exporting to ONNX and TensorRT formats. The following metrics were obtained:

ONNX export

  • metrics/accuracy_top1: 0.9489558935165405

  • metrics/accuracy_top5: 1.0

  • fitness: 0.9744779467582703

Files

Most files stored on the repo are standard files created during training with the Ultralytics YOLO library.

What was added:

  • an ONNX export of the trained model (best model), stored in weights/model.onnx.
  • a Parquet file containing predictions on the full dataset, stored in predictions.parquet.
  • metrics JSON files for each exported model format, stored in metrics_*.json:
    • metrics.json: metrics for the original PyTorch model
    • metrics_onnx.json: metrics for the ONNX exported model

Fontes

1 fonte
Hugging FacePrimárioVersão 4c068b441a76bc59c800caa2111dfd3694d1ed30
huggingface.co/openfoodfacts/price-tag-classification/tree/4c068b441a76bc59c800caa2111dfd3694d1ed30

Verificado 28 de set.

Artefatos de modelo

3 artefatos

weights/best.pt

pt · 2,86 MB · SHA-256 330babdbf949…7fa1 · Hugging Face

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weights/last.pt

pt · 2,86 MB · SHA-256 5a8263223ad3…47bd · Hugging Face

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weights/model.onnx

onnx · 5,52 MB · SHA-256 0ca892c934e5…8d66 · Hugging Face

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Trechos de fonte

2 trechos

--- base_model: yolov8n-cls.pt datasets: - openfoodfacts/price-tag-classification library_name: ultralytics license: agpl-3.0 pipeline_tag: image-classification --- # Model Card for price-tag-classification [Wandb run](https://wandb.ai/raphaeloff/price-tag-classification/runs/yolov8n-cls-e-100-custom-augmentation_20260316_090615) This image classification model was fine-tuned using the Ultralytics YOLO library. ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** Open Food Facts - **Model type:** image classification - **License:** agpl-3.0 - **Finetuned from model:** yolov8n-cls.pt ## Training Details ### Training Data The model was fine-tuned using the following dataset: [openfoodfacts/price-tag-classification](https://huggingface.co/datasets/openfoodfacts/price-tag-classification) (revision: `v1.0`). ### Training Procedure Dependency versions: - ultralytics: 8.4.14 - pytorch: 2.9.0+cu128 #### Training Hyperparameters - **Epochs:** 100 - **Batch size:** 4 - **Image size:** 960 ## Evaluation The following evaluation metrics were obtained after training the model: - **metrics/accuracy_top1:** 0.9489558935165405 - **metrics/accuracy_top5:** 1.0 - **fitness:** 0.9744779467582703 ### Evaluation on exported models The model was also evaluated after exporting to ONNX and TensorRT formats. The following metrics were obtained: #### ONNX export - **metrics/accuracy_top1:** 0.9489558935165405 - **metrics/accuracy_top5:** 1.0 - **fitness:** 0.9744779467582703 ## Files Most files stored on the repo are standard files created during training with the Ultralytics YOLO library. What was added: - an ONNX export of the trained model (best model), stored in `weights/model.onnx`. - a Parquet file containing predictions on the full dataset, stored in `predictions.parquet`. - metrics JSON files for each exported model format, stored in `metrics_*.json`: - `metrics.json`: metrics for the original PyTorch model - `metrics_onnx.json`: metrics for the ONNX exported model

Source context: 14 downloads · 0 likes · Pipeline image-classification · Library ultralytics · Repo openfoodfacts/price-tag-classification