---
library_name: transformers
metrics:
- accuracy
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
An Image Classifier model fine-tuned on ViT. This model can classify garbage images.

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

- **Finetuned from model :** ViT

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/KomaliValluru/waste-classification

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

- Target classes: Battery, Biological, Brown-grass, Cardboard, Clothes, Green-Glass, Metal, Paper, Plastic, Shoes, Trash, White-Glass

## Training Details

### Training Data

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
https://www.kaggle.com/datasets/mostafaabla/garbage-classification

#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->
Accuracy

### Results

Accuracy: 98%

#### Summary

- **Hours used:** 1 hour 30 minutes
- **References:** Based on the model yangy50/garbage-classification