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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
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