beer-classificator

Model Card for Model ID

Student project

Beer classification model Finetuned from vit-base 65 classes Manually collected dataset

Model Details

Model Description

• Developed by: Karetnikov Roman Khmilevsky Alexey Koreshkov Nicolay
• Model type: Vit for image classification
• License: MIT
• Finetuned from model: google/vit-base-patch16-224

Uses

Use for classification of beer from enlisted types

Bias, Risks, and Limitations

May not be 100% accurate

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

from transformers import ViTForImageClassification, ViTImageProcessor

model = ViTForImageClassification.from_pretrained("ramnck/beer-classificator")
processor = ViTImageProcessor.from_pretrained("ramnck/beer-classificator")

Training Details

Training Data

65 classes, around 50 photos per class, all photos was taken by our hands

Training Procedure

SFT

Preprocessing [optional]

Resize to 224x224

Training Hyperparameters

look in .ipynb

Speeds, Sizes, Times [optional]

idk

Evaluation

yes

Testing Data, Factors & Metrics

Testing Data

yes

Factors

it`s bad testing data (looks very alike as train data)

Metrics

Final Test Accuracy: 0.9982

Results

it works

Summary

have a nice day

Environmental Impact

i ate 20 KFC wings during train i hope i spoiled air as much as it was possible

Model Card Contact

write me on my HF/GH