# What number and quality of images are needed for labeling and fine-tuning a pretrained model?

**URL:** <https://community.labelstud.io/t/what-number-and-quality-of-images-are-needed-for-labeling-and-fine-tuning-a-pretrained-model/436>\
**Category:** Label Studio Support\
**Tags:** annotations\
**Created:** [December 25, 2024, 4:55pm UTC](https://community.labelstud.io/t/what-number-and-quality-of-images-are-needed-for-labeling-and-fine-tuning-a-pretrained-model/436 "2024-12-25T16:55:33Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![roman\_dimakov](https://avatars.discourse-cdn.com/v4/letter/r/74df32/32.png) [@roman\_dimakov](https://community.labelstud.io/u/roman_dimakov)\
**Post date:** [December 25, 2024, 4:55pm UTC](https://community.labelstud.io/t/what-number-and-quality-of-images-are-needed-for-labeling-and-fine-tuning-a-pretrained-model/436/1 "2024-12-25T16:55:33Z")

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Hello!

I am new to Label Studio and Layout Parser and would greatly appreciate your help with a couple of questions about image annotation for subsequent model fine-tuning (using scripts from this page: [GitHub - Layout-Parser/layout-model-training: The scripts for training Detectron2-based Layout Models on popular layout analysis datasets](https://github.com/Layout-Parser/layout-model-training/tree/master)).

1. How many images would be sufficient to label in Label Studio to fine-tune a pre-trained model (e.g., Faster R-CNN)?  
My dataset contains approximately 15,000 images. ChatGPT suggests labeling 100–200 images initially and 500+ for better performance. In contrast, Copilot recommends labeling 2,000–3,000 images to start.

2. Do the quality of images and the number/types of labels per image affect the speed of model fine-tuning?  
My images are in PNG format, RGB color space, and have a resolution of 1800x1200.

I look forward to your response!

Best regards,  
Roman