<p>I have an image dataset of about 400 images. 70% of these data points were used for training, 15% for validation, and 15% for testing. I am using the 70% to train a CNN-based binary classifier. I augmented the <em>training</em> data to around 8000 images. That makes my test set really small in comparison. Is that ok, and what is considered a decent size of images for a test set?</p>

CC BY-SA 4.0
2020-07-15T22:05:05.000Z
Also, I am an hs student who is really new to machine learning and would appreciate any advice :)
user38639
CC BY-SA 4.0
2020-07-16T01:16:58.917Z
Depends on the complexity of the task. I know I have previously achieved high accuracy on MNIST with a similarly low amount of training data.
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<neural-networks><convolutional-neural-networks><training><testing><data-augmentation>
What is the amount of test data needed to evaluate a CNN?
user38639
# What is the amount of test data needed to evaluate a CNN?

(Asked by: username_0 on 2020-07-15)

I have an image dataset of about 400 images. 70% of these data points were used for training, 15% for validation, and 15% for testing. I am using the 70% to train a CNN-based binary classifier. I augmented the *training* data to around 8000 images. That makes my test set really small in comparison. Is that ok, and what is considered a decent size of images for a test set?

**Tags:** neural-networks, convolutional-neural-networks, training, testing, data-augmentation

> **Comments:**
> **username_0**: Also, I am an hs student who is really new to machine learning and would appreciate any advice :)  
> **username_1**: Depends on the complexity of the task. I know I have previously achieved high accuracy on MNIST with a similarly low amount of training data.  

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## 0 answers

