简体   繁体   中英

Could not understand if my CNN model for multiclass classification is overfitted or not?

Good training, testing and validation accuracies but strange historical accuracies behavior for model: Here is the summary of my model:

在此处输入图像描述

I performed the execution and prediction tasks and I've got the next confusion matrix:

在此处输入图像描述

while the Accuracy behavior was the next:

在此处输入图像描述

I can not understand if this is overfitting or underfitting or a normal behavior?

Adding the loss plot to clarify more in the next

数字

Thank you in advance for any useful information and help !

Does not look like over fitting. Your training accuracy is increasing and so is the AVERAGE test accuracy. Over fitting is when the test loss improves, then plateaus and then starts to increase. It is best to look at loss metrics to monitor this. It is typical that once the training accuracy gets high the test loss will oscillate to a small degree. You can test for over fitting by varying the drop out rate and see the effect on test loss.

As you already mentioned your training is doing well.

First of all I recommend you to check a prediction by yourself with test-data. The Validation-loss will converge until a specific value. It may looks a little bit variance but you need as reference the y-Axis. The ups and downs of the last epochs are between 91% and 94% which is not really much in reference to 100% (maybe change the y-Axis).

The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM