<p>I am training a neural network which produces the following errors (epoch number on the x axis). I have some questions regrading interpreting it.</p>

<ul>
<li><p>When I say <code>model.predict</code> is it giving me the result based on the final state (that is epoch 5000)?</p></li>
<li><p>Towards the end (and some places in the middle) there are places where the training error and validation error are farther apart. Does this mean that the model was over-fitting on those epochs?</p></li>
<li><p>Based on the graph, can one determine that the model was <code>best</code> at a certain epoch? </p></li>
<li><p>Does Keras have API methods to retrieve the model at a specific epoch so that I can retrieve the <code>best</code> model?</p></li>
</ul>

<p><a href="https://i.sstatic.net/jKlil.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/jKlil.png" alt="enter image description here"></a></p>

CC BY-SA 4.0
2019-06-09T14:56:23.987Z
@DuttaA thank you for your comment. Can you please elaborate? Also looking at the train error,there is a wave like pattern. Would you not say that the wave like pattern indicates that the model is learning (that is it was performing best when the wave was at a minimum?)
Can't Tell
CC BY-SA 4.0
2019-06-10T09:21:43.140Z
@DuttaA loss, as drawn in this example https://www.tensorflow.org/tutorials/keras/basic_regression, although the data is not the same. I just took the graph code from there
Can't Tell
CC BY-SA 4.0
2019-06-11T15:11:42.957Z
do you do measures agains over-fitting or maybe reduce leraning rate with the time?
user8426627
CC BY-SA 4.0
2019-06-12T11:02:50.373Z
@user8426627 I use Adam optimizer and I use Dropout
Can't Tell
CC BY-SA 4.0
2019-06-12T11:08:07.937Z
thats weird because even train error dont converge. Make learning rate smaller and try to run over small amount of epochs
user8426627
CC BY-SA 4.0
2019-06-12T11:21:30.993Z
@user8426627 thanks for the suggestion. I will try that
Can't Tell
<deep-learning><keras>
How can I interpret the following error graph?
Can't Tell
# How can I interpret the following error graph?

(Asked by: username_0 on 2019-06-09)

I am training a neural network which produces the following errors (epoch number on the x axis). I have some questions regrading interpreting it.

* When I say `model.predict` is it giving me the result based on the final state (that is epoch 5000)?
* Towards the end (and some places in the middle) there are places where the training error and validation error are farther apart. Does this mean that the model was over-fitting on those epochs?
* Based on the graph, can one determine that the model was `best` at a certain epoch?
* Does Keras have API methods to retrieve the model at a specific epoch so that I can retrieve the `best` model?

[![enter image description here](https://i.sstatic.net/jKlil.png)](https://i.sstatic.net/jKlil.png)

**Tags:** deep-learning, keras

> **Comments:**
> **username_0**: @DuttaA thank you for your comment. Can you please elaborate? Also looking at the train error,there is a wave like pattern. Would you not say that the wave like pattern indicates that the model is learning (that is it was performing best when the wave was at a minimum?)  
> **username_0**: @DuttaA loss, as drawn in this example https://www.tensorflow.org/tutorials/keras/basic_regression, although the data is not the same. I just took the graph code from there  
> **username_1**: do you do measures agains over-fitting or maybe reduce leraning rate with the time?  
> **username_0**: @username_1 I use Adam optimizer and I use Dropout  
> **username_1**: thats weird because even train error dont converge. Make learning rate smaller and try to run over small amount of epochs  
> **username_0**: @username_1 thanks for the suggestion. I will try that  

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## 0 answers

