how to set threshold value by looking at loss distribution in anomaly detection task

I am following this tutorial https://towardsdatascience.com/lstm-autoencoder-for-anomaly-detection-e1f4f2ee7ccf to use LSTM autoencoder to detect anomalies in my unsupervised dataset. they plotted loss distribution and i plotted the same loss distribution on my dataset. given in image below

my question is how they are setting the threshold value by looking at the loss distribution. i also want to set threshold by looking at my loss distribution but not clear how can i select threshold. they are saying in tutorial By plotting the loss distribution of the calculated loss in the training set, we can determine a suitable threshold value for identifying an anomaly. In doing this, one can make sure that this threshold is set above the “noise level” so that false positives are not triggered