Eval metrics per class

[Mahmoud1Ali3ng]

My dataset does not contain the famous entity classes PER, ORG, ... it contains instead nine other classes [NE001-NE009] but I did not get a detailed metric report that contains each class accuracy, recall and f-measure when running nerTagger.py either with train_eval or eval.
PS: I used --fold-count 1 or not specified at all.
How can I show them like this, for example :

Evaluation on test set:
f1 (micro): 91.35
precision recall f1-score support

        NE001   0.8795    0.9007    0.8899      1661
        NE002   0.9647    0.9623    0.9635      1617
        ............    ............     ............     ............        .........
        NE009   0.9260    0.9305    0.9282      1668

avg / total     0.9109    0.9161    0.9135      5648

[Mahmoud1Ali3ng]

I just run the eval for more fold-count > 1