https://opennlp.apache.org/docs/1.8.0/manual/opennlp.html#tools.lemmatizer.training

The example of training is with a perceptron. An example (with default
features) can be found here:

https://github.com/apache/opennlp/blob/master/opennlp-tools/lang/ml/PerceptronTrainerParams.txt

Best,

R

On Wed, 26 Feb 2020 at 11:02, Markus Jelsma <markus.jel...@openindex.io> wrote:
>
> Hello Rodrigo,
>
> Although i am using the Java API mainly, i use the CLI tools for the training 
> jobs. And although there is some sporadic mention of Perceptron in the 
> manual, i have not been able to find any CLI tool that supports training a 
> Perceptron type model.
>
> How do you do it? I use v1.9.2.
>
> Thanks,
> Markus
>
> -----Original message-----
> > From:Rodrigo Agerri <rage...@apache.org>
> > Sent: Friday 21st February 2020 16:42
> > To: users@opennlp.apache.org
> > Subject: Re: LemmatizerTrainerME gets stuck with GaussianSmoothing enabled
> >
> > Hello,
> >
> > I do not know why is this happening, but while testing the lemmatizer
> > the best performance (word and sentence accuracy) was always obtained
> > using the Perceptron trainer (for a number of languages), so I would
> > recommend to train perceptron models (perhaps you have already tried
> > this, but just in case).
> >
> > Best,
> >
> > R
> >
> >
> >
> >
> >
> >
> > On Fri, 21 Feb 2020 at 16:07, Markus Jelsma <markus.jel...@openindex.io> 
> > wrote:
> > >
> > > Hello,
> > >
> > > When GaussianSmoothing is enabled, the LemmatizerTrainerME gets stuck. 
> > > The loglikelihood gets warped to NaN right after the first iteration, 
> > > like so:
> > > Computing model parameters in 16 threads...
> > > Performing 10000 iterations.
> > >   1:  ... loglikelihood=-1238383.3965208859     0.8032247485201534
> > >   2:  ... loglikelihood=NaN     0.8178054720724305
> > >   3:  ... loglikelihood=NaN     0.8032247485201534
> > >   4:  ... loglikelihood=NaN     0.8032247485201534
> > >
> > > Is this known to happen? Did i stumble upon some bug?
> > >
> > > Many thanks,
> > > Markus
> >

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