# Training table doubts

**URL:** <https://support.prodi.gy/t/training-table-doubts/6125>\
**Category:** Uncategorized\
**Tags:** ner, training\
**Created:** [November 17, 2022, 12:37pm UTC](https://support.prodi.gy/t/training-table-doubts/6125 "2022-11-17T12:37:12Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![alvaro.marlo](https://avatars.discourse-cdn.com/v4/letter/a/b38774/32.png) [@alvaro.marlo](https://support.prodi.gy/u/alvaro.marlo)\
**Post date:** [November 17, 2022, 12:37pm UTC](https://support.prodi.gy/t/training-table-doubts/6125/1 "2022-11-17T12:37:12Z")

</div>

Hi,

What exactly means each column of the training table?  
**E | # | LOSS TOK2VEC | LOSS NER | ENTS\_F | ENTS\_P | ENTS\_R | SCORE**  
Is somewhere at the documentation? I don't see anything about it.

Also, I have trained a model that displays a 0 at every row of the training table at **E** column. Why is this happening? I have something wrong?

 ![image](https://us1.discourse-cdn.com/flex020/uploads/prodigy/original/2X/2/2b00e8f5b8bbdb55e4a68877bca7cf87864debec.png)

Thanks,  
Alvaro

---

<div class="post-metadata">

**Author:** ![ryanwesslen](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ryanwesslen/32/2969_2.png) [@ryanwesslen](https://support.prodi.gy/u/ryanwesslen)\
**Post date:** [November 17, 2022, 1:56pm UTC](https://support.prodi.gy/t/training-table-doubts/6125/2 "2022-11-17T13:56:20Z")

</div>

hi @alvaro.marlo!

Check out this previous post:

> [@understanding the different terminology in the command line output of a training pipeline](https://support.prodi.gy/t/understanding-the-different-terminology-in-the-command-line-output-of-a-training-pipeline/5719/2):
>
> Hi @nanyasrivastav! Thank you for your questions! These concepts are very important. I'm glad you've asked because it's hard to effectively use Prodigy without understanding them slight_smile. Initial learn rate: The initial learning rate used. The learning rate is a [tuning parameter](https://en.wikipedia.org/wiki/Hyperparameter_(machine_learning)) in an [optimization algorithm](https://en.wikipedia.org/wiki/Mathematical_optimization) that determines the step size at each iteration while moving toward a minimum of a [loss function](https://en.wikipedia.org/wiki/Loss_function). This is a default value but can be optimized for training. Optimizing the learning …

> [@alvaro.marlo](#):
>
> Also, I have trained a model that displays a 0 at every row of the training table at **E** column. Why is this happening? I have something wrong?

The "E" is epochs and it seems like your dataset is so large (240,000+ training), it can't make a full pass (epoch) on your entire dataset.

I found [this spaCy discussion](https://github.com/explosion/spaCy/discussions/8456) post on advice on training large NER datasets. They recommended a few suggestions like creating a labels file (more to speed up the process), modifying the learning rate (will need some experimentation), and reducing the evaluation set. If you have further questions related to training, I would recommend posting on the spaCy discussion as the spaCy core team answers those posts (and `prodigy train` is really just a wrapper for `spacy train`, so your questions are really spaCy questions).