# accuracy not improving much with ner.batch-train

**URL:** <https://support.prodi.gy/t/accuracy-not-improving-much-with-ner-batch-train/2280>\
**Category:** Uncategorized\
**Tags:** usage, ner\
**Created:** [December 4, 2019, 3:44pm UTC](https://support.prodi.gy/t/accuracy-not-improving-much-with-ner-batch-train/2280 "2019-12-04T15:44:25Z")\
**Posts on this page:** 1\
**Showing post:** 15

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**Author:** ![Pedram](https://avatars.discourse-cdn.com/v4/letter/p/82dd89/32.png) [@Pedram](https://support.prodi.gy/u/Pedram)\
**Post date:** [December 19, 2019, 1:54pm UTC](https://support.prodi.gy/t/accuracy-not-improving-much-with-ner-batch-train/2280/15 "2019-12-19T13:54:37Z")

</div>

Hello,

I had an issue training my model, I realised it was because I was not merging entities for the same text. I can see from the way you are collecting your training data, you might get similar issue.

For example, you cannot train your model with these two training data:  
("Google and Apple are companies.", {'entities': [(0, 6, 'Company')]})  
("Google and Apple are companies.", {'entities': [(11, 16, 'Company')]})

Instead you need to have:  
("Google and Apple are companies.", {'entities': [(0, 6, 'Company'), (11, 16, 'Company')]})

Also don't remove any training data with no entities, for example:  
("Apple is a fruit.", {'entities': []})  
is a useful training data.

I'm new to Spacy, please correct me if I'm wrong.  
I hope it helps.

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