diff --git a/website/site/content/docs/configure/_index.md b/website/site/content/docs/configure/_index.md
index dccce7d9..81e697a6 100644
--- a/website/site/content/docs/configure/_index.md
+++ b/website/site/content/docs/configure/_index.md
@@ -290,7 +290,8 @@ Files are being processed by the joex component. So all the respective
 configuration is in this config only.
 
 File processing involves several stages, detailed information can be
-found [here](@/docs/joex/file-processing.md#text-analysis).
+found [here](@/docs/joex/file-processing.md#text-analysis) and in the
+corresponding sections in [joex default config](#joex).
 
 Configuration allows to define the external tools and set some
 limitations to control memory usage. The sections are:
@@ -301,9 +302,25 @@ limitations to control memory usage. The sections are:
 
 Options to external commands can use variables that are replaced by
 values at runtime. Variables are enclosed in double braces `{{…}}`.
-Please see the default configuration for more details.
+Please see the default configuration for what variables exist per
+command.
 
-### `text-analysis.nlp.mode`
+### Classification
+
+In `text-analysis.classification` you can define how many documents at
+most should be used for learning. The default settings should work
+well for most cases. However, it always depends on the amount of data
+and the machine that runs joex. For example, by default the documents
+to learn from are limited to 600 (`classification.item-count`) and
+every text is cut after 8000 characters (`text-analysis.max-length`).
+This is fine if *most* of your documents are small and only a few are
+near 8000 characters). But if *all* your documents are very large, you
+probably need to either assign more heap memory or go down with the
+limits.
+
+Classification can be disabled, too, for when it's not needed.
+
+### NLP
 
 This setting defines which NLP mode to use. It defaults to `full`,
 which requires more memory for certain languages (with the advantage
@@ -329,10 +346,7 @@ is used to find metadata.
 You might want to try different modes and see what combination suits
 best your usage pattern and machine running joex. If a powerful
 machine is used, simply leave the defaults. When running on an older
-raspberry pi, for example, you might need to adjust things. The
-corresponding sections in [joex default config](#joex) and the [file
-processing](@/docs/joex/file-processing.md#text-analysis) page provide more
-details.
+raspberry pi, for example, you might need to adjust things.
 
 # File Format
 
diff --git a/website/site/content/docs/joex/file-processing.md b/website/site/content/docs/joex/file-processing.md
index 8deb83f5..506dd8e0 100644
--- a/website/site/content/docs/joex/file-processing.md
+++ b/website/site/content/docs/joex/file-processing.md
@@ -363,12 +363,17 @@ related to a tag, a corrpesondent etc.
 When a new document arrives, this model is used to ask for what
 metadata (tag, correspondent, etc) it thinks is likely to apply here.
 
-Training the model is a rather resource intensive process, but using
-an existing model is quite cheap and fast. A model is trained
-periodically, the schedule can be defined in your collective settings.
-For tags, you can define the tag categories that should be trained (or
-that should not be trained). Docspell assigns one tag from all tags in
-a category to a new document.
+Training the model is a rather resource intensive process. How much
+memory is needed, depends on the number of documents to learn from and
+the size of text to consider. Both can be limited in the config file.
+The default values might require a heap of 1.4G if you have many and
+large documents. The maximum text length is about 8000 characters, if
+*all* your documents would be that large, adjusting these values might
+be necessary. But using an existing model is quite cheap and fast. A
+model is trained periodically, the schedule can be defined in your
+collective settings. For tags, you can define the tag categories that
+should be trained (or that should not be trained). Docspell assigns
+one tag from all tags in a category to a new document.
 
 Note that tags that can not be derived from the text only, should
 probably be excluded from learning. For example, if you tag all your