diff --git a/docs/benchmarks/index.md b/docs/benchmarks/index.md
index ca5067d29b..87c835c282 100644
--- a/docs/benchmarks/index.md
+++ b/docs/benchmarks/index.md
@@ -10,19 +10,19 @@ hide:
 
 <pre>Python implementation: CPython
 Python version       : 3.9.12
-IPython version      : 8.3.0
+IPython version      : 7.30.1
 
-river       : 0.11.1
+river       : 0.12.1
 numpy       : 1.22.3
-scikit-learn: 1.1.1
+scikit-learn: 1.1.0
 pandas      : 1.4.1
-scipy       : 1.8.0
+scipy       : 1.9.0
 
-Compiler    : Clang 12.0.0 
+Compiler    : Clang 12.0.1 
 OS          : Darwin
-Release     : 21.4.0
-Machine     : arm64
-Processor   : arm
+Release     : 21.5.0
+Machine     : x86_64
+Processor   : i386
 CPU cores   : 8
 Architecture: 64bit
 </pre>
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diff --git a/river/stats/lossy.py b/river/stats/lossy.py
index c318a009d8..20dc4b1051 100644
--- a/river/stats/lossy.py
+++ b/river/stats/lossy.py
@@ -18,9 +18,11 @@ class LossyCount(stats.base.Univariate):
     algorithm has the following properties:
 
     - All item(set)s whose true frequency exceeds `support * n` are output. There are no
-    false negatives;
-    - No item(set) whose true frequency is less than `(support - epsilon) * n` is outputted;
-    - Estimated frequencies are less than the true frequencies by at most `epsilon * n`.
+    false negatives
+
+    - No item(set) whose true frequency is less than `(support - epsilon) * n` is outputted
+
+    - Estimated frequencies are less than the true frequencies by at most `epsilon * n`
 
     Parameters
     ----------