diff --git a/data/lm/README.rst b/data/lm/README.rst
index beba5dbc..ed7f017d 100644
--- a/data/lm/README.rst
+++ b/data/lm/README.rst
@@ -29,4 +29,4 @@ Afterwards you can use ``generate_package.py`` to generate the scorer package us
 .. code-block:: bash
 
     python3 generate_package.py --alphabet ../alphabet.txt --lm lm.binary --vocab vocab-500000.txt \
-      --package kenlm.scorer --default_alpha 0.75 --default_beta 1.85
+      --package kenlm.scorer --default_alpha 0.931289039105002 --default_beta 1.1834137581510284
diff --git a/data/lm/kenlm.scorer b/data/lm/kenlm.scorer
index 02d5de6c..d8581c05 100644
--- a/data/lm/kenlm.scorer
+++ b/data/lm/kenlm.scorer
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3ba04978fca285c34c99bf115ee61549937e422ac91def80122a767e114c035e
-size 953436352
+oid sha256:d0cf926ab9cab54a8a7d70003b931b2d62ebd9105ed392d1ec9c840029867799
+size 953363776
diff --git a/training/deepspeech_training/util/flags.py b/training/deepspeech_training/util/flags.py
index 63bc7bb4..fde946cc 100644
--- a/training/deepspeech_training/util/flags.py
+++ b/training/deepspeech_training/util/flags.py
@@ -174,8 +174,8 @@ def create_flags():
     f.DEFINE_string('scorer_path', 'data/lm/kenlm.scorer', 'path to the external scorer file created with data/lm/generate_package.py')
     f.DEFINE_alias('scorer', 'scorer_path')
     f.DEFINE_integer('beam_width', 1024, 'beam width used in the CTC decoder when building candidate transcriptions')
-    f.DEFINE_float('lm_alpha', 0.75, 'the alpha hyperparameter of the CTC decoder. Language Model weight.')
-    f.DEFINE_float('lm_beta', 1.85, 'the beta hyperparameter of the CTC decoder. Word insertion weight.')
+    f.DEFINE_float('lm_alpha', 0.931289039105002, 'the alpha hyperparameter of the CTC decoder. Language Model weight.')
+    f.DEFINE_float('lm_beta', 1.1834137581510284, 'the beta hyperparameter of the CTC decoder. Word insertion weight.')
     f.DEFINE_float('cutoff_prob', 1.0, 'only consider characters until this probability mass is reached. 1.0 = disabled.')
     f.DEFINE_integer('cutoff_top_n', 300, 'only process this number of characters sorted by probability mass for each time step. If bigger than alphabet size, disabled.')