diff --git a/assets/locales/en.json b/assets/locales/en.json
index 29a07cc..eb724eb 100644
--- a/assets/locales/en.json
+++ b/assets/locales/en.json
@@ -99,7 +99,7 @@
     "command_markov_retrain": "Retraining the Markov model... Please wait.",
     "command_markov_memory_not_found": "Error: memory file not found!",
     "command_markov_memory_is_corrupt": "Error: memory file is corrupt!",
-    "command_markov_retraining": "Processing {processed_data}/{data_size} data points...",
+    "command_markov_retraining": "Processing {data_size} data points...",
     "command_markov_retrain_successful": "Markov model retrained successfully using {data_size} data points!",
     "command_desc_talk":"talks n like stuf",
     "command_talk_insufficent_text": "I need to learn more from messages before I can talk.",
diff --git a/assets/locales/it.json b/assets/locales/it.json
index 734e0d2..efb5a60 100644
--- a/assets/locales/it.json
+++ b/assets/locales/it.json
@@ -100,7 +100,7 @@
     "command_markov_retrain": "Rafforzamento del modello Markov in corso... Attendere.",
     "command_markov_memory_not_found": "Errore: file di memoria non trovato!",
     "command_markov_memory_is_corrupt": "Errore: file di memoria corrotto!",
-    "command_markov_retraining": "Elaborazione di {processed_data}/{data_size} punti dati...",
+    "command_markov_retraining": "Elaborazione di {data_size} punti dati...",
     "command_markov_retrain_successful": "Modello Markov rafforzato con successo utilizzando {data_size} punti dati!",
     "command_desc_talk": "parla n come stuf",
     "command_talk_insufficent_text": "Ho bisogno di imparare di più dai messaggi prima di poter parlare.",
diff --git a/bot.py b/bot.py
index 4e53488..358ef07 100644
--- a/bot.py
+++ b/bot.py
@@ -180,8 +180,6 @@ async def retrain(ctx: commands.Context) -> None:
     
     for i, data in enumerate(memory):
         processed_data += 1
-        if processed_data % 1000 == 0 or processed_data == data_size:
-            await send_message(ctx, f"{_('command_markov_retraining').format(processed_data=processed_data, data_size=data_size)}", edit=True, message_reference=processing_message_ref)
 
     global markov_model
     markov_model = train_markov_model(memory)