diff --git a/notebooks/piper_multilingual_training_notebook.ipynb b/notebooks/piper_multilingual_training_notebook.ipynb
index 338d6a4..c156b0e 100644
--- a/notebooks/piper_multilingual_training_notebook.ipynb
+++ b/notebooks/piper_multilingual_training_notebook.ipynb
@@ -5,7 +5,7 @@
     "colab": {
       "provenance": [],
       "gpuType": "T4",
-      "authorship_tag": "ABX9TyNiXaJjWsxcoKeHr7HeL2eD",
+      "authorship_tag": "ABX9TyN5orawFZNYEhhbtJPe+1fd",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -250,7 +250,11 @@
         "dataset_format = \"ljspeech\" #@param [\"ljspeech\", \"mycroft\"]\n",
         "#@markdown ---\n",
         "#@markdown ### Is this a single speaker dataset? Otherwise, uncheck:\n",
-        "single-speaker = True #@param {type:\"boolean\"}\n",
+        "single_speaker = True #@param {type:\"boolean\"}\n",
+        "if single_speaker:\n",
+        "  force_sp = \" --single-speaker\"\n",
+        "else:\n",
+        "  force_sp = \"\"\n",
         "#@markdown ---\n",
         "#@markdown ### Select the sample rate of the dataset\n",
         "sample_rate = \"16000\" #@param [\"16000\", \"22050\"]\n",
@@ -261,8 +265,8 @@
         "  --input-dir /content/dataset \\\n",
         "  --output-dir {output_dir} \\\n",
         "  --dataset-format {dataset_format} \\\n",
-        "  --sample-rate {sample_rate}|\n",
-        "  --single-speaker {single-speaker}"
+        "  --sample-rate {sample_rate} \\\n",
+        "  {force_sp}"
       ],
       "metadata": {
         "cellView": "form",
@@ -319,14 +323,14 @@
         "#@markdown * high - 22.05Khz audio, 28-32M params\n",
         "quality = \"x-low\" #@param [\"high\", \"x-low\", \"medium\"]\n",
         "#@markdown ---\n",
-        "#@markdown ### For how many steps to save training checkpoints?\n",
+        "#@markdown ### For how many epochs to save training checkpoints?\n",
         "checkpoint_epochs = 25 #@param {type:\"integer\"}\n",
         "#@markdown ---\n",
         "#@markdown ### Step interval to generate model samples\n",
         "log_every_n_steps = 250 #@param {type:\"integer\"}\n",
         "#@markdown ---\n",
         "#@markdown ### training epochs\n",
-        "max_epochs = 5000 #@param {type:\"integer\"}\n",
+        "max_epochs = 10000 #@param {type:\"integer\"}\n",
         "#@markdown ---"
       ],
       "metadata": {
@@ -356,6 +360,8 @@
       "cell_type": "code",
       "source": [
         "#@markdown ## 6. Train\n",
+        "\n",
+        "#@markdown **Note: Remember to empty the trash of your Drive from time to time to avoid a lot of space consumption when saving the models.**\n",
         "!python -m piper_train \\\n",
         "    --dataset-dir \"{output_dir}\" \\\n",
         "    --accelerator 'gpu' \\\n",