training guide up

Author: blondered

examples/tutorials/transformers_advanced_training_guide.ipynb

@@ -1550,6 +1550,16 @@
     "pd.concat([metrics_df.head(5), metrics_df.tail(5)])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Don't be surprised by the fact that validation loss is less then train loss in the plot below. \n",
+    "- First, this is data-specific, you may not see this in other datasets. \n",
+    "- Second, validation loss is calculated after the full training epoch while train loss is computed for each batch during training when model still hasn't seen other batches and hasn't updated weights.\n",
+    "- Validation loss is calculated only in the last item in validation users history. While train loss for SASRec is calculated for each item in user histor except the first one and the validation one."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 31,
@@ -1755,7 +1765,7 @@
    "source": [
     "### Configs for transformer models\n",
     "\n",
-    "`from_config`, `get_config` and `get_params` methods are fully available for transformers just like for any other models."
+    "`from_config`, `from_params`, `get_config` and `get_params` methods are fully available for transformers just like for any other models."
    ]
   },
   {
@@ -1928,7 +1938,7 @@
    "source": [
     "### Multi-gpu training\n",
     "RecTools models use PyTorch Lightning to handle multi-gpu training.\n",
-    "Please refer to lighting documentation for details. We do not cover it in this guide."
+    "Please refer to Lightning documentation for details. We do not cover it in this guide."
    ]
   }
  ],