Update documentation

classification/classifier/hyp-metrics.ipynb

@@ -34,6 +34,14 @@
     "np.random.seed(42)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "4d29e56f-ee81-4f43-96ff-99bb22c52f6a",
+   "metadata": {},
+   "source": [
+    "# Download Metrics from WandB"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -70,6 +78,16 @@
     "runs_df.to_csv(\"hyp-metrics.csv\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "821aeb7d-784b-4e38-b4f8-c49245ee25ce",
+   "metadata": {},
+   "source": [
+    "# Transform Metrics\n",
+    "\n",
+    "The column `summary` contains most of the metrics we are interested in (`test/precision`,…) but all of the metrics are in a dictionary in this column."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -970,7 +988,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.15"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,

classification/classifier/hyp.ipynb

@@ -1,5 +1,15 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5eca6897-e43c-4358-9281-ab6b1ece871a",
+   "metadata": {},
+   "source": [
+    "# Local Hyperparameter Optimization\n",
+    "\n",
+    "This notebook is similar to the `classifier_hyp` notebook, but it runs the hyperparameter optimization locally instead of on Google Colab. The definitive version is the Google Colab one because we run many more iterations and parameter combinations there due to GPU availability."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -4636,7 +4646,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.15"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,