Merge pull request #44 from georgian-io/akash/bugfix

Fix(.): Resolve issue in evaluation.
georgian-io · May 30, 2023 · bd5bf14 · bd5bf14
2 parents c0dd884 + 769f1f1
commit bd5bf14
Showing 1 changed file with 23 additions and 17 deletions.
diff --git a/notebooks/text_w_tabular_classification.ipynb b/notebooks/text_w_tabular_classification.ipynb
@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -14,6 +15,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -24,6 +26,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -34,6 +37,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -118,6 +122,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -217,6 +222,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -262,6 +268,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -291,9 +298,9 @@
      "output_type": "stream",
      "text": [
       "Downloading womens-ecommerce-clothing-reviews.zip to /content\n",
-      "\r",
+      "\r\n",
       "  0% 0.00/2.79M [00:00<?, ?B/s]\n",
-      "\r",
+      "\r\n",
       "100% 2.79M/2.79M [00:00<00:00, 88.6MB/s]\n",
       "Archive:  womens-ecommerce-clothing-reviews.zip\n",
       "  inflating: Womens Clothing E-Commerce Reviews.csv  \n",
@@ -309,6 +316,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -464,6 +472,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -717,6 +726,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -758,6 +768,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -880,6 +891,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -941,6 +953,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -1075,6 +1088,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -1286,6 +1300,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -1317,8 +1332,9 @@
     ")\n",
     "\n",
     "def calc_classification_metrics(p: EvalPrediction):\n",
-    "  pred_labels = np.argmax(p.predictions, axis=1)\n",
-    "  pred_scores = softmax(p.predictions, axis=1)[:, 1]\n",
+    "  predictions = p.predictions[0]\n",
+    "  pred_labels = np.argmax(predictions, axis=1)\n",
+    "  pred_scores = softmax(predictions, axis=1)[:, 1]\n",
     "  labels = p.label_ids\n",
     "  if len(np.unique(labels)) == 2:  # binary classification\n",
     "      roc_auc_pred_score = roc_auc_score(labels, pred_scores)\n",
@@ -1370,6 +1386,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -1572,6 +1589,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
@@ -1780,19 +1798,7 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "\n",
-       "        (async () => {\n",
-       "            const url = await google.colab.kernel.proxyPort(6006, {\"cache\": true});\n",
-       "            const iframe = document.createElement('iframe');\n",
-       "            iframe.src = url;\n",
-       "            iframe.setAttribute('width', '100%');\n",
-       "            iframe.setAttribute('height', '800');\n",
-       "            iframe.setAttribute('frameborder', 0);\n",
-       "            document.body.appendChild(iframe);\n",
-       "        })();\n",
-       "    "
-      ],
+      "application/javascript": "\n        (async () => {\n            const url = await google.colab.kernel.proxyPort(6006, {\"cache\": true});\n            const iframe = document.createElement('iframe');\n            iframe.src = url;\n            iframe.setAttribute('width', '100%');\n            iframe.setAttribute('height', '800');\n            iframe.setAttribute('frameborder', 0);\n            document.body.appendChild(iframe);\n        })();\n    ",
       "text/plain": [
        "<IPython.core.display.Javascript object>"
       ]