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app.py

@@ -70,8 +70,10 @@ demo = gr.Interface(
     inputs="textbox",
     outputs="label",
     examples=[
-        "炊き立て・・・・ってコト！？",
-        "晴れた空に種を蒔こう",
+        "守りたいんだ",
+        "どうしてどうしてどうして",
+        "そこから見ていてね",
+        "ヤンパパン"
     ],
 )
 

notebooks/loss.ipynb

@@ -0,0 +1,85 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "交差検証における損失の目安を知る"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 100％正しい場合\n",
+    "torch.nn.functional.cross_entropy(\n",
+    "    torch.Tensor([[0,1]]),\n",
+    "    torch.Tensor([[0,1]])\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor(0.3133)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 100％誤っている場合\n",
+    "torch.nn.functional.cross_entropy(\n",
+    "    torch.Tensor([[0,1]]),\n",
+    "    torch.Tensor([[1,0]])\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "chiikawa-yonezu",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

notebooks/preprocessing.ipynb

@@ -95,7 +95,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "csv_path = '../data/data.csv'\n",
+    "csv_path = '../data/datawithrakko.csv'\n",
     "preprocessed_csv_path = csv_path.replace('.csv', '_preprocessed.csv')\n",
     "preprocess(csv_path, preprocessed_csv_path)\n",
     "split(preprocessed_csv_path)"