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{
"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
}
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