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fix nn

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kubapok 2021-05-10 10:55:55 +02:00
parent 3d70d8a7ec
commit 54ab26b5f9
2 changed files with 60 additions and 58 deletions
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1
cw/08_regresja_logistyczna.ipynb
View File

@ -777,6 +777,7 @@
"\n",
" def forward(self, x):\n",
" x = self.fc1(x)\n",
" x = torch.relu(x)\n",
" x = self.fc2(x)\n",
" x = torch.sigmoid(x)\n",
" return x"

117
cw/08_regresja_logistyczna_ODPOWIEDZI.ipynb
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@ -402,11 +402,11 @@
{
"data": {
"text/plain": [
"tensor([[0.4978],\n",
" [0.5009],\n",
" [0.4998],\n",
" [0.4990],\n",
" [0.5018]], grad_fn=<SigmoidBackward>)"
"tensor([[0.4989],\n",
" [0.4985],\n",
" [0.4970],\n",
" [0.4968],\n",
" [0.5007]], grad_fn=<SigmoidBackward>)"
]
},
"execution_count": 20,
@ -449,10 +449,10 @@
"data": {
"text/plain": [
"[Parameter containing:\n",
" tensor([[-0.0059, 0.0035, 0.0021, ..., -0.0042, -0.0057, -0.0049]],\n",
" tensor([[ 0.0006, -0.0076, 0.0002, ..., 0.0051, 0.0034, -0.0004]],\n",
" requires_grad=True),\n",
" Parameter containing:\n",
" tensor([-0.0023], requires_grad=True)]"
" tensor([-0.0099], requires_grad=True)]"
]
},
"execution_count": 22,
@ -556,10 +556,10 @@
{
"data": {
"text/plain": [
"tensor([[0.5667],\n",
" [0.5802],\n",
" [0.5757],\n",
" [0.5670]], grad_fn=<SigmoidBackward>)"
"tensor([[0.5657],\n",
" [0.5827],\n",
" [0.5727],\n",
" [0.5672]], grad_fn=<SigmoidBackward>)"
]
},
"execution_count": 28,
@ -604,7 +604,7 @@
{
"data": {
"text/plain": [
"452"
"453"
]
},
"execution_count": 30,
@ -645,7 +645,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"accuracy: 0.5587144622991347\n"
"accuracy: 0.5599505562422744\n"
]
}
],
@ -664,7 +664,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"BCE loss: 0.6745463597170355\n"
"BCE loss: 0.6745760098965412\n"
]
}
],
@ -717,7 +717,7 @@
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@ -737,7 +737,7 @@
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@ -757,7 +757,7 @@
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@ -785,10 +785,10 @@
"data": {
"text/plain": [
"[Parameter containing:\n",
" tensor([[ 0.0314, -0.0375, 0.0131, ..., -0.0057, -0.0008, -0.0089]],\n",
" tensor([[ 0.0379, -0.0485, 0.0113, ..., 0.0035, 0.0083, -0.0044]],\n",
" requires_grad=True),\n",
" Parameter containing:\n",
" tensor([0.0563], requires_grad=True)]"
" tensor([0.0556], requires_grad=True)]"
]
},
"execution_count": 38,
@ -808,7 +808,7 @@
{
"data": {
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"tensor([ 0.0314, -0.0375, 0.0131, ..., -0.0057, -0.0008, -0.0089],\n",
"tensor([ 0.0379, -0.0485, 0.0113, ..., 0.0035, 0.0083, -0.0044],\n",
" grad_fn=<SelectBackward>)"
]
},
@ -830,11 +830,11 @@
"data": {
"text/plain": [
"torch.return_types.topk(\n",
"values=tensor([0.3753, 0.2305, 0.2007, 0.2006, 0.1993, 0.1952, 0.1930, 0.1898, 0.1831,\n",
" 0.1731, 0.1649, 0.1647, 0.1543, 0.1320, 0.1314, 0.1303, 0.1296, 0.1261,\n",
" 0.1245, 0.1243], grad_fn=<TopkBackward>),\n",
"indices=tensor([8942, 6336, 1852, 9056, 1865, 4039, 7820, 5002, 8208, 1857, 9709, 803,\n",
" 1046, 130, 4306, 6481, 4370, 4259, 4285, 1855]))"
"values=tensor([0.3804, 0.2315, 0.2033, 0.2026, 0.2014, 0.1993, 0.1942, 0.1890, 0.1868,\n",
" 0.1818, 0.1727, 0.1542, 0.1474, 0.1458, 0.1360, 0.1359, 0.1260, 0.1204,\n",
" 0.1184, 0.1174], grad_fn=<TopkBackward>),\n",
"indices=tensor([8942, 6336, 1865, 1852, 8208, 9056, 7820, 4039, 5002, 1857, 9709, 803,\n",
" 130, 1046, 4370, 4259, 4306, 1855, 4285, 6481]))"
]
},
"execution_count": 40,
@ -857,24 +857,24 @@
"text": [
"the\n",
"of\n",
"christ\n",
"to\n",
"church\n",
"god\n",
"rutgers\n",
"jesus\n",
"christ\n",
"sin\n",
"to\n",
"rutgers\n",
"god\n",
"jesus\n",
"christians\n",
"we\n",
"and\n",
"athos\n",
"1993\n",
"hell\n",
"our\n",
"athos\n",
"his\n",
"he\n",
"hell\n",
"christian\n",
"heaven\n",
"christian\n"
"our\n"
]
}
],
@ -892,11 +892,11 @@
"data": {
"text/plain": [
"torch.return_types.topk(\n",
"values=tensor([-0.3478, -0.2578, -0.2455, -0.2347, -0.2330, -0.2265, -0.2205, -0.2050,\n",
" -0.2044, -0.1979, -0.1876, -0.1790, -0.1747, -0.1745, -0.1734, -0.1647,\n",
" -0.1639, -0.1617, -0.1601, -0.1592], grad_fn=<TopkBackward>),\n",
"indices=tensor([5119, 8096, 5420, 4436, 6194, 1627, 6901, 5946, 9970, 3116, 1036, 9906,\n",
" 5654, 8329, 7869, 1039, 1991, 4926, 5035, 4925]))"
"values=tensor([-0.3464, -0.2578, -0.2372, -0.2307, -0.2300, -0.2259, -0.2227, -0.2107,\n",
" -0.2054, -0.1949, -0.1919, -0.1767, -0.1767, -0.1749, -0.1747, -0.1739,\n",
" -0.1715, -0.1633, -0.1567, -0.1562], grad_fn=<TopkBackward>),\n",
"indices=tensor([5119, 8096, 5420, 1627, 6194, 6901, 4436, 9970, 5946, 3116, 1036, 9906,\n",
" 7869, 5654, 1991, 8329, 4925, 4926, 6373, 1039]))"
]
},
"execution_count": 42,
@ -922,23 +922,23 @@
"keith\n",
"sgi\n",
"livesey\n",
"host\n",
"nntp\n",
"caltech\n",
"nntp\n",
"posting\n",
"morality\n",
"host\n",
"you\n",
"morality\n",
"edu\n",
"atheism\n",
"wpd\n",
"mathew\n",
"solntze\n",
"sandvik\n",
"atheists\n",
"mathew\n",
"com\n",
"solntze\n",
"islam\n",
"islamic\n",
"jon\n",
"islam\n"
"okcforum\n",
"atheists\n"
]
}
],
@ -969,6 +969,7 @@
"\n",
" def forward(self, x):\n",
" x = self.fc1(x)\n",
" x = torch.relu(x)\n",
" x = self.fc2(x)\n",
" x = torch.sigmoid(x)\n",
" return x"
@ -1029,7 +1030,7 @@
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@ -1065,7 +1066,7 @@
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@ -1083,7 +1084,7 @@
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@ -1092,7 +1093,7 @@
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@ -1119,7 +1120,7 @@
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@ -1137,7 +1138,7 @@
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@ -1146,7 +1147,7 @@
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@ -1189,7 +1190,7 @@
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