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Lars
2021-06-09 16:11:00 +02:00
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commit 015f38913e
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exercises/Jupyter notebook CVML.ipynb
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@@ -2441,7 +2441,7 @@
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@@ -2451,7 +2451,7 @@
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@@ -2465,7 +2465,7 @@
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@@ -2476,7 +2476,7 @@
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@@ -2503,7 +2503,7 @@
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@@ -2513,7 +2513,7 @@
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@@ -2524,7 +2524,7 @@
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@@ -2535,7 +2535,7 @@
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@@ -2546,7 +2546,7 @@
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@@ -2573,7 +2573,7 @@
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@@ -2585,7 +2585,7 @@
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@@ -2594,119 +2594,119 @@
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"text": [
"Epoch 1/100\n",
"3/3 [==============================] - 1s 367ms/step - loss: 1369.4281 - accuracy: 0.2222 - val_loss: 338.9728 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 370ms/step - loss: 631.9047 - accuracy: 0.2857 - val_loss: 25.2832 - val_accuracy: 0.5000\n",
"Epoch 2/100\n",
"3/3 [==============================] - 1s 300ms/step - loss: 86.5720 - accuracy: 0.7778 - val_loss: 67.7473 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 313ms/step - loss: 6.2664 - accuracy: 0.7778 - val_loss: 7.8777 - val_accuracy: 0.5000\n",
"Epoch 3/100\n",
"3/3 [==============================] - 1s 315ms/step - loss: 37.1450 - accuracy: 0.5714 - val_loss: 2.6404 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 318ms/step - loss: 5.2766 - accuracy: 0.5556 - val_loss: 0.7369 - val_accuracy: 0.6667\n",
"Epoch 4/100\n",
"3/3 [==============================] - 1s 299ms/step - loss: 0.9144 - accuracy: 0.7778 - val_loss: 0.8965 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 413ms/step - loss: 0.4368 - accuracy: 0.8889 - val_loss: 1.0521 - val_accuracy: 0.5000\n",
"Epoch 5/100\n",
"3/3 [==============================] - 1s 313ms/step - loss: 2.7767 - accuracy: 0.5556 - val_loss: 10.4820 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 414ms/step - loss: 1.1013 - accuracy: 0.6667 - val_loss: 0.5382 - val_accuracy: 0.6000\n",
"Epoch 6/100\n",
"3/3 [==============================] - 1s 305ms/step - loss: 25.6959 - accuracy: 0.2857 - val_loss: 3.7780 - val_accuracy: 0.5667\n",
"3/3 [==============================] - 1s 398ms/step - loss: 0.1352 - accuracy: 1.0000 - val_loss: 0.5930 - val_accuracy: 0.7000\n",
"Epoch 7/100\n",
"3/3 [==============================] - 1s 297ms/step - loss: 14.7089 - accuracy: 0.3333 - val_loss: 18.5807 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 395ms/step - loss: 0.1718 - accuracy: 0.8889 - val_loss: 0.5389 - val_accuracy: 0.7000\n",
"Epoch 8/100\n",
"3/3 [==============================] - 1s 409ms/step - loss: 3.6453 - accuracy: 0.8571 - val_loss: 0.7631 - val_accuracy: 0.6667\n",
"3/3 [==============================] - 1s 322ms/step - loss: 0.7288 - accuracy: 0.5714 - val_loss: 4.2130 - val_accuracy: 0.5000\n",
"Epoch 9/100\n",
"3/3 [==============================] - 1s 300ms/step - loss: 0.3044 - accuracy: 0.7778 - val_loss: 0.3835 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 303ms/step - loss: 1.0668 - accuracy: 0.6667 - val_loss: 0.4827 - val_accuracy: 0.8000\n",
"Epoch 10/100\n",
"3/3 [==============================] - 1s 283ms/step - loss: 0.2352 - accuracy: 0.8571 - val_loss: 0.3909 - val_accuracy: 0.8667\n",
"3/3 [==============================] - 1s 342ms/step - loss: 3.9666 - accuracy: 0.5556 - val_loss: 1.4615 - val_accuracy: 0.7333\n",
"Epoch 11/100\n",
"3/3 [==============================] - 1s 325ms/step - loss: 0.3825 - accuracy: 0.7778 - val_loss: 4.3373 - val_accuracy: 0.5333\n",
"3/3 [==============================] - 1s 303ms/step - loss: 2.2754 - accuracy: 0.6667 - val_loss: 12.2518 - val_accuracy: 0.5000\n",
"Epoch 12/100\n",
"3/3 [==============================] - 1s 324ms/step - loss: 2.1057 - accuracy: 0.4444 - val_loss: 8.2827 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 327ms/step - loss: 2.3443 - accuracy: 0.7778 - val_loss: 2.7297 - val_accuracy: 0.7333\n",
"Epoch 13/100\n",
"3/3 [==============================] - 1s 295ms/step - loss: 4.1824 - accuracy: 0.5556 - val_loss: 6.4766 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 297ms/step - loss: 2.6555 - accuracy: 0.7143 - val_loss: 0.7721 - val_accuracy: 0.7667\n",
"Epoch 14/100\n",
"3/3 [==============================] - 1s 324ms/step - loss: 3.0275 - accuracy: 0.5556 - val_loss: 0.4090 - val_accuracy: 0.8667\n",
"3/3 [==============================] - 1s 428ms/step - loss: 0.8492 - accuracy: 0.6667 - val_loss: 1.5201 - val_accuracy: 0.7333\n",
"Epoch 15/100\n",
"3/3 [==============================] - 1s 332ms/step - loss: 0.1266 - accuracy: 1.0000 - val_loss: 0.5297 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 428ms/step - loss: 13.1264 - accuracy: 0.5556 - val_loss: 2.7429 - val_accuracy: 0.5000\n",
"Epoch 16/100\n",
"3/3 [==============================] - 1s 365ms/step - loss: 0.1222 - accuracy: 1.0000 - val_loss: 0.4829 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 378ms/step - loss: 4.3159 - accuracy: 0.4286 - val_loss: 0.5180 - val_accuracy: 0.7333\n",
"Epoch 17/100\n",
"3/3 [==============================] - 1s 286ms/step - loss: 3.0182 - accuracy: 0.7143 - val_loss: 25.7416 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 423ms/step - loss: 1.6509 - accuracy: 0.6667 - val_loss: 1.3948 - val_accuracy: 0.5667\n",
"Epoch 18/100\n",
"3/3 [==============================] - 1s 304ms/step - loss: 4.8687 - accuracy: 0.8889 - val_loss: 0.8640 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 322ms/step - loss: 0.7452 - accuracy: 0.8889 - val_loss: 0.4667 - val_accuracy: 0.8333\n",
"Epoch 19/100\n",
"3/3 [==============================] - 1s 321ms/step - loss: 1.2353 - accuracy: 0.7778 - val_loss: 1.0395 - val_accuracy: 0.6667\n",
"3/3 [==============================] - 1s 325ms/step - loss: 0.2158 - accuracy: 1.0000 - val_loss: 0.4812 - val_accuracy: 0.7667\n",
"Epoch 20/100\n",
"3/3 [==============================] - 1s 303ms/step - loss: 0.0286 - accuracy: 1.0000 - val_loss: 2.6145 - val_accuracy: 0.6333\n",
"3/3 [==============================] - 1s 388ms/step - loss: 0.2269 - accuracy: 0.8889 - val_loss: 0.4995 - val_accuracy: 0.7000\n",
"Epoch 21/100\n",
"3/3 [==============================] - 1s 289ms/step - loss: 1.3674 - accuracy: 0.6667 - val_loss: 0.4656 - val_accuracy: 0.7000\n",
"3/3 [==============================] - 1s 358ms/step - loss: 0.1684 - accuracy: 1.0000 - val_loss: 1.4857 - val_accuracy: 0.6000\n",
"Epoch 22/100\n",
"3/3 [==============================] - 1s 296ms/step - loss: 0.4592 - accuracy: 0.6667 - val_loss: 0.7198 - val_accuracy: 0.7000\n",
"3/3 [==============================] - 1s 383ms/step - loss: 0.4235 - accuracy: 0.7778 - val_loss: 0.4008 - val_accuracy: 0.8000\n",
"Epoch 23/100\n",
"3/3 [==============================] - 1s 317ms/step - loss: 0.1039 - accuracy: 1.0000 - val_loss: 0.6429 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 377ms/step - loss: 0.0630 - accuracy: 1.0000 - val_loss: 0.4164 - val_accuracy: 0.7667\n",
"Epoch 24/100\n",
"3/3 [==============================] - 1s 310ms/step - loss: 0.0445 - accuracy: 1.0000 - val_loss: 0.7312 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 363ms/step - loss: 0.3585 - accuracy: 0.8889 - val_loss: 0.8163 - val_accuracy: 0.7333\n",
"Epoch 25/100\n",
"3/3 [==============================] - 1s 367ms/step - loss: 3.0544 - accuracy: 0.6667 - val_loss: 0.8471 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 340ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 1.0544 - val_accuracy: 0.7000\n",
"Epoch 26/100\n",
"3/3 [==============================] - 1s 302ms/step - loss: 38.3388 - accuracy: 0.5556 - val_loss: 0.6707 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 336ms/step - loss: 0.1005 - accuracy: 0.8889 - val_loss: 0.6170 - val_accuracy: 0.8333\n",
"Epoch 27/100\n",
"3/3 [==============================] - 1s 323ms/step - loss: 29.2603 - accuracy: 0.4444 - val_loss: 2.3584 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 366ms/step - loss: 1.3599 - accuracy: 0.7778 - val_loss: 10.4229 - val_accuracy: 0.5000\n",
"Epoch 28/100\n",
"3/3 [==============================] - 1s 295ms/step - loss: 2.0242 - accuracy: 0.5556 - val_loss: 17.3064 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 323ms/step - loss: 7.0201 - accuracy: 0.4444 - val_loss: 10.5174 - val_accuracy: 0.5000\n",
"Epoch 29/100\n",
"3/3 [==============================] - 1s 307ms/step - loss: 3.6977 - accuracy: 0.8889 - val_loss: 0.3189 - val_accuracy: 0.9000\n",
"3/3 [==============================] - 1s 323ms/step - loss: 4.5109 - accuracy: 0.6667 - val_loss: 10.1909 - val_accuracy: 0.5000\n",
"Epoch 30/100\n",
"3/3 [==============================] - 1s 286ms/step - loss: 0.0380 - accuracy: 1.0000 - val_loss: 1.1260 - val_accuracy: 0.7000\n",
"3/3 [==============================] - 1s 368ms/step - loss: 2.6090 - accuracy: 0.7778 - val_loss: 0.3708 - val_accuracy: 0.8333\n",
"Epoch 31/100\n",
"3/3 [==============================] - 1s 387ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.1609 - val_accuracy: 0.7000\n",
"3/3 [==============================] - 1s 393ms/step - loss: 1.8314 - accuracy: 0.6667 - val_loss: 1.8235 - val_accuracy: 0.5667\n",
"Epoch 32/100\n",
"3/3 [==============================] - 1s 339ms/step - loss: 1.6543 - accuracy: 0.6667 - val_loss: 1.1693 - val_accuracy: 0.6333\n",
"3/3 [==============================] - 1s 310ms/step - loss: 0.2703 - accuracy: 0.8889 - val_loss: 0.6332 - val_accuracy: 0.7667\n",
"Epoch 33/100\n",
"3/3 [==============================] - 1s 295ms/step - loss: 0.4399 - accuracy: 0.7778 - val_loss: 1.2607 - val_accuracy: 0.6333\n",
"3/3 [==============================] - 1s 331ms/step - loss: 0.0285 - accuracy: 1.0000 - val_loss: 0.4926 - val_accuracy: 0.8000\n",
"Epoch 34/100\n",
"3/3 [==============================] - 1s 307ms/step - loss: 0.5807 - accuracy: 0.5556 - val_loss: 0.7143 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 306ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 0.7783 - val_accuracy: 0.7667\n",
"Epoch 35/100\n",
"3/3 [==============================] - 1s 345ms/step - loss: 0.1359 - accuracy: 0.8889 - val_loss: 6.6615 - val_accuracy: 0.5333\n",
"3/3 [==============================] - 1s 319ms/step - loss: 0.2824 - accuracy: 0.8571 - val_loss: 0.6383 - val_accuracy: 0.7000\n",
"Epoch 36/100\n",
"3/3 [==============================] - 1s 307ms/step - loss: 1.9848 - accuracy: 0.7778 - val_loss: 2.4730 - val_accuracy: 0.6667\n",
"3/3 [==============================] - 1s 386ms/step - loss: 0.0472 - accuracy: 1.0000 - val_loss: 0.6081 - val_accuracy: 0.7667\n",
"Epoch 37/100\n",
"3/3 [==============================] - 1s 304ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 1.3785 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 318ms/step - loss: 0.0328 - accuracy: 1.0000 - val_loss: 1.5909 - val_accuracy: 0.7333\n",
"Epoch 38/100\n",
"3/3 [==============================] - 1s 321ms/step - loss: 23.4378 - accuracy: 0.2222 - val_loss: 2.3482 - val_accuracy: 0.5333\n",
"3/3 [==============================] - 1s 339ms/step - loss: 0.4909 - accuracy: 0.8889 - val_loss: 0.4917 - val_accuracy: 0.7333\n",
"Epoch 39/100\n",
"3/3 [==============================] - 1s 397ms/step - loss: 1.7446 - accuracy: 0.6667 - val_loss: 3.5555 - val_accuracy: 0.5333\n",
"3/3 [==============================] - 1s 334ms/step - loss: 0.1339 - accuracy: 0.8889 - val_loss: 0.5201 - val_accuracy: 0.7667\n",
"Epoch 40/100\n",
"3/3 [==============================] - 1s 367ms/step - loss: 0.9586 - accuracy: 0.6667 - val_loss: 0.6670 - val_accuracy: 0.7000\n",
"3/3 [==============================] - 1s 330ms/step - loss: 0.2175 - accuracy: 0.8889 - val_loss: 4.0990 - val_accuracy: 0.5333\n",
"Epoch 41/100\n",
"3/3 [==============================] - 1s 286ms/step - loss: 0.5917 - accuracy: 0.5714 - val_loss: 2.0161 - val_accuracy: 0.5333\n",
"3/3 [==============================] - 1s 319ms/step - loss: 1.2361 - accuracy: 0.7778 - val_loss: 0.7778 - val_accuracy: 0.7667\n",
"Epoch 42/100\n",
"3/3 [==============================] - 1s 376ms/step - loss: 2.0168 - accuracy: 0.5556 - val_loss: 0.6411 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 300ms/step - loss: 0.1615 - accuracy: 0.8571 - val_loss: 10.9553 - val_accuracy: 0.5000\n",
"Epoch 43/100\n",
"3/3 [==============================] - 1s 295ms/step - loss: 1.0722 - accuracy: 0.5556 - val_loss: 0.5454 - val_accuracy: 0.6667\n",
"3/3 [==============================] - 1s 362ms/step - loss: 6.1308 - accuracy: 0.6667 - val_loss: 0.9029 - val_accuracy: 0.6000\n",
"Epoch 44/100\n",
"3/3 [==============================] - 1s 390ms/step - loss: 0.0442 - accuracy: 1.0000 - val_loss: 0.5824 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 363ms/step - loss: 0.1388 - accuracy: 0.8889 - val_loss: 0.5052 - val_accuracy: 0.8000\n",
"Epoch 45/100\n",
"3/3 [==============================] - 1s 311ms/step - loss: 9.0435 - accuracy: 0.6667 - val_loss: 0.7655 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 365ms/step - loss: 0.1895 - accuracy: 0.8889 - val_loss: 0.6759 - val_accuracy: 0.7000\n",
"Epoch 46/100\n",
"3/3 [==============================] - 1s 313ms/step - loss: 2.9779e-04 - accuracy: 1.0000 - val_loss: 0.9408 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 344ms/step - loss: 0.0418 - accuracy: 1.0000 - val_loss: 1.4219 - val_accuracy: 0.6667\n",
"Epoch 47/100\n",
"3/3 [==============================] - 1s 372ms/step - loss: 2.1282 - accuracy: 0.6667 - val_loss: 0.6426 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 379ms/step - loss: 0.0013 - accuracy: 1.0000 - val_loss: 2.8323 - val_accuracy: 0.5667\n",
"Epoch 48/100\n",
"3/3 [==============================] - 1s 324ms/step - loss: 0.0880 - accuracy: 1.0000 - val_loss: 5.0223 - val_accuracy: 0.5333\n",
"3/3 [==============================] - 1s 326ms/step - loss: 0.2265 - accuracy: 0.8889 - val_loss: 0.8237 - val_accuracy: 0.7667\n",
"Epoch 49/100\n",
"3/3 [==============================] - 1s 302ms/step - loss: 4.1637 - accuracy: 0.5556 - val_loss: 0.8247 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 369ms/step - loss: 5.4279e-04 - accuracy: 1.0000 - val_loss: 0.9069 - val_accuracy: 0.7667\n",
"Epoch 50/100\n",
"3/3 [==============================] - 1s 315ms/step - loss: 0.5698 - accuracy: 0.7778 - val_loss: 1.1764 - val_accuracy: 0.7000\n",
"3/3 [==============================] - 1s 443ms/step - loss: 9.4348e-04 - accuracy: 1.0000 - val_loss: 1.1811 - val_accuracy: 0.7667\n",
"Epoch 51/100\n",
"3/3 [==============================] - 1s 394ms/step - loss: 0.0318 - accuracy: 1.0000 - val_loss: 1.0798 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 334ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.5748 - val_accuracy: 0.7667\n",
"Epoch 52/100\n",
"3/3 [==============================] - 1s 301ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.0926 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 352ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.2691 - val_accuracy: 0.8000\n",
"Epoch 53/100\n",
"3/3 [==============================] - 1s 302ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 1.2287 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 327ms/step - loss: 2.3012e-04 - accuracy: 1.0000 - val_loss: 1.4067 - val_accuracy: 0.8000\n",
"Epoch 54/100\n",
"3/3 [==============================] - 1s 420ms/step - loss: 5.6540e-04 - accuracy: 1.0000 - val_loss: 1.2118 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 342ms/step - loss: 4.2465e-05 - accuracy: 1.0000 - val_loss: 1.3568 - val_accuracy: 0.8000\n",
"Epoch 55/100\n",
"3/3 [==============================] - 1s 321ms/step - loss: 2.9656e-04 - accuracy: 1.0000 - val_loss: 1.1280 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 326ms/step - loss: 2.3235e-05 - accuracy: 1.0000 - val_loss: 1.3414 - val_accuracy: 0.8000\n",
"Epoch 56/100\n",
"3/3 [==============================] - 1s 329ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.4730 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 402ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.2960 - val_accuracy: 0.8000\n",
"Epoch 57/100\n",
"3/3 [==============================] - 1s 325ms/step - loss: 7.4079e-04 - accuracy: 1.0000 - val_loss: 1.2876 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 316ms/step - loss: 1.9244e-05 - accuracy: 1.0000 - val_loss: 1.3116 - val_accuracy: 0.8000\n",
"Epoch 58/100\n"
]
},
@@ -2714,91 +2714,91 @@
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"text": [
"3/3 [==============================] - 1s 373ms/step - loss: 3.4847e-04 - accuracy: 1.0000 - val_loss: 1.3517 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 324ms/step - loss: 1.8088e-05 - accuracy: 1.0000 - val_loss: 1.3336 - val_accuracy: 0.8000\n",
"Epoch 59/100\n",
"3/3 [==============================] - 1s 318ms/step - loss: 4.5189e-04 - accuracy: 1.0000 - val_loss: 1.1280 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 319ms/step - loss: 3.6851e-05 - accuracy: 1.0000 - val_loss: 1.4207 - val_accuracy: 0.8000\n",
"Epoch 60/100\n",
"3/3 [==============================] - 1s 303ms/step - loss: 1.1957e-04 - accuracy: 1.0000 - val_loss: 1.2622 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 387ms/step - loss: 1.6570e-05 - accuracy: 1.0000 - val_loss: 1.4509 - val_accuracy: 0.8000\n",
"Epoch 61/100\n",
"3/3 [==============================] - 1s 295ms/step - loss: 7.9549e-05 - accuracy: 1.0000 - val_loss: 1.2555 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 358ms/step - loss: 4.3533e-04 - accuracy: 1.0000 - val_loss: 0.8771 - val_accuracy: 0.7667\n",
"Epoch 62/100\n",
"3/3 [==============================] - 1s 384ms/step - loss: 0.0629 - accuracy: 1.0000 - val_loss: 1.8866 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 368ms/step - loss: 3.0294e-05 - accuracy: 1.0000 - val_loss: 0.9190 - val_accuracy: 0.7667\n",
"Epoch 63/100\n",
"3/3 [==============================] - 1s 391ms/step - loss: 6.0368 - accuracy: 0.7778 - val_loss: 0.6219 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 394ms/step - loss: 7.9558e-06 - accuracy: 1.0000 - val_loss: 0.9367 - val_accuracy: 0.7667\n",
"Epoch 64/100\n",
"3/3 [==============================] - 1s 314ms/step - loss: 1.5387 - accuracy: 0.7778 - val_loss: 1.9052 - val_accuracy: 0.6000\n",
"3/3 [==============================] - 1s 381ms/step - loss: 8.8777e-06 - accuracy: 1.0000 - val_loss: 0.9605 - val_accuracy: 0.7667\n",
"Epoch 65/100\n",
"3/3 [==============================] - 1s 299ms/step - loss: 0.0539 - accuracy: 1.0000 - val_loss: 1.0248 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 325ms/step - loss: 9.7372e-06 - accuracy: 1.0000 - val_loss: 0.9864 - val_accuracy: 0.8000\n",
"Epoch 66/100\n",
"3/3 [==============================] - 1s 374ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.2154 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 338ms/step - loss: 8.2406e-06 - accuracy: 1.0000 - val_loss: 1.0122 - val_accuracy: 0.8000\n",
"Epoch 67/100\n",
"3/3 [==============================] - 1s 308ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8622 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 322ms/step - loss: 3.0732e-05 - accuracy: 1.0000 - val_loss: 1.2107 - val_accuracy: 0.8000\n",
"Epoch 68/100\n",
"3/3 [==============================] - 1s 392ms/step - loss: 2.3555e-04 - accuracy: 1.0000 - val_loss: 2.1361 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 330ms/step - loss: 1.5750e-05 - accuracy: 1.0000 - val_loss: 1.3865 - val_accuracy: 0.8000\n",
"Epoch 69/100\n",
"3/3 [==============================] - 1s 322ms/step - loss: 0.0388 - accuracy: 1.0000 - val_loss: 6.0318 - val_accuracy: 0.5667\n",
"3/3 [==============================] - 1s 307ms/step - loss: 6.6675e-06 - accuracy: 1.0000 - val_loss: 1.1851 - val_accuracy: 0.8000\n",
"Epoch 70/100\n",
"3/3 [==============================] - 1s 315ms/step - loss: 0.1016 - accuracy: 1.0000 - val_loss: 12.2368 - val_accuracy: 0.5667\n",
"3/3 [==============================] - 1s 340ms/step - loss: 1.6783e-06 - accuracy: 1.0000 - val_loss: 1.1979 - val_accuracy: 0.8000\n",
"Epoch 71/100\n",
"3/3 [==============================] - 1s 307ms/step - loss: 4.4367 - accuracy: 0.5556 - val_loss: 3.8923 - val_accuracy: 0.6333\n",
"3/3 [==============================] - 1s 334ms/step - loss: 2.1998e-06 - accuracy: 1.0000 - val_loss: 1.2349 - val_accuracy: 0.8000\n",
"Epoch 72/100\n",
"3/3 [==============================] - 1s 299ms/step - loss: 0.6864 - accuracy: 0.8889 - val_loss: 1.1572 - val_accuracy: 0.8333\n",
"3/3 [==============================] - 1s 432ms/step - loss: 1.9722e-06 - accuracy: 1.0000 - val_loss: 1.2664 - val_accuracy: 0.8000\n",
"Epoch 73/100\n",
"3/3 [==============================] - 1s 365ms/step - loss: 2.4695e-04 - accuracy: 1.0000 - val_loss: 1.0523 - val_accuracy: 0.8667\n",
"3/3 [==============================] - 1s 339ms/step - loss: 2.4348e-06 - accuracy: 1.0000 - val_loss: 1.2911 - val_accuracy: 0.8000\n",
"Epoch 74/100\n",
"3/3 [==============================] - 1s 303ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 6.4837 - val_accuracy: 0.5667\n",
"3/3 [==============================] - 1s 345ms/step - loss: 3.5031e-06 - accuracy: 1.0000 - val_loss: 1.3663 - val_accuracy: 0.8000\n",
"Epoch 75/100\n",
"3/3 [==============================] - 1s 315ms/step - loss: 11.3018 - accuracy: 0.4444 - val_loss: 4.6191 - val_accuracy: 0.5333\n",
"3/3 [==============================] - 1s 395ms/step - loss: 5.0517e-07 - accuracy: 1.0000 - val_loss: 1.3714 - val_accuracy: 0.8000\n",
"Epoch 76/100\n",
"3/3 [==============================] - 1s 312ms/step - loss: 0.3357 - accuracy: 0.8889 - val_loss: 1.7216 - val_accuracy: 0.8667\n",
"3/3 [==============================] - 1s 330ms/step - loss: 1.0532e-06 - accuracy: 1.0000 - val_loss: 1.3611 - val_accuracy: 0.8000\n",
"Epoch 77/100\n",
"3/3 [==============================] - 1s 329ms/step - loss: 0.4952 - accuracy: 0.8889 - val_loss: 1.2722 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 325ms/step - loss: 1.2722e-06 - accuracy: 1.0000 - val_loss: 1.4170 - val_accuracy: 0.8000\n",
"Epoch 78/100\n",
"3/3 [==============================] - 1s 332ms/step - loss: 0.3751 - accuracy: 0.8889 - val_loss: 1.6066 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 341ms/step - loss: 1.4741e-06 - accuracy: 1.0000 - val_loss: 1.4845 - val_accuracy: 0.8000\n",
"Epoch 79/100\n",
"3/3 [==============================] - 1s 299ms/step - loss: 0.1591 - accuracy: 0.8889 - val_loss: 1.3587 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 416ms/step - loss: 8.8492e-07 - accuracy: 1.0000 - val_loss: 1.5334 - val_accuracy: 0.8000\n",
"Epoch 80/100\n",
"3/3 [==============================] - 1s 296ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.4834 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 358ms/step - loss: 9.4000e-07 - accuracy: 1.0000 - val_loss: 1.5491 - val_accuracy: 0.8000\n",
"Epoch 81/100\n",
"3/3 [==============================] - 1s 322ms/step - loss: 0.0268 - accuracy: 1.0000 - val_loss: 1.5582 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 342ms/step - loss: 1.7681e-07 - accuracy: 1.0000 - val_loss: 1.5567 - val_accuracy: 0.8000\n",
"Epoch 82/100\n",
"3/3 [==============================] - 1s 346ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 2.9275 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 333ms/step - loss: 1.6814e-06 - accuracy: 1.0000 - val_loss: 1.7238 - val_accuracy: 0.8000\n",
"Epoch 83/100\n",
"3/3 [==============================] - 1s 309ms/step - loss: 2.1840e-06 - accuracy: 1.0000 - val_loss: 2.8794 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 321ms/step - loss: 2.4142e-07 - accuracy: 1.0000 - val_loss: 1.6751 - val_accuracy: 0.8000\n",
"Epoch 84/100\n",
"3/3 [==============================] - 1s 313ms/step - loss: 4.1264e-06 - accuracy: 1.0000 - val_loss: 2.7301 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 358ms/step - loss: 2.4599e-07 - accuracy: 1.0000 - val_loss: 1.6318 - val_accuracy: 0.8000\n",
"Epoch 85/100\n",
"3/3 [==============================] - 1s 287ms/step - loss: 4.0914e-08 - accuracy: 1.0000 - val_loss: 2.7331 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 393ms/step - loss: 1.2130e-07 - accuracy: 1.0000 - val_loss: 1.6175 - val_accuracy: 0.8000\n",
"Epoch 86/100\n",
"3/3 [==============================] - 1s 304ms/step - loss: 5.2867e-07 - accuracy: 1.0000 - val_loss: 2.7186 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 322ms/step - loss: 4.8431e-07 - accuracy: 1.0000 - val_loss: 1.6252 - val_accuracy: 0.8000\n",
"Epoch 87/100\n",
"3/3 [==============================] - 1s 317ms/step - loss: 1.9100e-06 - accuracy: 1.0000 - val_loss: 2.6256 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 344ms/step - loss: 3.1227e-07 - accuracy: 1.0000 - val_loss: 1.6863 - val_accuracy: 0.8000\n",
"Epoch 88/100\n",
"3/3 [==============================] - 1s 380ms/step - loss: 4.3839e-07 - accuracy: 1.0000 - val_loss: 2.6523 - val_accuracy: 0.7333\n",
"3/3 [==============================] - 1s 324ms/step - loss: 7.5780e-07 - accuracy: 1.0000 - val_loss: 1.2082 - val_accuracy: 0.8000\n",
"Epoch 89/100\n",
"3/3 [==============================] - 1s 307ms/step - loss: 0.2357 - accuracy: 0.8571 - val_loss: 2.7167 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 332ms/step - loss: 2.0578e-07 - accuracy: 1.0000 - val_loss: 1.2582 - val_accuracy: 0.8000\n",
"Epoch 90/100\n",
"3/3 [==============================] - 1s 407ms/step - loss: 3.4208e-05 - accuracy: 1.0000 - val_loss: 3.0456 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 318ms/step - loss: 4.5273e-07 - accuracy: 1.0000 - val_loss: 1.3558 - val_accuracy: 0.8000\n",
"Epoch 91/100\n",
"3/3 [==============================] - 1s 295ms/step - loss: 12.6518 - accuracy: 0.7778 - val_loss: 4.0452 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 310ms/step - loss: 3.5196e-08 - accuracy: 1.0000 - val_loss: 1.3530 - val_accuracy: 0.8000\n",
"Epoch 92/100\n",
"3/3 [==============================] - 1s 293ms/step - loss: 2.5877 - accuracy: 0.7778 - val_loss: 3.4705 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 394ms/step - loss: 1.3083e-06 - accuracy: 1.0000 - val_loss: 2.1760 - val_accuracy: 0.8000\n",
"Epoch 93/100\n",
"3/3 [==============================] - 1s 307ms/step - loss: 0.6331 - accuracy: 0.8889 - val_loss: 8.0785 - val_accuracy: 0.6667\n",
"3/3 [==============================] - 1s 356ms/step - loss: 4.7386e-07 - accuracy: 1.0000 - val_loss: 1.8897 - val_accuracy: 0.8000\n",
"Epoch 94/100\n",
"3/3 [==============================] - 1s 339ms/step - loss: 1.1341 - accuracy: 0.8889 - val_loss: 34.2737 - val_accuracy: 0.5000\n",
"3/3 [==============================] - 1s 408ms/step - loss: 1.0568e-07 - accuracy: 1.0000 - val_loss: 1.8855 - val_accuracy: 0.8000\n",
"Epoch 95/100\n",
"3/3 [==============================] - 1s 308ms/step - loss: 4.7906 - accuracy: 0.7778 - val_loss: 1.5598 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 319ms/step - loss: 8.8544e-08 - accuracy: 1.0000 - val_loss: 1.9152 - val_accuracy: 0.8000\n",
"Epoch 96/100\n",
"3/3 [==============================] - 1s 323ms/step - loss: 6.6407e-04 - accuracy: 1.0000 - val_loss: 1.3289 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 420ms/step - loss: 3.6541e-08 - accuracy: 1.0000 - val_loss: 1.9103 - val_accuracy: 0.8000\n",
"Epoch 97/100\n",
"3/3 [==============================] - 1s 383ms/step - loss: 8.3085e-05 - accuracy: 1.0000 - val_loss: 1.4292 - val_accuracy: 0.8000\n",
"3/3 [==============================] - 1s 331ms/step - loss: 5.0840e-08 - accuracy: 1.0000 - val_loss: 1.9280 - val_accuracy: 0.8000\n",
"Epoch 98/100\n",
"3/3 [==============================] - 1s 331ms/step - loss: 5.3813e-04 - accuracy: 1.0000 - val_loss: 1.7836 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 309ms/step - loss: 6.9709e-08 - accuracy: 1.0000 - val_loss: 1.9674 - val_accuracy: 0.8000\n",
"Epoch 99/100\n",
"3/3 [==============================] - 1s 331ms/step - loss: 1.0353e-04 - accuracy: 1.0000 - val_loss: 1.7338 - val_accuracy: 0.7667\n",
"3/3 [==============================] - 1s 323ms/step - loss: 3.7592e-08 - accuracy: 1.0000 - val_loss: 1.9508 - val_accuracy: 0.8000\n",
"Epoch 100/100\n",
"3/3 [==============================] - 1s 302ms/step - loss: 4.9188e-05 - accuracy: 1.0000 - val_loss: 1.7997 - val_accuracy: 0.7667\n"
"3/3 [==============================] - 1s 322ms/step - loss: 4.3305e-08 - accuracy: 1.0000 - val_loss: 2.0279 - val_accuracy: 0.8000\n"
]
}
],
@@ -2811,7 +2811,7 @@
},
{
"cell_type": "code",
"execution_count": 43,
"execution_count": 10,
"id": "a2afe8b7",
"metadata": {
"scrolled": false
@@ -3061,7 +3061,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"sem\n"
"lars\n"
]
},
{