From e5da149da94800ff00da235ff7ff8ffb760cd3fb Mon Sep 17 00:00:00 2001 From: Kai Koellemann Date: Sat, 10 Jun 2023 17:06:32 +0200 Subject: [PATCH] =?UTF-8?q?Aufgabe=203=20gel=C3=B6st,=20getestet,=20funkti?= =?UTF-8?q?oniert=2020/20=20Mal?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Aufgabe 4/aufgabe04.ipynb | 1071 ++++++++++++++++++++++++++++++++++++- 1 file changed, 1062 insertions(+), 9 deletions(-) diff --git a/Aufgabe 4/aufgabe04.ipynb b/Aufgabe 4/aufgabe04.ipynb index f2b3956..e7af0a6 100644 --- a/Aufgabe 4/aufgabe04.ipynb +++ b/Aufgabe 4/aufgabe04.ipynb @@ -185,21 +185,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Correct classifications before training: 0.474\n" + "Correct classifications before training: 0.775\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 80/80 [00:00<00:00, 3998.96it/s]" + "100%|██████████| 80/80 [00:00<00:00, 10012.66it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Correct classifications after training: 1.0\n" + "Correct classifications after training: 0.775\n" ] }, { @@ -236,14 +236,12 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -269,6 +267,1061 @@ " ax.imshow(data, cmap=\"hot\", interpolation=\"nearest\", extent=dim)\n", "visualize(nn)\n" ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:absl:At this time, the v2.11+ optimizer `tf.keras.optimizers.Adam` runs slowly on M1/M2 Macs, please use the legacy Keras optimizer instead, located at `tf.keras.optimizers.legacy.Adam`.\n", + "WARNING:absl:There is a known slowdown when using v2.11+ Keras optimizers on M1/M2 Macs. Falling back to the legacy Keras optimizer, i.e., `tf.keras.optimizers.legacy.Adam`.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2819 - mse: 0.2819 - binary_accuracy: 0.5000\n", + "Epoch 2/500\n", + "4/4 [==============================] - 0s 890us/step - loss: 0.2572 - mse: 0.2572 - binary_accuracy: 0.5000\n", + "Epoch 3/500\n", + "4/4 [==============================] - 0s 922us/step - loss: 0.2598 - mse: 0.2598 - binary_accuracy: 0.5000\n", + "Epoch 4/500\n", + "4/4 [==============================] - 0s 972us/step - loss: 0.2542 - mse: 0.2542 - binary_accuracy: 0.5000\n", + "Epoch 5/500\n", + "4/4 [==============================] - 0s 960us/step - loss: 0.2532 - mse: 0.2532 - binary_accuracy: 0.5000\n", + "Epoch 6/500\n", + "4/4 [==============================] - 0s 975us/step - loss: 0.2532 - mse: 0.2532 - binary_accuracy: 0.5000\n", + "Epoch 7/500\n", + "4/4 [==============================] - 0s 926us/step - loss: 0.2508 - mse: 0.2508 - binary_accuracy: 0.5000\n", + "Epoch 8/500\n", + "4/4 [==============================] - 0s 876us/step - loss: 0.2520 - mse: 0.2520 - binary_accuracy: 0.5000\n", + "Epoch 9/500\n", + "4/4 [==============================] - 0s 908us/step - loss: 0.2535 - mse: 0.2535 - binary_accuracy: 0.2500\n", + "Epoch 10/500\n", + "4/4 [==============================] - 0s 993us/step - loss: 0.2566 - mse: 0.2566 - binary_accuracy: 0.2500\n", + "Epoch 11/500\n", + "4/4 [==============================] - 0s 985us/step - loss: 0.2543 - mse: 0.2543 - binary_accuracy: 0.5000\n", + "Epoch 12/500\n", + "4/4 [==============================] - 0s 911us/step - loss: 0.2520 - mse: 0.2520 - binary_accuracy: 0.5000\n", + "Epoch 13/500\n", + "4/4 [==============================] - 0s 964us/step - loss: 0.2531 - mse: 0.2531 - binary_accuracy: 0.5000\n", + "Epoch 14/500\n", + "4/4 [==============================] - 0s 3ms/step - loss: 0.2533 - mse: 0.2533 - binary_accuracy: 0.2500\n", + "Epoch 15/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2512 - mse: 0.2512 - binary_accuracy: 0.7500\n", + "Epoch 16/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2511 - mse: 0.2511 - binary_accuracy: 0.7500\n", + "Epoch 17/500\n", + "4/4 [==============================] - 0s 932us/step - loss: 0.2504 - mse: 0.2504 - binary_accuracy: 0.5000\n", + "Epoch 18/500\n", + "4/4 [==============================] - 0s 922us/step - loss: 0.2507 - mse: 0.2507 - binary_accuracy: 0.5000\n", + "Epoch 19/500\n", + "4/4 [==============================] - 0s 844us/step - loss: 0.2531 - mse: 0.2531 - binary_accuracy: 0.5000\n", + "Epoch 20/500\n", + "4/4 [==============================] - 0s 993us/step - loss: 0.2524 - mse: 0.2524 - binary_accuracy: 0.5000\n", + "Epoch 21/500\n", + "4/4 [==============================] - 0s 895us/step - loss: 0.2504 - mse: 0.2504 - binary_accuracy: 0.5000\n", + "Epoch 22/500\n", + "4/4 [==============================] - 0s 896us/step - loss: 0.2505 - mse: 0.2505 - binary_accuracy: 0.7500\n", + "Epoch 23/500\n", + "4/4 [==============================] - 0s 950us/step - loss: 0.2522 - mse: 0.2522 - binary_accuracy: 0.7500\n", + "Epoch 24/500\n", + "4/4 [==============================] - 0s 813us/step - loss: 0.2507 - mse: 0.2507 - binary_accuracy: 0.7500\n", + "Epoch 25/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2484 - mse: 0.2484 - binary_accuracy: 0.7500\n", + "Epoch 26/500\n", + "4/4 [==============================] - 0s 830us/step - loss: 0.2480 - mse: 0.2480 - binary_accuracy: 0.7500\n", + "Epoch 27/500\n", + "4/4 [==============================] - 0s 952us/step - loss: 0.2502 - mse: 0.2502 - binary_accuracy: 0.7500\n", + "Epoch 28/500\n", + "4/4 [==============================] - 0s 951us/step - loss: 0.2489 - mse: 0.2489 - binary_accuracy: 0.7500\n", + "Epoch 29/500\n", + "4/4 [==============================] - 0s 890us/step - loss: 0.2476 - mse: 0.2476 - binary_accuracy: 0.7500\n", + "Epoch 30/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2526 - mse: 0.2526 - binary_accuracy: 0.2500\n", + "Epoch 31/500\n", + "4/4 [==============================] - 0s 814us/step - loss: 0.2485 - mse: 0.2485 - binary_accuracy: 0.2500\n", + "Epoch 32/500\n", + "4/4 [==============================] - 0s 900us/step - loss: 0.2518 - mse: 0.2518 - binary_accuracy: 0.2500\n", + "Epoch 33/500\n", + "4/4 [==============================] - 0s 934us/step - loss: 0.2480 - mse: 0.2480 - binary_accuracy: 0.5000\n", + "Epoch 34/500\n", + "4/4 [==============================] - 0s 869us/step - loss: 0.2482 - mse: 0.2482 - binary_accuracy: 0.5000\n", + "Epoch 35/500\n", + "4/4 [==============================] - 0s 908us/step - loss: 0.2498 - mse: 0.2498 - binary_accuracy: 0.7500\n", + "Epoch 36/500\n", + "4/4 [==============================] - 0s 992us/step - loss: 0.2478 - mse: 0.2478 - binary_accuracy: 0.7500\n", + "Epoch 37/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.2468 - mse: 0.2468 - binary_accuracy: 0.7500\n", + "Epoch 38/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.2461 - mse: 0.2461 - binary_accuracy: 0.7500\n", + "Epoch 39/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2458 - mse: 0.2458 - binary_accuracy: 0.7500\n", + "Epoch 40/500\n", + "4/4 [==============================] - 0s 836us/step - loss: 0.2451 - mse: 0.2451 - binary_accuracy: 0.7500\n", + "Epoch 41/500\n", + "4/4 [==============================] - 0s 960us/step - loss: 0.2449 - mse: 0.2449 - binary_accuracy: 0.7500\n", + "Epoch 42/500\n", + "4/4 [==============================] - 0s 957us/step - loss: 0.2484 - mse: 0.2484 - binary_accuracy: 0.7500\n", + "Epoch 43/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2435 - mse: 0.2435 - binary_accuracy: 0.7500\n", + "Epoch 44/500\n", + "4/4 [==============================] - 0s 949us/step - loss: 0.2440 - mse: 0.2440 - binary_accuracy: 0.7500\n", + "Epoch 45/500\n", + "4/4 [==============================] - 0s 857us/step - loss: 0.2436 - mse: 0.2436 - binary_accuracy: 0.7500\n", + "Epoch 46/500\n", + "4/4 [==============================] - 0s 843us/step - loss: 0.2431 - mse: 0.2431 - binary_accuracy: 0.7500\n", + "Epoch 47/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2426 - mse: 0.2426 - binary_accuracy: 0.7500\n", + "Epoch 48/500\n", + "4/4 [==============================] - 0s 837us/step - loss: 0.2422 - mse: 0.2422 - binary_accuracy: 0.7500\n", + "Epoch 49/500\n", + "4/4 [==============================] - 0s 941us/step - loss: 0.2417 - mse: 0.2417 - binary_accuracy: 0.7500\n", + "Epoch 50/500\n", + "4/4 [==============================] - 0s 889us/step - loss: 0.2412 - mse: 0.2412 - binary_accuracy: 0.7500\n", + "Epoch 51/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2437 - mse: 0.2437 - binary_accuracy: 0.7500\n", + "Epoch 52/500\n", + "4/4 [==============================] - 0s 855us/step - loss: 0.2416 - mse: 0.2416 - binary_accuracy: 0.7500\n", + "Epoch 53/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2406 - mse: 0.2406 - binary_accuracy: 0.2500\n", + "Epoch 54/500\n", + "4/4 [==============================] - 0s 849us/step - loss: 0.2379 - mse: 0.2379 - binary_accuracy: 0.7500\n", + "Epoch 55/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2409 - mse: 0.2409 - binary_accuracy: 0.7500\n", + "Epoch 56/500\n", + "4/4 [==============================] - 0s 868us/step - loss: 0.2383 - mse: 0.2383 - binary_accuracy: 0.7500\n", + "Epoch 57/500\n", + "4/4 [==============================] - 0s 970us/step - loss: 0.2375 - mse: 0.2375 - binary_accuracy: 0.7500\n", + "Epoch 58/500\n", + "4/4 [==============================] - 0s 929us/step - loss: 0.2371 - mse: 0.2371 - binary_accuracy: 0.7500\n", + "Epoch 59/500\n", + "4/4 [==============================] - 0s 914us/step - loss: 0.2362 - mse: 0.2362 - binary_accuracy: 0.7500\n", + "Epoch 60/500\n", + "4/4 [==============================] - 0s 920us/step - loss: 0.2405 - mse: 0.2405 - binary_accuracy: 0.7500\n", + "Epoch 61/500\n", + "4/4 [==============================] - 0s 897us/step - loss: 0.2356 - mse: 0.2356 - binary_accuracy: 0.7500\n", + "Epoch 62/500\n", + "4/4 [==============================] - 0s 904us/step - loss: 0.2348 - mse: 0.2348 - binary_accuracy: 0.7500\n", + "Epoch 63/500\n", + "4/4 [==============================] - 0s 893us/step - loss: 0.2344 - mse: 0.2344 - binary_accuracy: 0.7500\n", + "Epoch 64/500\n", + "4/4 [==============================] - 0s 949us/step - loss: 0.2357 - mse: 0.2357 - binary_accuracy: 0.7500\n", + "Epoch 65/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2382 - mse: 0.2382 - binary_accuracy: 0.7500\n", + "Epoch 66/500\n", + "4/4 [==============================] - 0s 762us/step - loss: 0.2342 - mse: 0.2342 - binary_accuracy: 0.7500\n", + "Epoch 67/500\n", + "4/4 [==============================] - 0s 967us/step - loss: 0.2326 - mse: 0.2326 - binary_accuracy: 0.7500\n", + "Epoch 68/500\n", + "4/4 [==============================] - 0s 833us/step - loss: 0.2307 - mse: 0.2307 - binary_accuracy: 0.7500\n", + "Epoch 69/500\n", + "4/4 [==============================] - 0s 820us/step - loss: 0.2299 - mse: 0.2299 - binary_accuracy: 0.7500\n", + "Epoch 70/500\n", + "4/4 [==============================] - 0s 929us/step - loss: 0.2314 - mse: 0.2314 - binary_accuracy: 0.7500\n", + "Epoch 71/500\n", + "4/4 [==============================] - 0s 883us/step - loss: 0.2297 - mse: 0.2297 - binary_accuracy: 0.7500\n", + "Epoch 72/500\n", + "4/4 [==============================] - 0s 911us/step - loss: 0.2274 - mse: 0.2274 - binary_accuracy: 0.7500\n", + "Epoch 73/500\n", + "4/4 [==============================] - 0s 816us/step - loss: 0.2282 - mse: 0.2282 - binary_accuracy: 0.7500\n", + "Epoch 74/500\n", + "4/4 [==============================] - 0s 968us/step - loss: 0.2277 - mse: 0.2277 - binary_accuracy: 0.7500\n", + "Epoch 75/500\n", + "4/4 [==============================] - 0s 990us/step - loss: 0.2255 - mse: 0.2255 - binary_accuracy: 0.7500\n", + "Epoch 76/500\n", + "4/4 [==============================] - 0s 984us/step - loss: 0.2247 - mse: 0.2247 - binary_accuracy: 0.7500\n", + "Epoch 77/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2238 - mse: 0.2238 - binary_accuracy: 0.7500\n", + "Epoch 78/500\n", + "4/4 [==============================] - 0s 710us/step - loss: 0.2224 - mse: 0.2224 - binary_accuracy: 0.7500\n", + "Epoch 79/500\n", + "4/4 [==============================] - 0s 898us/step - loss: 0.2244 - mse: 0.2244 - binary_accuracy: 0.7500\n", + "Epoch 80/500\n", + "4/4 [==============================] - 0s 922us/step - loss: 0.2225 - mse: 0.2225 - binary_accuracy: 0.7500\n", + "Epoch 81/500\n", + "4/4 [==============================] - 0s 827us/step - loss: 0.2217 - mse: 0.2217 - binary_accuracy: 0.7500\n", + "Epoch 82/500\n", + "4/4 [==============================] - 0s 1000us/step - loss: 0.2199 - mse: 0.2199 - binary_accuracy: 0.7500\n", + "Epoch 83/500\n", + "4/4 [==============================] - 0s 806us/step - loss: 0.2176 - mse: 0.2176 - binary_accuracy: 0.7500\n", + "Epoch 84/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2156 - mse: 0.2156 - binary_accuracy: 0.7500\n", + "Epoch 85/500\n", + "4/4 [==============================] - 0s 846us/step - loss: 0.2161 - mse: 0.2161 - binary_accuracy: 0.7500\n", + "Epoch 86/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2157 - mse: 0.2157 - binary_accuracy: 0.7500\n", + "Epoch 87/500\n", + "4/4 [==============================] - 0s 844us/step - loss: 0.2176 - mse: 0.2176 - binary_accuracy: 0.7500\n", + "Epoch 88/500\n", + "4/4 [==============================] - 0s 951us/step - loss: 0.2135 - mse: 0.2135 - binary_accuracy: 0.7500\n", + "Epoch 89/500\n", + "4/4 [==============================] - 0s 927us/step - loss: 0.2144 - mse: 0.2144 - binary_accuracy: 0.7500\n", + "Epoch 90/500\n", + "4/4 [==============================] - 0s 894us/step - loss: 0.2110 - mse: 0.2110 - binary_accuracy: 0.7500\n", + "Epoch 91/500\n", + "4/4 [==============================] - 0s 950us/step - loss: 0.2113 - mse: 0.2113 - binary_accuracy: 0.7500\n", + "Epoch 92/500\n", + "4/4 [==============================] - 0s 983us/step - loss: 0.2086 - mse: 0.2086 - binary_accuracy: 0.7500\n", + "Epoch 93/500\n", + "4/4 [==============================] - 0s 896us/step - loss: 0.2093 - mse: 0.2093 - binary_accuracy: 0.7500\n", + "Epoch 94/500\n", + "4/4 [==============================] - 0s 948us/step - loss: 0.2087 - mse: 0.2087 - binary_accuracy: 0.7500\n", + "Epoch 95/500\n", + "4/4 [==============================] - 0s 839us/step - loss: 0.2066 - mse: 0.2066 - binary_accuracy: 0.7500\n", + "Epoch 96/500\n", + "4/4 [==============================] - 0s 933us/step - loss: 0.2059 - mse: 0.2059 - binary_accuracy: 0.7500\n", + "Epoch 97/500\n", + "4/4 [==============================] - 0s 926us/step - loss: 0.2078 - mse: 0.2078 - binary_accuracy: 0.7500\n", + "Epoch 98/500\n", + "4/4 [==============================] - 0s 880us/step - loss: 0.2048 - mse: 0.2048 - binary_accuracy: 0.7500\n", + "Epoch 99/500\n", + "4/4 [==============================] - 0s 928us/step - loss: 0.2025 - mse: 0.2025 - binary_accuracy: 0.7500\n", + "Epoch 100/500\n", + "4/4 [==============================] - 0s 885us/step - loss: 0.2022 - mse: 0.2022 - binary_accuracy: 0.7500\n", + "Epoch 101/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2051 - mse: 0.2051 - binary_accuracy: 0.7500\n", + "Epoch 102/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.2008 - mse: 0.2008 - binary_accuracy: 0.7500\n", + "Epoch 103/500\n", + "4/4 [==============================] - 0s 871us/step - loss: 0.1997 - mse: 0.1997 - binary_accuracy: 0.7500\n", + "Epoch 104/500\n", + "4/4 [==============================] - 0s 899us/step - loss: 0.2012 - mse: 0.2012 - binary_accuracy: 0.7500\n", + "Epoch 105/500\n", + "4/4 [==============================] - 0s 930us/step - loss: 0.2015 - mse: 0.2015 - binary_accuracy: 0.7500\n", + "Epoch 106/500\n", + "4/4 [==============================] - 0s 929us/step - loss: 0.1977 - mse: 0.1977 - binary_accuracy: 0.7500\n", + "Epoch 107/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1989 - mse: 0.1989 - binary_accuracy: 0.7500\n", + "Epoch 108/500\n", + "4/4 [==============================] - 0s 917us/step - loss: 0.1978 - mse: 0.1978 - binary_accuracy: 0.7500\n", + "Epoch 109/500\n", + "4/4 [==============================] - 0s 839us/step - loss: 0.1959 - mse: 0.1959 - binary_accuracy: 0.7500\n", + "Epoch 110/500\n", + "4/4 [==============================] - 0s 880us/step - loss: 0.1936 - mse: 0.1936 - binary_accuracy: 0.7500\n", + "Epoch 111/500\n", + "4/4 [==============================] - 0s 974us/step - loss: 0.1927 - mse: 0.1927 - binary_accuracy: 0.7500\n", + "Epoch 112/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.1928 - mse: 0.1928 - binary_accuracy: 0.7500\n", + "Epoch 113/500\n", + "4/4 [==============================] - 0s 927us/step - loss: 0.1914 - mse: 0.1914 - binary_accuracy: 0.7500\n", + "Epoch 114/500\n", + "4/4 [==============================] - 0s 820us/step - loss: 0.1921 - mse: 0.1921 - binary_accuracy: 0.7500\n", + "Epoch 115/500\n", + "4/4 [==============================] - 0s 946us/step - loss: 0.1887 - mse: 0.1887 - binary_accuracy: 0.7500\n", + "Epoch 116/500\n", + "4/4 [==============================] - 0s 897us/step - loss: 0.1898 - mse: 0.1898 - binary_accuracy: 0.7500\n", + "Epoch 117/500\n", + "4/4 [==============================] - 0s 898us/step - loss: 0.1875 - mse: 0.1875 - binary_accuracy: 0.7500\n", + "Epoch 118/500\n", + "4/4 [==============================] - 0s 886us/step - loss: 0.1866 - mse: 0.1866 - binary_accuracy: 0.7500\n", + "Epoch 119/500\n", + "4/4 [==============================] - 0s 979us/step - loss: 0.1865 - mse: 0.1865 - binary_accuracy: 0.7500\n", + "Epoch 120/500\n", + "4/4 [==============================] - 0s 864us/step - loss: 0.1854 - mse: 0.1854 - binary_accuracy: 0.7500\n", + "Epoch 121/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1869 - mse: 0.1869 - binary_accuracy: 0.7500\n", + "Epoch 122/500\n", + "4/4 [==============================] - 0s 872us/step - loss: 0.1836 - mse: 0.1836 - binary_accuracy: 0.7500\n", + "Epoch 123/500\n", + "4/4 [==============================] - 0s 998us/step - loss: 0.1826 - mse: 0.1826 - binary_accuracy: 0.7500\n", + "Epoch 124/500\n", + "4/4 [==============================] - 0s 945us/step - loss: 0.1837 - mse: 0.1837 - binary_accuracy: 0.7500\n", + "Epoch 125/500\n", + "4/4 [==============================] - 0s 930us/step - loss: 0.1830 - mse: 0.1830 - binary_accuracy: 0.7500\n", + "Epoch 126/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1818 - mse: 0.1818 - binary_accuracy: 0.7500\n", + "Epoch 127/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1816 - mse: 0.1816 - binary_accuracy: 0.7500\n", + "Epoch 128/500\n", + "4/4 [==============================] - 0s 792us/step - loss: 0.1803 - mse: 0.1803 - binary_accuracy: 0.7500\n", + "Epoch 129/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1790 - mse: 0.1790 - binary_accuracy: 0.7500\n", + "Epoch 130/500\n", + "4/4 [==============================] - 0s 961us/step - loss: 0.1778 - mse: 0.1778 - binary_accuracy: 0.7500\n", + "Epoch 131/500\n", + "4/4 [==============================] - 0s 896us/step - loss: 0.1775 - mse: 0.1775 - binary_accuracy: 0.7500\n", + "Epoch 132/500\n", + "4/4 [==============================] - 0s 859us/step - loss: 0.1773 - mse: 0.1773 - binary_accuracy: 0.7500\n", + "Epoch 133/500\n", + "4/4 [==============================] - 0s 966us/step - loss: 0.1777 - mse: 0.1777 - binary_accuracy: 0.7500\n", + "Epoch 134/500\n", + "4/4 [==============================] - 0s 765us/step - loss: 0.1752 - mse: 0.1752 - binary_accuracy: 0.7500\n", + "Epoch 135/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1764 - mse: 0.1764 - binary_accuracy: 0.7500\n", + "Epoch 136/500\n", + "4/4 [==============================] - 0s 810us/step - loss: 0.1738 - mse: 0.1738 - binary_accuracy: 0.7500\n", + "Epoch 137/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1771 - mse: 0.1771 - binary_accuracy: 0.7500\n", + "Epoch 138/500\n", + "4/4 [==============================] - 0s 836us/step - loss: 0.1742 - mse: 0.1742 - binary_accuracy: 0.7500\n", + "Epoch 139/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1722 - mse: 0.1722 - binary_accuracy: 0.7500\n", + "Epoch 140/500\n", + "4/4 [==============================] - 0s 807us/step - loss: 0.1727 - mse: 0.1727 - binary_accuracy: 0.7500\n", + "Epoch 141/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1729 - mse: 0.1729 - binary_accuracy: 0.7500\n", + "Epoch 142/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.1692 - mse: 0.1692 - binary_accuracy: 0.7500\n", + "Epoch 143/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1701 - mse: 0.1701 - binary_accuracy: 0.7500\n", + "Epoch 144/500\n", + "4/4 [==============================] - 0s 879us/step - loss: 0.1674 - mse: 0.1674 - binary_accuracy: 0.7500\n", + "Epoch 145/500\n", + "4/4 [==============================] - 0s 877us/step - loss: 0.1683 - mse: 0.1683 - binary_accuracy: 0.7500\n", + "Epoch 146/500\n", + "4/4 [==============================] - 0s 868us/step - loss: 0.1671 - mse: 0.1671 - binary_accuracy: 0.7500\n", + "Epoch 147/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1657 - mse: 0.1657 - binary_accuracy: 0.7500\n", + "Epoch 148/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1643 - mse: 0.1643 - binary_accuracy: 0.7500\n", + "Epoch 149/500\n", + "4/4 [==============================] - 0s 997us/step - loss: 0.1659 - mse: 0.1659 - binary_accuracy: 0.7500\n", + "Epoch 150/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1636 - mse: 0.1636 - binary_accuracy: 0.7500\n", + "Epoch 151/500\n", + "4/4 [==============================] - 0s 965us/step - loss: 0.1627 - mse: 0.1627 - binary_accuracy: 0.7500\n", + "Epoch 152/500\n", + "4/4 [==============================] - 0s 938us/step - loss: 0.1616 - mse: 0.1616 - binary_accuracy: 0.7500\n", + "Epoch 153/500\n", + "4/4 [==============================] - 0s 809us/step - loss: 0.1643 - mse: 0.1643 - binary_accuracy: 0.7500\n", + "Epoch 154/500\n", + "4/4 [==============================] - 0s 870us/step - loss: 0.1622 - mse: 0.1622 - binary_accuracy: 0.7500\n", + "Epoch 155/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1610 - mse: 0.1610 - binary_accuracy: 0.7500\n", + "Epoch 156/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1592 - mse: 0.1592 - binary_accuracy: 0.7500\n", + "Epoch 157/500\n", + "4/4 [==============================] - 0s 989us/step - loss: 0.1627 - mse: 0.1627 - binary_accuracy: 0.7500\n", + "Epoch 158/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1569 - mse: 0.1569 - binary_accuracy: 0.7500\n", + "Epoch 159/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1575 - mse: 0.1575 - binary_accuracy: 0.7500\n", + "Epoch 160/500\n", + "4/4 [==============================] - 0s 926us/step - loss: 0.1559 - mse: 0.1559 - binary_accuracy: 0.7500\n", + "Epoch 161/500\n", + "4/4 [==============================] - 0s 926us/step - loss: 0.1593 - mse: 0.1593 - binary_accuracy: 0.7500\n", + "Epoch 162/500\n", + "4/4 [==============================] - 0s 814us/step - loss: 0.1535 - mse: 0.1535 - binary_accuracy: 0.7500\n", + "Epoch 163/500\n", + "4/4 [==============================] - 0s 935us/step - loss: 0.1535 - mse: 0.1535 - binary_accuracy: 0.7500\n", + "Epoch 164/500\n", + "4/4 [==============================] - 0s 942us/step - loss: 0.1519 - mse: 0.1519 - binary_accuracy: 0.7500\n", + "Epoch 165/500\n", + "4/4 [==============================] - 0s 828us/step - loss: 0.1552 - mse: 0.1552 - binary_accuracy: 0.7500\n", + "Epoch 166/500\n", + "4/4 [==============================] - 0s 815us/step - loss: 0.1513 - mse: 0.1513 - binary_accuracy: 0.7500\n", + "Epoch 167/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1497 - mse: 0.1497 - binary_accuracy: 0.7500\n", + "Epoch 168/500\n", + "4/4 [==============================] - 0s 772us/step - loss: 0.1497 - mse: 0.1497 - binary_accuracy: 0.7500\n", + "Epoch 169/500\n", + "4/4 [==============================] - 0s 946us/step - loss: 0.1494 - mse: 0.1494 - binary_accuracy: 0.7500\n", + "Epoch 170/500\n", + "4/4 [==============================] - 0s 862us/step - loss: 0.1480 - mse: 0.1480 - binary_accuracy: 0.7500\n", + "Epoch 171/500\n", + "4/4 [==============================] - 0s 994us/step - loss: 0.1475 - mse: 0.1475 - binary_accuracy: 0.7500\n", + "Epoch 172/500\n", + "4/4 [==============================] - 0s 769us/step - loss: 0.1442 - mse: 0.1442 - binary_accuracy: 0.7500\n", + "Epoch 173/500\n", + "4/4 [==============================] - 0s 986us/step - loss: 0.1462 - mse: 0.1462 - binary_accuracy: 0.7500\n", + "Epoch 174/500\n", + "4/4 [==============================] - 0s 920us/step - loss: 0.1442 - mse: 0.1442 - binary_accuracy: 0.7500\n", + "Epoch 175/500\n", + "4/4 [==============================] - 0s 940us/step - loss: 0.1412 - mse: 0.1412 - binary_accuracy: 1.0000\n", + "Epoch 176/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1419 - mse: 0.1419 - binary_accuracy: 1.0000\n", + "Epoch 177/500\n", + "4/4 [==============================] - 0s 959us/step - loss: 0.1407 - mse: 0.1407 - binary_accuracy: 1.0000\n", + "Epoch 178/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1390 - mse: 0.1390 - binary_accuracy: 0.7500\n", + "Epoch 179/500\n", + "4/4 [==============================] - 0s 952us/step - loss: 0.1381 - mse: 0.1381 - binary_accuracy: 0.7500\n", + "Epoch 180/500\n", + "4/4 [==============================] - 0s 935us/step - loss: 0.1358 - mse: 0.1358 - binary_accuracy: 0.7500\n", + "Epoch 181/500\n", + "4/4 [==============================] - 0s 952us/step - loss: 0.1369 - mse: 0.1369 - binary_accuracy: 0.7500\n", + "Epoch 182/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1331 - mse: 0.1331 - binary_accuracy: 1.0000\n", + "Epoch 183/500\n", + "4/4 [==============================] - 0s 803us/step - loss: 0.1326 - mse: 0.1326 - binary_accuracy: 1.0000\n", + "Epoch 184/500\n", + "4/4 [==============================] - 0s 810us/step - loss: 0.1306 - mse: 0.1306 - binary_accuracy: 1.0000\n", + "Epoch 185/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1311 - mse: 0.1311 - binary_accuracy: 1.0000\n", + "Epoch 186/500\n", + "4/4 [==============================] - 0s 883us/step - loss: 0.1291 - mse: 0.1291 - binary_accuracy: 1.0000\n", + "Epoch 187/500\n", + "4/4 [==============================] - 0s 883us/step - loss: 0.1280 - mse: 0.1280 - binary_accuracy: 1.0000\n", + "Epoch 188/500\n", + "4/4 [==============================] - 0s 884us/step - loss: 0.1256 - mse: 0.1256 - binary_accuracy: 1.0000\n", + "Epoch 189/500\n", + "4/4 [==============================] - 0s 893us/step - loss: 0.1250 - mse: 0.1250 - binary_accuracy: 1.0000\n", + "Epoch 190/500\n", + "4/4 [==============================] - 0s 794us/step - loss: 0.1242 - mse: 0.1242 - binary_accuracy: 1.0000\n", + "Epoch 191/500\n", + "4/4 [==============================] - 0s 798us/step - loss: 0.1239 - mse: 0.1239 - binary_accuracy: 1.0000\n", + "Epoch 192/500\n", + "4/4 [==============================] - 0s 895us/step - loss: 0.1234 - mse: 0.1234 - binary_accuracy: 1.0000\n", + "Epoch 193/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1213 - mse: 0.1213 - binary_accuracy: 1.0000\n", + "Epoch 194/500\n", + "4/4 [==============================] - 0s 769us/step - loss: 0.1203 - mse: 0.1203 - binary_accuracy: 1.0000\n", + "Epoch 195/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1180 - mse: 0.1180 - binary_accuracy: 1.0000\n", + "Epoch 196/500\n", + "4/4 [==============================] - 0s 907us/step - loss: 0.1175 - mse: 0.1175 - binary_accuracy: 1.0000\n", + "Epoch 197/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1147 - mse: 0.1147 - binary_accuracy: 1.0000\n", + "Epoch 198/500\n", + "4/4 [==============================] - 0s 862us/step - loss: 0.1137 - mse: 0.1137 - binary_accuracy: 1.0000\n", + "Epoch 199/500\n", + "4/4 [==============================] - 0s 985us/step - loss: 0.1121 - mse: 0.1121 - binary_accuracy: 1.0000\n", + "Epoch 200/500\n", + "4/4 [==============================] - 0s 919us/step - loss: 0.1102 - mse: 0.1102 - binary_accuracy: 1.0000\n", + "Epoch 201/500\n", + "4/4 [==============================] - 0s 886us/step - loss: 0.1100 - mse: 0.1100 - binary_accuracy: 1.0000\n", + "Epoch 202/500\n", + "4/4 [==============================] - 0s 963us/step - loss: 0.1080 - mse: 0.1080 - binary_accuracy: 1.0000\n", + "Epoch 203/500\n", + "4/4 [==============================] - 0s 873us/step - loss: 0.1066 - mse: 0.1066 - binary_accuracy: 1.0000\n", + "Epoch 204/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1061 - mse: 0.1061 - binary_accuracy: 1.0000\n", + "Epoch 205/500\n", + "4/4 [==============================] - 0s 844us/step - loss: 0.1031 - mse: 0.1031 - binary_accuracy: 1.0000\n", + "Epoch 206/500\n", + "4/4 [==============================] - 0s 992us/step - loss: 0.1024 - mse: 0.1024 - binary_accuracy: 1.0000\n", + "Epoch 207/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1014 - mse: 0.1014 - binary_accuracy: 1.0000\n", + "Epoch 208/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.1004 - mse: 0.1004 - binary_accuracy: 1.0000\n", + "Epoch 209/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0995 - mse: 0.0995 - binary_accuracy: 1.0000\n", + "Epoch 210/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0973 - mse: 0.0973 - binary_accuracy: 1.0000\n", + "Epoch 211/500\n", + "4/4 [==============================] - 0s 923us/step - loss: 0.0954 - mse: 0.0954 - binary_accuracy: 1.0000\n", + "Epoch 212/500\n", + "4/4 [==============================] - 0s 975us/step - loss: 0.0943 - mse: 0.0943 - binary_accuracy: 1.0000\n", + "Epoch 213/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0949 - mse: 0.0949 - binary_accuracy: 1.0000\n", + "Epoch 214/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0922 - mse: 0.0922 - binary_accuracy: 1.0000\n", + "Epoch 215/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0900 - mse: 0.0900 - binary_accuracy: 1.0000\n", + "Epoch 216/500\n", + "4/4 [==============================] - 0s 788us/step - loss: 0.0899 - mse: 0.0899 - binary_accuracy: 1.0000\n", + "Epoch 217/500\n", + "4/4 [==============================] - 0s 852us/step - loss: 0.0879 - mse: 0.0879 - binary_accuracy: 1.0000\n", + "Epoch 218/500\n", + "4/4 [==============================] - 0s 788us/step - loss: 0.0866 - mse: 0.0866 - binary_accuracy: 1.0000\n", + "Epoch 219/500\n", + "4/4 [==============================] - 0s 850us/step - loss: 0.0851 - mse: 0.0851 - binary_accuracy: 1.0000\n", + "Epoch 220/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0855 - mse: 0.0855 - binary_accuracy: 1.0000\n", + "Epoch 221/500\n", + "4/4 [==============================] - 0s 828us/step - loss: 0.0835 - mse: 0.0835 - binary_accuracy: 1.0000\n", + "Epoch 222/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0818 - mse: 0.0818 - binary_accuracy: 1.0000\n", + "Epoch 223/500\n", + "4/4 [==============================] - 0s 717us/step - loss: 0.0811 - mse: 0.0811 - binary_accuracy: 1.0000\n", + "Epoch 224/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0791 - mse: 0.0791 - binary_accuracy: 1.0000\n", + "Epoch 225/500\n", + "4/4 [==============================] - 0s 923us/step - loss: 0.0781 - mse: 0.0781 - binary_accuracy: 1.0000\n", + "Epoch 226/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0770 - mse: 0.0770 - binary_accuracy: 1.0000\n", + "Epoch 227/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0756 - mse: 0.0756 - binary_accuracy: 1.0000\n", + "Epoch 228/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0743 - mse: 0.0743 - binary_accuracy: 1.0000\n", + "Epoch 229/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0754 - mse: 0.0754 - binary_accuracy: 1.0000\n", + "Epoch 230/500\n", + "4/4 [==============================] - 0s 884us/step - loss: 0.0726 - mse: 0.0726 - binary_accuracy: 1.0000\n", + "Epoch 231/500\n", + "4/4 [==============================] - 0s 953us/step - loss: 0.0720 - mse: 0.0720 - binary_accuracy: 1.0000\n", + "Epoch 232/500\n", + "4/4 [==============================] - 0s 966us/step - loss: 0.0700 - mse: 0.0700 - binary_accuracy: 1.0000\n", + "Epoch 233/500\n", + "4/4 [==============================] - 0s 851us/step - loss: 0.0692 - mse: 0.0692 - binary_accuracy: 1.0000\n", + "Epoch 234/500\n", + "4/4 [==============================] - 0s 791us/step - loss: 0.0688 - mse: 0.0688 - binary_accuracy: 1.0000\n", + "Epoch 235/500\n", + "4/4 [==============================] - 0s 811us/step - loss: 0.0668 - mse: 0.0668 - binary_accuracy: 1.0000\n", + "Epoch 236/500\n", + "4/4 [==============================] - 0s 864us/step - loss: 0.0658 - mse: 0.0658 - binary_accuracy: 1.0000\n", + "Epoch 237/500\n", + "4/4 [==============================] - 0s 954us/step - loss: 0.0646 - mse: 0.0646 - binary_accuracy: 1.0000\n", + "Epoch 238/500\n", + "4/4 [==============================] - 0s 876us/step - loss: 0.0642 - mse: 0.0642 - binary_accuracy: 1.0000\n", + "Epoch 239/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0623 - mse: 0.0623 - binary_accuracy: 1.0000\n", + "Epoch 240/500\n", + "4/4 [==============================] - 0s 881us/step - loss: 0.0613 - mse: 0.0613 - binary_accuracy: 1.0000\n", + "Epoch 241/500\n", + "4/4 [==============================] - 0s 884us/step - loss: 0.0629 - mse: 0.0629 - binary_accuracy: 1.0000\n", + "Epoch 242/500\n", + "4/4 [==============================] - 0s 804us/step - loss: 0.0598 - mse: 0.0598 - binary_accuracy: 1.0000\n", + "Epoch 243/500\n", + "4/4 [==============================] - 0s 975us/step - loss: 0.0591 - mse: 0.0591 - binary_accuracy: 1.0000\n", + "Epoch 244/500\n", + "4/4 [==============================] - 0s 841us/step - loss: 0.0589 - mse: 0.0589 - binary_accuracy: 1.0000\n", + "Epoch 245/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0572 - mse: 0.0572 - binary_accuracy: 1.0000\n", + "Epoch 246/500\n", + "4/4 [==============================] - 0s 898us/step - loss: 0.0563 - mse: 0.0563 - binary_accuracy: 1.0000\n", + "Epoch 247/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0551 - mse: 0.0551 - binary_accuracy: 1.0000\n", + "Epoch 248/500\n", + "4/4 [==============================] - 0s 955us/step - loss: 0.0544 - mse: 0.0544 - binary_accuracy: 1.0000\n", + "Epoch 249/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0544 - mse: 0.0544 - binary_accuracy: 1.0000\n", + "Epoch 250/500\n", + "4/4 [==============================] - 0s 920us/step - loss: 0.0538 - mse: 0.0538 - binary_accuracy: 1.0000\n", + "Epoch 251/500\n", + "4/4 [==============================] - 0s 887us/step - loss: 0.0524 - mse: 0.0524 - binary_accuracy: 1.0000\n", + "Epoch 252/500\n", + "4/4 [==============================] - 0s 976us/step - loss: 0.0513 - mse: 0.0513 - binary_accuracy: 1.0000\n", + "Epoch 253/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0504 - mse: 0.0504 - binary_accuracy: 1.0000\n", + "Epoch 254/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0497 - mse: 0.0497 - binary_accuracy: 1.0000\n", + "Epoch 255/500\n", + "4/4 [==============================] - 0s 916us/step - loss: 0.0495 - mse: 0.0495 - binary_accuracy: 1.0000\n", + "Epoch 256/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0485 - mse: 0.0485 - binary_accuracy: 1.0000\n", + "Epoch 257/500\n", + "4/4 [==============================] - 0s 914us/step - loss: 0.0481 - mse: 0.0481 - binary_accuracy: 1.0000\n", + "Epoch 258/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0470 - mse: 0.0470 - binary_accuracy: 1.0000\n", + "Epoch 259/500\n", + "4/4 [==============================] - 0s 786us/step - loss: 0.0462 - mse: 0.0462 - binary_accuracy: 1.0000\n", + "Epoch 260/500\n", + "4/4 [==============================] - 0s 987us/step - loss: 0.0458 - mse: 0.0458 - binary_accuracy: 1.0000\n", + "Epoch 261/500\n", + "4/4 [==============================] - 0s 904us/step - loss: 0.0453 - mse: 0.0453 - binary_accuracy: 1.0000\n", + "Epoch 262/500\n", + "4/4 [==============================] - 0s 958us/step - loss: 0.0449 - mse: 0.0449 - binary_accuracy: 1.0000\n", + "Epoch 263/500\n", + "4/4 [==============================] - 0s 859us/step - loss: 0.0440 - mse: 0.0440 - binary_accuracy: 1.0000\n", + "Epoch 264/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0432 - mse: 0.0432 - binary_accuracy: 1.0000\n", + "Epoch 265/500\n", + "4/4 [==============================] - 0s 813us/step - loss: 0.0423 - mse: 0.0423 - binary_accuracy: 1.0000\n", + "Epoch 266/500\n", + "4/4 [==============================] - 0s 895us/step - loss: 0.0419 - mse: 0.0419 - binary_accuracy: 1.0000\n", + "Epoch 267/500\n", + "4/4 [==============================] - 0s 859us/step - loss: 0.0414 - mse: 0.0414 - binary_accuracy: 1.0000\n", + "Epoch 268/500\n", + "4/4 [==============================] - 0s 949us/step - loss: 0.0408 - mse: 0.0408 - binary_accuracy: 1.0000\n", + "Epoch 269/500\n", + "4/4 [==============================] - 0s 779us/step - loss: 0.0403 - mse: 0.0403 - binary_accuracy: 1.0000\n", + "Epoch 270/500\n", + "4/4 [==============================] - 0s 956us/step - loss: 0.0398 - mse: 0.0398 - binary_accuracy: 1.0000\n", + "Epoch 271/500\n", + "4/4 [==============================] - 0s 939us/step - loss: 0.0392 - mse: 0.0392 - binary_accuracy: 1.0000\n", + "Epoch 272/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0386 - mse: 0.0386 - binary_accuracy: 1.0000\n", + "Epoch 273/500\n", + "4/4 [==============================] - 0s 966us/step - loss: 0.0380 - mse: 0.0380 - binary_accuracy: 1.0000\n", + "Epoch 274/500\n", + "4/4 [==============================] - 0s 953us/step - loss: 0.0377 - mse: 0.0377 - binary_accuracy: 1.0000\n", + "Epoch 275/500\n", + "4/4 [==============================] - 0s 984us/step - loss: 0.0370 - mse: 0.0370 - binary_accuracy: 1.0000\n", + "Epoch 276/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0366 - mse: 0.0366 - binary_accuracy: 1.0000\n", + "Epoch 277/500\n", + "4/4 [==============================] - 0s 966us/step - loss: 0.0359 - mse: 0.0359 - binary_accuracy: 1.0000\n", + "Epoch 278/500\n", + "4/4 [==============================] - 0s 859us/step - loss: 0.0356 - mse: 0.0356 - binary_accuracy: 1.0000\n", + "Epoch 279/500\n", + "4/4 [==============================] - 0s 951us/step - loss: 0.0351 - mse: 0.0351 - binary_accuracy: 1.0000\n", + "Epoch 280/500\n", + "4/4 [==============================] - 0s 953us/step - loss: 0.0348 - mse: 0.0348 - binary_accuracy: 1.0000\n", + "Epoch 281/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0345 - mse: 0.0345 - binary_accuracy: 1.0000\n", + "Epoch 282/500\n", + "4/4 [==============================] - 0s 934us/step - loss: 0.0339 - mse: 0.0339 - binary_accuracy: 1.0000\n", + "Epoch 283/500\n", + "4/4 [==============================] - 0s 889us/step - loss: 0.0333 - mse: 0.0333 - binary_accuracy: 1.0000\n", + "Epoch 284/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0329 - mse: 0.0329 - binary_accuracy: 1.0000\n", + "Epoch 285/500\n", + "4/4 [==============================] - 0s 989us/step - loss: 0.0327 - mse: 0.0327 - binary_accuracy: 1.0000\n", + "Epoch 286/500\n", + "4/4 [==============================] - 0s 919us/step - loss: 0.0321 - mse: 0.0321 - binary_accuracy: 1.0000\n", + "Epoch 287/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0316 - mse: 0.0316 - binary_accuracy: 1.0000\n", + "Epoch 288/500\n", + "4/4 [==============================] - 0s 892us/step - loss: 0.0312 - mse: 0.0312 - binary_accuracy: 1.0000\n", + "Epoch 289/500\n", + "4/4 [==============================] - 0s 938us/step - loss: 0.0308 - mse: 0.0308 - binary_accuracy: 1.0000\n", + "Epoch 290/500\n", + "4/4 [==============================] - 0s 940us/step - loss: 0.0305 - mse: 0.0305 - binary_accuracy: 1.0000\n", + "Epoch 291/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0301 - mse: 0.0301 - binary_accuracy: 1.0000\n", + "Epoch 292/500\n", + "4/4 [==============================] - 0s 912us/step - loss: 0.0298 - mse: 0.0298 - binary_accuracy: 1.0000\n", + "Epoch 293/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0296 - mse: 0.0296 - binary_accuracy: 1.0000\n", + "Epoch 294/500\n", + "4/4 [==============================] - 0s 936us/step - loss: 0.0292 - mse: 0.0292 - binary_accuracy: 1.0000\n", + "Epoch 295/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0289 - mse: 0.0289 - binary_accuracy: 1.0000\n", + "Epoch 296/500\n", + "4/4 [==============================] - 0s 869us/step - loss: 0.0285 - mse: 0.0285 - binary_accuracy: 1.0000\n", + "Epoch 297/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0281 - mse: 0.0281 - binary_accuracy: 1.0000\n", + "Epoch 298/500\n", + "4/4 [==============================] - 0s 957us/step - loss: 0.0278 - mse: 0.0278 - binary_accuracy: 1.0000\n", + "Epoch 299/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0274 - mse: 0.0274 - binary_accuracy: 1.0000\n", + "Epoch 300/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0270 - mse: 0.0270 - binary_accuracy: 1.0000\n", + "Epoch 301/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0270 - mse: 0.0270 - binary_accuracy: 1.0000\n", + "Epoch 302/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0265 - mse: 0.0265 - binary_accuracy: 1.0000\n", + "Epoch 303/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0261 - mse: 0.0261 - binary_accuracy: 1.0000\n", + "Epoch 304/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0259 - mse: 0.0259 - binary_accuracy: 1.0000\n", + "Epoch 305/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0256 - mse: 0.0256 - binary_accuracy: 1.0000\n", + "Epoch 306/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0253 - mse: 0.0253 - binary_accuracy: 1.0000\n", + "Epoch 307/500\n", + "4/4 [==============================] - 0s 932us/step - loss: 0.0250 - mse: 0.0250 - binary_accuracy: 1.0000\n", + "Epoch 308/500\n", + "4/4 [==============================] - 0s 894us/step - loss: 0.0247 - mse: 0.0247 - binary_accuracy: 1.0000\n", + "Epoch 309/500\n", + "4/4 [==============================] - 0s 851us/step - loss: 0.0246 - mse: 0.0246 - binary_accuracy: 1.0000\n", + "Epoch 310/500\n", + "4/4 [==============================] - 0s 836us/step - loss: 0.0242 - mse: 0.0242 - binary_accuracy: 1.0000\n", + "Epoch 311/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0239 - mse: 0.0239 - binary_accuracy: 1.0000\n", + "Epoch 312/500\n", + "4/4 [==============================] - 0s 794us/step - loss: 0.0238 - mse: 0.0238 - binary_accuracy: 1.0000\n", + "Epoch 313/500\n", + "4/4 [==============================] - 0s 993us/step - loss: 0.0235 - mse: 0.0235 - binary_accuracy: 1.0000\n", + "Epoch 314/500\n", + "4/4 [==============================] - 0s 806us/step - loss: 0.0232 - mse: 0.0232 - binary_accuracy: 1.0000\n", + "Epoch 315/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0229 - mse: 0.0229 - binary_accuracy: 1.0000\n", + "Epoch 316/500\n", + "4/4 [==============================] - 0s 937us/step - loss: 0.0227 - mse: 0.0227 - binary_accuracy: 1.0000\n", + "Epoch 317/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0224 - mse: 0.0224 - binary_accuracy: 1.0000\n", + "Epoch 318/500\n", + "4/4 [==============================] - 0s 899us/step - loss: 0.0222 - mse: 0.0222 - binary_accuracy: 1.0000\n", + "Epoch 319/500\n", + "4/4 [==============================] - 0s 930us/step - loss: 0.0219 - mse: 0.0219 - binary_accuracy: 1.0000\n", + "Epoch 320/500\n", + "4/4 [==============================] - 0s 889us/step - loss: 0.0217 - mse: 0.0217 - binary_accuracy: 1.0000\n", + "Epoch 321/500\n", + "4/4 [==============================] - 0s 889us/step - loss: 0.0216 - mse: 0.0216 - binary_accuracy: 1.0000\n", + "Epoch 322/500\n", + "4/4 [==============================] - 0s 915us/step - loss: 0.0213 - mse: 0.0213 - binary_accuracy: 1.0000\n", + "Epoch 323/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0210 - mse: 0.0210 - binary_accuracy: 1.0000\n", + "Epoch 324/500\n", + "4/4 [==============================] - 0s 817us/step - loss: 0.0209 - mse: 0.0209 - binary_accuracy: 1.0000\n", + "Epoch 325/500\n", + "4/4 [==============================] - 0s 916us/step - loss: 0.0207 - mse: 0.0207 - binary_accuracy: 1.0000\n", + "Epoch 326/500\n", + "4/4 [==============================] - 0s 896us/step - loss: 0.0204 - mse: 0.0204 - binary_accuracy: 1.0000\n", + "Epoch 327/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0202 - mse: 0.0202 - binary_accuracy: 1.0000\n", + "Epoch 328/500\n", + "4/4 [==============================] - 0s 912us/step - loss: 0.0201 - mse: 0.0201 - binary_accuracy: 1.0000\n", + "Epoch 329/500\n", + "4/4 [==============================] - 0s 898us/step - loss: 0.0198 - mse: 0.0198 - binary_accuracy: 1.0000\n", + "Epoch 330/500\n", + "4/4 [==============================] - 0s 835us/step - loss: 0.0197 - mse: 0.0197 - binary_accuracy: 1.0000\n", + "Epoch 331/500\n", + "4/4 [==============================] - 0s 903us/step - loss: 0.0195 - mse: 0.0195 - binary_accuracy: 1.0000\n", + "Epoch 332/500\n", + "4/4 [==============================] - 0s 970us/step - loss: 0.0193 - mse: 0.0193 - binary_accuracy: 1.0000\n", + "Epoch 333/500\n", + "4/4 [==============================] - 0s 936us/step - loss: 0.0191 - mse: 0.0191 - binary_accuracy: 1.0000\n", + "Epoch 334/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0189 - mse: 0.0189 - binary_accuracy: 1.0000\n", + "Epoch 335/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0187 - mse: 0.0187 - binary_accuracy: 1.0000\n", + "Epoch 336/500\n", + "4/4 [==============================] - 0s 917us/step - loss: 0.0186 - mse: 0.0186 - binary_accuracy: 1.0000\n", + "Epoch 337/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0183 - mse: 0.0183 - binary_accuracy: 1.0000\n", + "Epoch 338/500\n", + "4/4 [==============================] - 0s 907us/step - loss: 0.0182 - mse: 0.0182 - binary_accuracy: 1.0000\n", + "Epoch 339/500\n", + "4/4 [==============================] - 0s 883us/step - loss: 0.0180 - mse: 0.0180 - binary_accuracy: 1.0000\n", + "Epoch 340/500\n", + "4/4 [==============================] - 0s 910us/step - loss: 0.0178 - mse: 0.0178 - binary_accuracy: 1.0000\n", + "Epoch 341/500\n", + "4/4 [==============================] - 0s 912us/step - loss: 0.0177 - mse: 0.0177 - binary_accuracy: 1.0000\n", + "Epoch 342/500\n", + "4/4 [==============================] - 0s 841us/step - loss: 0.0175 - mse: 0.0175 - binary_accuracy: 1.0000\n", + "Epoch 343/500\n", + "4/4 [==============================] - 0s 835us/step - loss: 0.0174 - mse: 0.0174 - binary_accuracy: 1.0000\n", + "Epoch 344/500\n", + "4/4 [==============================] - 0s 698us/step - loss: 0.0172 - mse: 0.0172 - binary_accuracy: 1.0000\n", + "Epoch 345/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0170 - mse: 0.0170 - binary_accuracy: 1.0000\n", + "Epoch 346/500\n", + "4/4 [==============================] - 0s 962us/step - loss: 0.0170 - mse: 0.0170 - binary_accuracy: 1.0000\n", + "Epoch 347/500\n", + "4/4 [==============================] - 0s 935us/step - loss: 0.0167 - mse: 0.0167 - binary_accuracy: 1.0000\n", + "Epoch 348/500\n", + "4/4 [==============================] - 0s 930us/step - loss: 0.0166 - mse: 0.0166 - binary_accuracy: 1.0000\n", + "Epoch 349/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0165 - mse: 0.0165 - binary_accuracy: 1.0000\n", + "Epoch 350/500\n", + "4/4 [==============================] - 0s 798us/step - loss: 0.0163 - mse: 0.0163 - binary_accuracy: 1.0000\n", + "Epoch 351/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0162 - mse: 0.0162 - binary_accuracy: 1.0000\n", + "Epoch 352/500\n", + "4/4 [==============================] - 0s 848us/step - loss: 0.0160 - mse: 0.0160 - binary_accuracy: 1.0000\n", + "Epoch 353/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0159 - mse: 0.0159 - binary_accuracy: 1.0000\n", + "Epoch 354/500\n", + "4/4 [==============================] - 0s 770us/step - loss: 0.0157 - mse: 0.0157 - binary_accuracy: 1.0000\n", + "Epoch 355/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0156 - mse: 0.0156 - binary_accuracy: 1.0000\n", + "Epoch 356/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0155 - mse: 0.0155 - binary_accuracy: 1.0000\n", + "Epoch 357/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0153 - mse: 0.0153 - binary_accuracy: 1.0000\n", + "Epoch 358/500\n", + "4/4 [==============================] - 0s 806us/step - loss: 0.0152 - mse: 0.0152 - binary_accuracy: 1.0000\n", + "Epoch 359/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0150 - mse: 0.0150 - binary_accuracy: 1.0000\n", + "Epoch 360/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0149 - mse: 0.0149 - binary_accuracy: 1.0000\n", + "Epoch 361/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0148 - mse: 0.0148 - binary_accuracy: 1.0000\n", + "Epoch 362/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0147 - mse: 0.0147 - binary_accuracy: 1.0000\n", + "Epoch 363/500\n", + "4/4 [==============================] - 0s 842us/step - loss: 0.0145 - mse: 0.0145 - binary_accuracy: 1.0000\n", + "Epoch 364/500\n", + "4/4 [==============================] - 0s 910us/step - loss: 0.0145 - mse: 0.0145 - binary_accuracy: 1.0000\n", + "Epoch 365/500\n", + "4/4 [==============================] - 0s 900us/step - loss: 0.0144 - mse: 0.0144 - binary_accuracy: 1.0000\n", + "Epoch 366/500\n", + "4/4 [==============================] - 0s 832us/step - loss: 0.0142 - mse: 0.0142 - binary_accuracy: 1.0000\n", + "Epoch 367/500\n", + "4/4 [==============================] - 0s 771us/step - loss: 0.0141 - mse: 0.0141 - binary_accuracy: 1.0000\n", + "Epoch 368/500\n", + "4/4 [==============================] - 0s 885us/step - loss: 0.0141 - mse: 0.0141 - binary_accuracy: 1.0000\n", + "Epoch 369/500\n", + "4/4 [==============================] - 0s 795us/step - loss: 0.0138 - mse: 0.0138 - binary_accuracy: 1.0000\n", + "Epoch 370/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.0137 - mse: 0.0137 - binary_accuracy: 1.0000\n", + "Epoch 371/500\n", + "4/4 [==============================] - 0s 919us/step - loss: 0.0137 - mse: 0.0137 - binary_accuracy: 1.0000\n", + "Epoch 372/500\n", + "4/4 [==============================] - 0s 930us/step - loss: 0.0135 - mse: 0.0135 - binary_accuracy: 1.0000\n", + "Epoch 373/500\n", + "4/4 [==============================] - 0s 763us/step - loss: 0.0134 - mse: 0.0134 - binary_accuracy: 1.0000\n", + "Epoch 374/500\n", + "4/4 [==============================] - 0s 689us/step - loss: 0.0133 - mse: 0.0133 - binary_accuracy: 1.0000\n", + "Epoch 375/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0132 - mse: 0.0132 - binary_accuracy: 1.0000\n", + "Epoch 376/500\n", + "4/4 [==============================] - 0s 970us/step - loss: 0.0131 - mse: 0.0131 - binary_accuracy: 1.0000\n", + "Epoch 377/500\n", + "4/4 [==============================] - 0s 884us/step - loss: 0.0130 - mse: 0.0130 - binary_accuracy: 1.0000\n", + "Epoch 378/500\n", + "4/4 [==============================] - 0s 808us/step - loss: 0.0129 - mse: 0.0129 - binary_accuracy: 1.0000\n", + "Epoch 379/500\n", + "4/4 [==============================] - 0s 753us/step - loss: 0.0128 - mse: 0.0128 - binary_accuracy: 1.0000\n", + "Epoch 380/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.0127 - mse: 0.0127 - binary_accuracy: 1.0000\n", + "Epoch 381/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.0126 - mse: 0.0126 - binary_accuracy: 1.0000\n", + "Epoch 382/500\n", + "4/4 [==============================] - 0s 875us/step - loss: 0.0125 - mse: 0.0125 - binary_accuracy: 1.0000\n", + "Epoch 383/500\n", + "4/4 [==============================] - 0s 902us/step - loss: 0.0124 - mse: 0.0124 - binary_accuracy: 1.0000\n", + "Epoch 384/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0123 - mse: 0.0123 - binary_accuracy: 1.0000\n", + "Epoch 385/500\n", + "4/4 [==============================] - 0s 868us/step - loss: 0.0122 - mse: 0.0122 - binary_accuracy: 1.0000\n", + "Epoch 386/500\n", + "4/4 [==============================] - 0s 963us/step - loss: 0.0121 - mse: 0.0121 - binary_accuracy: 1.0000\n", + "Epoch 387/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0121 - mse: 0.0121 - binary_accuracy: 1.0000\n", + "Epoch 388/500\n", + "4/4 [==============================] - 0s 998us/step - loss: 0.0119 - mse: 0.0119 - binary_accuracy: 1.0000\n", + "Epoch 389/500\n", + "4/4 [==============================] - 0s 770us/step - loss: 0.0118 - mse: 0.0118 - binary_accuracy: 1.0000\n", + "Epoch 390/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0117 - mse: 0.0117 - binary_accuracy: 1.0000\n", + "Epoch 391/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0118 - mse: 0.0118 - binary_accuracy: 1.0000\n", + "Epoch 392/500\n", + "4/4 [==============================] - 0s 863us/step - loss: 0.0116 - mse: 0.0116 - binary_accuracy: 1.0000\n", + "Epoch 393/500\n", + "4/4 [==============================] - 0s 917us/step - loss: 0.0115 - mse: 0.0115 - binary_accuracy: 1.0000\n", + "Epoch 394/500\n", + "4/4 [==============================] - 0s 873us/step - loss: 0.0114 - mse: 0.0114 - binary_accuracy: 1.0000\n", + "Epoch 395/500\n", + "4/4 [==============================] - 0s 852us/step - loss: 0.0113 - mse: 0.0113 - binary_accuracy: 1.0000\n", + "Epoch 396/500\n", + "4/4 [==============================] - 0s 995us/step - loss: 0.0112 - mse: 0.0112 - binary_accuracy: 1.0000\n", + "Epoch 397/500\n", + "4/4 [==============================] - 0s 795us/step - loss: 0.0111 - mse: 0.0111 - binary_accuracy: 1.0000\n", + "Epoch 398/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0111 - mse: 0.0111 - binary_accuracy: 1.0000\n", + "Epoch 399/500\n", + "4/4 [==============================] - 0s 848us/step - loss: 0.0110 - mse: 0.0110 - binary_accuracy: 1.0000\n", + "Epoch 400/500\n", + "4/4 [==============================] - 0s 892us/step - loss: 0.0109 - mse: 0.0109 - binary_accuracy: 1.0000\n", + "Epoch 401/500\n", + "4/4 [==============================] - 0s 908us/step - loss: 0.0108 - mse: 0.0108 - binary_accuracy: 1.0000\n", + "Epoch 402/500\n", + "4/4 [==============================] - 0s 947us/step - loss: 0.0108 - mse: 0.0108 - binary_accuracy: 1.0000\n", + "Epoch 403/500\n", + "4/4 [==============================] - 0s 921us/step - loss: 0.0107 - mse: 0.0107 - binary_accuracy: 1.0000\n", + "Epoch 404/500\n", + "4/4 [==============================] - 0s 917us/step - loss: 0.0106 - mse: 0.0106 - binary_accuracy: 1.0000\n", + "Epoch 405/500\n", + "4/4 [==============================] - 0s 803us/step - loss: 0.0105 - mse: 0.0105 - binary_accuracy: 1.0000\n", + "Epoch 406/500\n", + "4/4 [==============================] - 0s 854us/step - loss: 0.0104 - mse: 0.0104 - binary_accuracy: 1.0000\n", + "Epoch 407/500\n", + "4/4 [==============================] - 0s 781us/step - loss: 0.0104 - mse: 0.0104 - binary_accuracy: 1.0000\n", + "Epoch 408/500\n", + "4/4 [==============================] - 0s 683us/step - loss: 0.0103 - mse: 0.0103 - binary_accuracy: 1.0000\n", + "Epoch 409/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0102 - mse: 0.0102 - binary_accuracy: 1.0000\n", + "Epoch 410/500\n", + "4/4 [==============================] - 0s 832us/step - loss: 0.0102 - mse: 0.0102 - binary_accuracy: 1.0000\n", + "Epoch 411/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0101 - mse: 0.0101 - binary_accuracy: 1.0000\n", + "Epoch 412/500\n", + "4/4 [==============================] - 0s 927us/step - loss: 0.0100 - mse: 0.0100 - binary_accuracy: 1.0000\n", + "Epoch 413/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0099 - mse: 0.0099 - binary_accuracy: 1.0000\n", + "Epoch 414/500\n", + "4/4 [==============================] - 0s 834us/step - loss: 0.0099 - mse: 0.0099 - binary_accuracy: 1.0000\n", + "Epoch 415/500\n", + "4/4 [==============================] - 0s 892us/step - loss: 0.0098 - mse: 0.0098 - binary_accuracy: 1.0000\n", + "Epoch 416/500\n", + "4/4 [==============================] - 0s 953us/step - loss: 0.0098 - mse: 0.0098 - binary_accuracy: 1.0000\n", + "Epoch 417/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0097 - mse: 0.0097 - binary_accuracy: 1.0000\n", + "Epoch 418/500\n", + "4/4 [==============================] - 0s 788us/step - loss: 0.0096 - mse: 0.0096 - binary_accuracy: 1.0000\n", + "Epoch 419/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0095 - mse: 0.0095 - binary_accuracy: 1.0000\n", + "Epoch 420/500\n", + "4/4 [==============================] - 0s 853us/step - loss: 0.0095 - mse: 0.0095 - binary_accuracy: 1.0000\n", + "Epoch 421/500\n", + "4/4 [==============================] - 0s 866us/step - loss: 0.0094 - mse: 0.0094 - binary_accuracy: 1.0000\n", + "Epoch 422/500\n", + "4/4 [==============================] - 0s 824us/step - loss: 0.0094 - mse: 0.0094 - binary_accuracy: 1.0000\n", + "Epoch 423/500\n", + "4/4 [==============================] - 0s 926us/step - loss: 0.0093 - mse: 0.0093 - binary_accuracy: 1.0000\n", + "Epoch 424/500\n", + "4/4 [==============================] - 0s 963us/step - loss: 0.0092 - mse: 0.0092 - binary_accuracy: 1.0000\n", + "Epoch 425/500\n", + "4/4 [==============================] - 0s 924us/step - loss: 0.0092 - mse: 0.0092 - binary_accuracy: 1.0000\n", + "Epoch 426/500\n", + "4/4 [==============================] - 0s 865us/step - loss: 0.0091 - mse: 0.0091 - binary_accuracy: 1.0000\n", + "Epoch 427/500\n", + "4/4 [==============================] - 0s 848us/step - loss: 0.0090 - mse: 0.0090 - binary_accuracy: 1.0000\n", + "Epoch 428/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0090 - mse: 0.0090 - binary_accuracy: 1.0000\n", + "Epoch 429/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0089 - mse: 0.0089 - binary_accuracy: 1.0000\n", + "Epoch 430/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0089 - mse: 0.0089 - binary_accuracy: 1.0000\n", + "Epoch 431/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0088 - mse: 0.0088 - binary_accuracy: 1.0000\n", + "Epoch 432/500\n", + "4/4 [==============================] - 0s 2ms/step - loss: 0.0088 - mse: 0.0088 - binary_accuracy: 1.0000\n", + "Epoch 433/500\n", + "4/4 [==============================] - 0s 907us/step - loss: 0.0087 - mse: 0.0087 - binary_accuracy: 1.0000\n", + "Epoch 434/500\n", + "4/4 [==============================] - 0s 949us/step - loss: 0.0086 - mse: 0.0086 - binary_accuracy: 1.0000\n", + "Epoch 435/500\n", + "4/4 [==============================] - 0s 947us/step - loss: 0.0086 - mse: 0.0086 - binary_accuracy: 1.0000\n", + "Epoch 436/500\n", + "4/4 [==============================] - 0s 863us/step - loss: 0.0085 - mse: 0.0085 - binary_accuracy: 1.0000\n", + "Epoch 437/500\n", + "4/4 [==============================] - 0s 675us/step - loss: 0.0085 - mse: 0.0085 - binary_accuracy: 1.0000\n", + "Epoch 438/500\n", + "4/4 [==============================] - 0s 988us/step - loss: 0.0084 - mse: 0.0084 - binary_accuracy: 1.0000\n", + "Epoch 439/500\n", + "4/4 [==============================] - 0s 961us/step - loss: 0.0084 - mse: 0.0084 - binary_accuracy: 1.0000\n", + "Epoch 440/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0083 - mse: 0.0083 - binary_accuracy: 1.0000\n", + "Epoch 441/500\n", + "4/4 [==============================] - 0s 863us/step - loss: 0.0083 - mse: 0.0083 - binary_accuracy: 1.0000\n", + "Epoch 442/500\n", + "4/4 [==============================] - 0s 887us/step - loss: 0.0082 - mse: 0.0082 - binary_accuracy: 1.0000\n", + "Epoch 443/500\n", + "4/4 [==============================] - 0s 742us/step - loss: 0.0082 - mse: 0.0082 - binary_accuracy: 1.0000\n", + "Epoch 444/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0081 - mse: 0.0081 - binary_accuracy: 1.0000\n", + "Epoch 445/500\n", + "4/4 [==============================] - 0s 852us/step - loss: 0.0080 - mse: 0.0080 - binary_accuracy: 1.0000\n", + "Epoch 446/500\n", + "4/4 [==============================] - 0s 851us/step - loss: 0.0080 - mse: 0.0080 - binary_accuracy: 1.0000\n", + "Epoch 447/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0080 - mse: 0.0080 - binary_accuracy: 1.0000\n", + "Epoch 448/500\n", + "4/4 [==============================] - 0s 916us/step - loss: 0.0079 - mse: 0.0079 - binary_accuracy: 1.0000\n", + "Epoch 449/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0079 - mse: 0.0079 - binary_accuracy: 1.0000\n", + "Epoch 450/500\n", + "4/4 [==============================] - 0s 914us/step - loss: 0.0078 - mse: 0.0078 - binary_accuracy: 1.0000\n", + "Epoch 451/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0078 - mse: 0.0078 - binary_accuracy: 1.0000\n", + "Epoch 452/500\n", + "4/4 [==============================] - 0s 797us/step - loss: 0.0077 - mse: 0.0077 - binary_accuracy: 1.0000\n", + "Epoch 453/500\n", + "4/4 [==============================] - 0s 959us/step - loss: 0.0077 - mse: 0.0077 - binary_accuracy: 1.0000\n", + "Epoch 454/500\n", + "4/4 [==============================] - 0s 930us/step - loss: 0.0076 - mse: 0.0076 - binary_accuracy: 1.0000\n", + "Epoch 455/500\n", + "4/4 [==============================] - 0s 981us/step - loss: 0.0076 - mse: 0.0076 - binary_accuracy: 1.0000\n", + "Epoch 456/500\n", + "4/4 [==============================] - 0s 855us/step - loss: 0.0075 - mse: 0.0075 - binary_accuracy: 1.0000\n", + "Epoch 457/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0075 - mse: 0.0075 - binary_accuracy: 1.0000\n", + "Epoch 458/500\n", + "4/4 [==============================] - 0s 753us/step - loss: 0.0074 - mse: 0.0074 - binary_accuracy: 1.0000\n", + "Epoch 459/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0074 - mse: 0.0074 - binary_accuracy: 1.0000\n", + "Epoch 460/500\n", + "4/4 [==============================] - 0s 804us/step - loss: 0.0074 - mse: 0.0074 - binary_accuracy: 1.0000\n", + "Epoch 461/500\n", + "4/4 [==============================] - 0s 844us/step - loss: 0.0073 - mse: 0.0073 - binary_accuracy: 1.0000\n", + "Epoch 462/500\n", + "4/4 [==============================] - 0s 811us/step - loss: 0.0073 - mse: 0.0073 - binary_accuracy: 1.0000\n", + "Epoch 463/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0072 - mse: 0.0072 - binary_accuracy: 1.0000\n", + "Epoch 464/500\n", + "4/4 [==============================] - 0s 976us/step - loss: 0.0072 - mse: 0.0072 - binary_accuracy: 1.0000\n", + "Epoch 465/500\n", + "4/4 [==============================] - 0s 863us/step - loss: 0.0071 - mse: 0.0071 - binary_accuracy: 1.0000\n", + "Epoch 466/500\n", + "4/4 [==============================] - 0s 923us/step - loss: 0.0071 - mse: 0.0071 - binary_accuracy: 1.0000\n", + "Epoch 467/500\n", + "4/4 [==============================] - 0s 912us/step - loss: 0.0071 - mse: 0.0071 - binary_accuracy: 1.0000\n", + "Epoch 468/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0070 - mse: 0.0070 - binary_accuracy: 1.0000\n", + "Epoch 469/500\n", + "4/4 [==============================] - 0s 956us/step - loss: 0.0070 - mse: 0.0070 - binary_accuracy: 1.0000\n", + "Epoch 470/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0069 - mse: 0.0069 - binary_accuracy: 1.0000\n", + "Epoch 471/500\n", + "4/4 [==============================] - 0s 956us/step - loss: 0.0069 - mse: 0.0069 - binary_accuracy: 1.0000\n", + "Epoch 472/500\n", + "4/4 [==============================] - 0s 946us/step - loss: 0.0068 - mse: 0.0068 - binary_accuracy: 1.0000\n", + "Epoch 473/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0068 - mse: 0.0068 - binary_accuracy: 1.0000\n", + "Epoch 474/500\n", + "4/4 [==============================] - 0s 971us/step - loss: 0.0068 - mse: 0.0068 - binary_accuracy: 1.0000\n", + "Epoch 475/500\n", + "4/4 [==============================] - 0s 976us/step - loss: 0.0067 - mse: 0.0067 - binary_accuracy: 1.0000\n", + "Epoch 476/500\n", + "4/4 [==============================] - 0s 927us/step - loss: 0.0067 - mse: 0.0067 - binary_accuracy: 1.0000\n", + "Epoch 477/500\n", + "4/4 [==============================] - 0s 985us/step - loss: 0.0067 - mse: 0.0067 - binary_accuracy: 1.0000\n", + "Epoch 478/500\n", + "4/4 [==============================] - 0s 934us/step - loss: 0.0066 - mse: 0.0066 - binary_accuracy: 1.0000\n", + "Epoch 479/500\n", + "4/4 [==============================] - 0s 808us/step - loss: 0.0066 - mse: 0.0066 - binary_accuracy: 1.0000\n", + "Epoch 480/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0065 - mse: 0.0065 - binary_accuracy: 1.0000\n", + "Epoch 481/500\n", + "4/4 [==============================] - 0s 933us/step - loss: 0.0065 - mse: 0.0065 - binary_accuracy: 1.0000\n", + "Epoch 482/500\n", + "4/4 [==============================] - 0s 950us/step - loss: 0.0065 - mse: 0.0065 - binary_accuracy: 1.0000\n", + "Epoch 483/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0064 - mse: 0.0064 - binary_accuracy: 1.0000\n", + "Epoch 484/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0064 - mse: 0.0064 - binary_accuracy: 1.0000\n", + "Epoch 485/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0064 - mse: 0.0064 - binary_accuracy: 1.0000\n", + "Epoch 486/500\n", + "4/4 [==============================] - 0s 887us/step - loss: 0.0063 - mse: 0.0063 - binary_accuracy: 1.0000\n", + "Epoch 487/500\n", + "4/4 [==============================] - 0s 958us/step - loss: 0.0063 - mse: 0.0063 - binary_accuracy: 1.0000\n", + "Epoch 488/500\n", + "4/4 [==============================] - 0s 812us/step - loss: 0.0063 - mse: 0.0063 - binary_accuracy: 1.0000\n", + "Epoch 489/500\n", + "4/4 [==============================] - 0s 947us/step - loss: 0.0062 - mse: 0.0062 - binary_accuracy: 1.0000\n", + "Epoch 490/500\n", + "4/4 [==============================] - 0s 808us/step - loss: 0.0062 - mse: 0.0062 - binary_accuracy: 1.0000\n", + "Epoch 491/500\n", + "4/4 [==============================] - 0s 855us/step - loss: 0.0062 - mse: 0.0062 - binary_accuracy: 1.0000\n", + "Epoch 492/500\n", + "4/4 [==============================] - 0s 722us/step - loss: 0.0061 - mse: 0.0061 - binary_accuracy: 1.0000\n", + "Epoch 493/500\n", + "4/4 [==============================] - 0s 980us/step - loss: 0.0061 - mse: 0.0061 - binary_accuracy: 1.0000\n", + "Epoch 494/500\n", + "4/4 [==============================] - 0s 932us/step - loss: 0.0061 - mse: 0.0061 - binary_accuracy: 1.0000\n", + "Epoch 495/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0060 - mse: 0.0060 - binary_accuracy: 1.0000\n", + "Epoch 496/500\n", + "4/4 [==============================] - 0s 847us/step - loss: 0.0060 - mse: 0.0060 - binary_accuracy: 1.0000\n", + "Epoch 497/500\n", + "4/4 [==============================] - 0s 999us/step - loss: 0.0060 - mse: 0.0060 - binary_accuracy: 1.0000\n", + "Epoch 498/500\n", + "4/4 [==============================] - 0s 939us/step - loss: 0.0059 - mse: 0.0059 - binary_accuracy: 1.0000\n", + "Epoch 499/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0059 - mse: 0.0059 - binary_accuracy: 1.0000\n", + "Epoch 500/500\n", + "4/4 [==============================] - 0s 1ms/step - loss: 0.0059 - mse: 0.0059 - binary_accuracy: 1.0000\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "########### Ab hier Aufgabenblatt 4 ##############\n", + "# Aufgabe 3\n", + "import tensorflow as tf\n", + "from tensorflow import keras\n", + "\n", + "#input\n", + "x = np.array([[0,0], [0,1], [1,0], [1,1]], dtype=np.float32)\n", + "#output\n", + "y = np.array([[0],[1],[1],[0]], dtype=np.float32)\n", + "\n", + "model = tf.keras.models.Sequential()\n", + "model.add(tf.keras.Input(shape=(2,)))\n", + "model.add(tf.keras.layers.Dense(2, activation=tf.keras.activations.sigmoid, kernel_initializer=tf.initializers.Constant(0.5)))\n", + "model.add(tf.keras.layers.Dense(1, activation=tf.keras.activations.sigmoid))\n", + "\n", + "model.compile(optimizer=tf.keras.optimizers.legacy.Adam(learning_rate=0.05), loss=tf.keras.losses.MeanSquaredError(), metrics=['mse', 'binary_accuracy'])\n", + "#model.summary()\n", + "\n", + "model.fit(x, y, batch_size=1, epochs=500)\n", + "\n", + "# Klappt 20/20 Mal (nur 20 mal getestet)\n", + "\n" + ] } ], "metadata": { @@ -287,7 +1340,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9 (main, Dec 15 2022, 17:11:09) [Clang 14.0.0 (clang-1400.0.29.202)]" + "version": "3.10.9" }, "orig_nbformat": 4, "vscode": {