Created
April 28, 2020 14:55
-
-
Save sergei-mironov/724e0598bbc56deb3ae6507a8527f6f4 to your computer and use it in GitHub Desktop.
codebraid_progress_bar.html
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| <!DOCTYPE html> | |
| <html xmlns="http://www.w3.org/1999/xhtml" lang xml:lang> | |
| <head> | |
| <meta charset="utf-8" /> | |
| <meta name="generator" content="pandoc" /> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> | |
| <title>BERT Pretraining</title> | |
| <style> | |
| code{white-space: pre-wrap;} | |
| span.smallcaps{font-variant: small-caps;} | |
| span.underline{text-decoration: underline;} | |
| div.column{display: inline-block; vertical-align: top; width: 50%;} | |
| </style> | |
| <style> | |
| a.sourceLine { display: inline-block; line-height: 1.25; } | |
| a.sourceLine { pointer-events: none; color: inherit; text-decoration: inherit; } | |
| a.sourceLine:empty { height: 1.2em; } | |
| .sourceCode { overflow: visible; } | |
| code.sourceCode { white-space: pre; position: relative; } | |
| div.sourceCode { margin: 1em 0; } | |
| pre.sourceCode { margin: 0; } | |
| @media screen { | |
| div.sourceCode { overflow: auto; } | |
| } | |
| @media print { | |
| code.sourceCode { white-space: pre-wrap; } | |
| a.sourceLine { text-indent: -1em; padding-left: 1em; } | |
| } | |
| pre.numberSource a.sourceLine | |
| { position: relative; left: -4em; } | |
| pre.numberSource a.sourceLine::before | |
| { content: attr(title); | |
| position: relative; left: -1em; text-align: right; vertical-align: baseline; | |
| border: none; pointer-events: all; display: inline-block; | |
| -webkit-touch-callout: none; -webkit-user-select: none; | |
| -khtml-user-select: none; -moz-user-select: none; | |
| -ms-user-select: none; user-select: none; | |
| padding: 0 4px; width: 4em; | |
| color: #aaaaaa; | |
| } | |
| pre.numberSource { margin-left: 3em; border-left: 1px solid #aaaaaa; padding-left: 4px; } | |
| div.sourceCode | |
| { } | |
| @media screen { | |
| a.sourceLine::before { text-decoration: underline; } | |
| } | |
| code span.al { color: #ff0000; font-weight: bold; } /* Alert */ | |
| code span.an { color: #60a0b0; font-weight: bold; font-style: italic; } /* Annotation */ | |
| code span.at { color: #7d9029; } /* Attribute */ | |
| code span.bn { color: #40a070; } /* BaseN */ | |
| code span.bu { } /* BuiltIn */ | |
| code span.cf { color: #007020; font-weight: bold; } /* ControlFlow */ | |
| code span.ch { color: #4070a0; } /* Char */ | |
| code span.cn { color: #880000; } /* Constant */ | |
| code span.co { color: #60a0b0; font-style: italic; } /* Comment */ | |
| code span.cv { color: #60a0b0; font-weight: bold; font-style: italic; } /* CommentVar */ | |
| code span.do { color: #ba2121; font-style: italic; } /* Documentation */ | |
| code span.dt { color: #902000; } /* DataType */ | |
| code span.dv { color: #40a070; } /* DecVal */ | |
| code span.er { color: #ff0000; font-weight: bold; } /* Error */ | |
| code span.ex { } /* Extension */ | |
| code span.fl { color: #40a070; } /* Float */ | |
| code span.fu { color: #06287e; } /* Function */ | |
| code span.im { } /* Import */ | |
| code span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Information */ | |
| code span.kw { color: #007020; font-weight: bold; } /* Keyword */ | |
| code span.op { color: #666666; } /* Operator */ | |
| code span.ot { color: #007020; } /* Other */ | |
| code span.pp { color: #bc7a00; } /* Preprocessor */ | |
| code span.sc { color: #4070a0; } /* SpecialChar */ | |
| code span.ss { color: #bb6688; } /* SpecialString */ | |
| code span.st { color: #4070a0; } /* String */ | |
| code span.va { color: #19177c; } /* Variable */ | |
| code span.vs { color: #4070a0; } /* VerbatimString */ | |
| code span.wa { color: #60a0b0; font-weight: bold; font-style: italic; } /* Warning */ | |
| </style> | |
| <!--[if lt IE 9]> | |
| <script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.3/html5shiv-printshiv.min.js"></script> | |
| <![endif]--> | |
| </head> | |
| <body> | |
| <h1 id="example-showing-an-snippet-which-prints-a-progress-bar">Example showing an snippet which prints a progress-bar</h1> | |
| <div class="sourceCode" id="cb1" data-startFrom="1"><pre class="sourceCode numberSource python numberLines"><code class="sourceCode python"><a class="sourceLine" id="cb1-1" title="1"><span class="im">from</span> stagedml.stages.<span class="bu">all</span> <span class="im">import</span> <span class="op">*</span></a> | |
| <a class="sourceLine" id="cb1-2" title="2">rref<span class="op">=</span>realize(instantiate(all_convnn_mnist), force_rebuild<span class="op">=</span><span class="va">True</span>)</a></code></pre></div> | |
| <pre class="stdout"><code>x_train shape: (60000, 28, 28, 1) | |
| 60000 train samples | |
| 10000 test samples | |
| Train on 48000 samples, validate on 12000 samples | |
| Epoch 1/6 | |
| 32/48000 [..............................] - ETA: 25:23 - loss: 2.3240 - accuracy: 0.0312 | |
| 480/48000 [..............................] - ETA: 1:45 - loss: 1.8179 - accuracy: 0.4021 | |
| 896/48000 [..............................] - ETA: 58s - loss: 1.5192 - accuracy: 0.4944 | |
| 1312/48000 [..............................] - ETA: 41s - loss: 1.2903 - accuracy: 0.5716 | |
| 1760/48000 [>.............................] - ETA: 32s - loss: 1.1251 - accuracy: 0.6284 | |
| 2240/48000 [>.............................] - ETA: 25s - loss: 1.0159 - accuracy: 0.6607 | |
| 2656/48000 [>.............................] - ETA: 22s - loss: 0.9500 - accuracy: 0.6849 | |
| 3072/48000 [>.............................] - ETA: 20s - loss: 0.8908 - accuracy: 0.7067 | |
| 3424/48000 [=>............................] - ETA: 18s - loss: 0.8404 - accuracy: 0.7223 | |
| 3808/48000 [=>............................] - ETA: 17s - loss: 0.7976 - accuracy: 0.7363 | |
| 4192/48000 [=>............................] - ETA: 15s - loss: 0.7625 - accuracy: 0.7488 | |
| 4704/48000 [=>............................] - ETA: 14s - loss: 0.7222 - accuracy: 0.7634 | |
| 5184/48000 [==>...........................] - ETA: 13s - loss: 0.6870 - accuracy: 0.7758 | |
| 5632/48000 [==>...........................] - ETA: 12s - loss: 0.6583 - accuracy: 0.7862 | |
| 5984/48000 [==>...........................] - ETA: 12s - loss: 0.6354 - accuracy: 0.7936 | |
| 6336/48000 [==>...........................] - ETA: 11s - loss: 0.6205 - accuracy: 0.7986 | |
| 6784/48000 [===>..........................] - ETA: 11s - loss: 0.6092 - accuracy: 0.8038 | |
| 7360/48000 [===>..........................] - ETA: 10s - loss: 0.5870 - accuracy: 0.8110 | |
| 7904/48000 [===>..........................] - ETA: 9s - loss: 0.5644 - accuracy: 0.8191 | |
| 8448/48000 [====>.........................] - ETA: 9s - loss: 0.5419 - accuracy: 0.8268 | |
| 8960/48000 [====>.........................] - ETA: 8s - loss: 0.5253 - accuracy: 0.8313 | |
| 9536/48000 [====>.........................] - ETA: 8s - loss: 0.5091 - accuracy: 0.8361 | |
| 10112/48000 [=====>........................] - ETA: 8s - loss: 0.4922 - accuracy: 0.8420 | |
| 10688/48000 [=====>........................] - ETA: 7s - loss: 0.4748 - accuracy: 0.8479 | |
| 11296/48000 [======>.......................] - ETA: 7s - loss: 0.4601 - accuracy: 0.8530 | |
| 11872/48000 [======>.......................] - ETA: 7s - loss: 0.4453 - accuracy: 0.8581 | |
| 12448/48000 [======>.......................] - ETA: 6s - loss: 0.4338 - accuracy: 0.8622 | |
| 13024/48000 [=======>......................] - ETA: 6s - loss: 0.4255 - accuracy: 0.8657 | |
| 13600/48000 [=======>......................] - ETA: 6s - loss: 0.4158 - accuracy: 0.8686 | |
| 14176/48000 [=======>......................] - ETA: 5s - loss: 0.4060 - accuracy: 0.8713 | |
| 14720/48000 [========>.....................] - ETA: 5s - loss: 0.3985 - accuracy: 0.8739 | |
| 15296/48000 [========>.....................] - ETA: 5s - loss: 0.3922 - accuracy: 0.8760 | |
| 15808/48000 [========>.....................] - ETA: 5s - loss: 0.3847 - accuracy: 0.8784 | |
| 16352/48000 [=========>....................] - ETA: 5s - loss: 0.3767 - accuracy: 0.8811 | |
| 16896/48000 [=========>....................] - ETA: 5s - loss: 0.3689 - accuracy: 0.8835 | |
| 17440/48000 [=========>....................] - ETA: 4s - loss: 0.3630 - accuracy: 0.8854 | |
| 18016/48000 [==========>...................] - ETA: 4s - loss: 0.3587 - accuracy: 0.8871 | |
| 18624/48000 [==========>...................] - ETA: 4s - loss: 0.3526 - accuracy: 0.8892 | |
| 19168/48000 [==========>...................] - ETA: 4s - loss: 0.3465 - accuracy: 0.8910 | |
| 19744/48000 [===========>..................] - ETA: 4s - loss: 0.3407 - accuracy: 0.8926 | |
| 20288/48000 [===========>..................] - ETA: 4s - loss: 0.3368 - accuracy: 0.8938 | |
| 20704/48000 [===========>..................] - ETA: 4s - loss: 0.3338 - accuracy: 0.8950 | |
| 21120/48000 [============>.................] - ETA: 4s - loss: 0.3305 - accuracy: 0.8962 | |
| 21536/48000 [============>.................] - ETA: 3s - loss: 0.3276 - accuracy: 0.8972 | |
| 22016/48000 [============>.................] - ETA: 3s - loss: 0.3227 - accuracy: 0.8988 | |
| 22496/48000 [=============>................] - ETA: 3s - loss: 0.3202 - accuracy: 0.8997 | |
| 22976/48000 [=============>................] - ETA: 3s - loss: 0.3177 - accuracy: 0.9006 | |
| 23520/48000 [=============>................] - ETA: 3s - loss: 0.3136 - accuracy: 0.9019 | |
| 23936/48000 [=============>................] - ETA: 3s - loss: 0.3111 - accuracy: 0.9027 | |
| 24384/48000 [==============>...............] - ETA: 3s - loss: 0.3080 - accuracy: 0.9037 | |
| 24992/48000 [==============>...............] - ETA: 3s - loss: 0.3039 - accuracy: 0.9049 | |
| 25536/48000 [==============>...............] - ETA: 3s - loss: 0.2999 - accuracy: 0.9062 | |
| 26080/48000 [===============>..............] - ETA: 3s - loss: 0.2974 - accuracy: 0.9070 | |
| 26592/48000 [===============>..............] - ETA: 3s - loss: 0.2943 - accuracy: 0.9081 | |
| 27136/48000 [===============>..............] - ETA: 2s - loss: 0.2919 - accuracy: 0.9089 | |
| 27616/48000 [================>.............] - ETA: 2s - loss: 0.2890 - accuracy: 0.9100 | |
| 28000/48000 [================>.............] - ETA: 2s - loss: 0.2875 - accuracy: 0.9106 | |
| 28416/48000 [================>.............] - ETA: 2s - loss: 0.2849 - accuracy: 0.9115 | |
| 28928/48000 [=================>............] - ETA: 2s - loss: 0.2823 - accuracy: 0.9124 | |
| 29472/48000 [=================>............] - ETA: 2s - loss: 0.2792 - accuracy: 0.9134 | |
| 29888/48000 [=================>............] - ETA: 2s - loss: 0.2772 - accuracy: 0.9140 | |
| 30400/48000 [==================>...........] - ETA: 2s - loss: 0.2749 - accuracy: 0.9147 | |
| 30912/48000 [==================>...........] - ETA: 2s - loss: 0.2735 - accuracy: 0.9150 | |
| 31360/48000 [==================>...........] - ETA: 2s - loss: 0.2708 - accuracy: 0.9158 | |
| 31904/48000 [==================>...........] - ETA: 2s - loss: 0.2684 - accuracy: 0.9166 | |
| 32480/48000 [===================>..........] - ETA: 2s - loss: 0.2655 - accuracy: 0.9175 | |
| 33024/48000 [===================>..........] - ETA: 2s - loss: 0.2627 - accuracy: 0.9183 | |
| 33568/48000 [===================>..........] - ETA: 1s - loss: 0.2603 - accuracy: 0.9192 | |
| 34112/48000 [====================>.........] - ETA: 1s - loss: 0.2587 - accuracy: 0.9197 | |
| 34656/48000 [====================>.........] - ETA: 1s - loss: 0.2570 - accuracy: 0.9201 | |
| 35168/48000 [====================>.........] - ETA: 1s - loss: 0.2549 - accuracy: 0.9209 | |
| 35744/48000 [=====================>........] - ETA: 1s - loss: 0.2521 - accuracy: 0.9218 | |
| 36320/48000 [=====================>........] - ETA: 1s - loss: 0.2499 - accuracy: 0.9225 | |
| 36832/48000 [======================>.......] - ETA: 1s - loss: 0.2483 - accuracy: 0.9230 | |
| 37376/48000 [======================>.......] - ETA: 1s - loss: 0.2469 - accuracy: 0.9235 | |
| 37888/48000 [======================>.......] - ETA: 1s - loss: 0.2448 - accuracy: 0.9242 | |
| 38368/48000 [======================>.......] - ETA: 1s - loss: 0.2434 - accuracy: 0.9245 | |
| 38912/48000 [=======================>......] - ETA: 1s - loss: 0.2413 - accuracy: 0.9252 | |
| 39424/48000 [=======================>......] - ETA: 1s - loss: 0.2398 - accuracy: 0.9258 | |
| 39872/48000 [=======================>......] - ETA: 1s - loss: 0.2381 - accuracy: 0.9262 | |
| 40416/48000 [========================>.....] - ETA: 0s - loss: 0.2369 - accuracy: 0.9267 | |
| 40992/48000 [========================>.....] - ETA: 0s - loss: 0.2348 - accuracy: 0.9272 | |
| 41536/48000 [========================>.....] - ETA: 0s - loss: 0.2334 - accuracy: 0.9276 | |
| 41920/48000 [=========================>....] - ETA: 0s - loss: 0.2324 - accuracy: 0.9280 | |
| 42496/48000 [=========================>....] - ETA: 0s - loss: 0.2310 - accuracy: 0.9284 | |
| 43040/48000 [=========================>....] - ETA: 0s - loss: 0.2295 - accuracy: 0.9288 | |
| 43584/48000 [==========================>...] - ETA: 0s - loss: 0.2280 - accuracy: 0.9294 | |
| 44160/48000 [==========================>...] - ETA: 0s - loss: 0.2261 - accuracy: 0.9300 | |
| 44704/48000 [==========================>...] - ETA: 0s - loss: 0.2248 - accuracy: 0.9303 | |
| 45216/48000 [===========================>..] - ETA: 0s - loss: 0.2233 - accuracy: 0.9309 | |
| 45728/48000 [===========================>..] - ETA: 0s - loss: 0.2224 - accuracy: 0.9312 | |
| 46240/48000 [===========================>..] - ETA: 0s - loss: 0.2211 - accuracy: 0.9317 | |
| 46688/48000 [============================>.] - ETA: 0s - loss: 0.2200 - accuracy: 0.9320 | |
| 47232/48000 [============================>.] - ETA: 0s - loss: 0.2190 - accuracy: 0.9323 | |
| 47808/48000 [============================>.] - ETA: 0s - loss: 0.2176 - accuracy: 0.9327 | |
| Epoch 00001: val_accuracy improved from -inf to 0.97925, saving model to /workspace/_pylightnix/tmp/200428-17:54:28:846168+0300_out_af307179_s6kq1b3l/checkpoint.ckpt | |
| 48000/48000 [==============================] - 7s 138us/sample - loss: 0.2175 - accuracy: 0.9329 - val_loss: 0.0693 - val_accuracy: 0.9793 | |
| Epoch 2/6 | |
| 32/48000 [..............................] - ETA: 7s - loss: 0.1325 - accuracy: 0.9375 | |
| 544/48000 [..............................] - ETA: 4s - loss: 0.0845 - accuracy: 0.9798 | |
| 1024/48000 [..............................] - ETA: 4s - loss: 0.0952 - accuracy: 0.9746 | |
| 1536/48000 [..............................] - ETA: 4s - loss: 0.0883 - accuracy: 0.9759 | |
| 2048/48000 [>.............................] - ETA: 4s - loss: 0.0904 - accuracy: 0.9756 | |
| 2528/48000 [>.............................] - ETA: 4s - loss: 0.0885 - accuracy: 0.9747 | |
| 2912/48000 [>.............................] - ETA: 4s - loss: 0.0907 - accuracy: 0.9722 | |
| 3392/48000 [=>............................] - ETA: 4s - loss: 0.0884 - accuracy: 0.9723 | |
| 3872/48000 [=>............................] - ETA: 4s - loss: 0.0930 - accuracy: 0.9726 | |
| 4288/48000 [=>............................] - ETA: 4s - loss: 0.0942 - accuracy: 0.9727 | |
| 4768/48000 [=>............................] - ETA: 4s - loss: 0.0930 - accuracy: 0.9734 | |
| 5280/48000 [==>...........................] - ETA: 4s - loss: 0.0910 - accuracy: 0.9741 | |
| 5792/48000 [==>...........................] - ETA: 4s - loss: 0.0930 - accuracy: 0.9739 | |
| 6272/48000 [==>...........................] - ETA: 4s - loss: 0.0953 - accuracy: 0.9727 | |
| 6784/48000 [===>..........................] - ETA: 4s - loss: 0.0945 - accuracy: 0.9724 | |
| 7296/48000 [===>..........................] - ETA: 4s - loss: 0.0932 - accuracy: 0.9729 | |
| 7808/48000 [===>..........................] - ETA: 4s - loss: 0.0936 - accuracy: 0.9727 | |
| 8320/48000 [====>.........................] - ETA: 4s - loss: 0.0918 - accuracy: 0.9730 | |
| 8800/48000 [====>.........................] - ETA: 4s - loss: 0.0923 - accuracy: 0.9733 | |
| 9312/48000 [====>.........................] - ETA: 4s - loss: 0.0915 - accuracy: 0.9735 | |
| 9792/48000 [=====>........................] - ETA: 4s - loss: 0.0921 - accuracy: 0.9737 | |
| 10272/48000 [=====>........................] - ETA: 4s - loss: 0.0923 - accuracy: 0.9739 | |
| 10784/48000 [=====>........................] - ETA: 3s - loss: 0.0937 - accuracy: 0.9739 | |
| 11296/48000 [======>.......................] - ETA: 3s - loss: 0.0940 - accuracy: 0.9735 | |
| 11808/48000 [======>.......................] - ETA: 3s - loss: 0.0945 - accuracy: 0.9731 | |
| 12288/48000 [======>.......................] - ETA: 3s - loss: 0.0952 - accuracy: 0.9730 | |
| 12704/48000 [======>.......................] - ETA: 3s - loss: 0.0967 - accuracy: 0.9724 | |
| 13248/48000 [=======>......................] - ETA: 3s - loss: 0.0952 - accuracy: 0.9728 | |
| 13728/48000 [=======>......................] - ETA: 3s - loss: 0.0950 - accuracy: 0.9727 | |
| 14240/48000 [=======>......................] - ETA: 3s - loss: 0.0950 - accuracy: 0.9728 | |
| 14752/48000 [========>.....................] - ETA: 3s - loss: 0.0953 - accuracy: 0.9729 | |
| 15264/48000 [========>.....................] - ETA: 3s - loss: 0.0954 - accuracy: 0.9728 | |
| 15712/48000 [========>.....................] - ETA: 3s - loss: 0.0943 - accuracy: 0.9731 | |
| 16224/48000 [=========>....................] - ETA: 3s - loss: 0.0945 - accuracy: 0.9728 | |
| 16704/48000 [=========>....................] - ETA: 3s - loss: 0.0942 - accuracy: 0.9730 | |
| 17216/48000 [=========>....................] - ETA: 3s - loss: 0.0944 - accuracy: 0.9730 | |
| 17760/48000 [==========>...................] - ETA: 3s - loss: 0.0935 - accuracy: 0.9733 | |
| 18272/48000 [==========>...................] - ETA: 3s - loss: 0.0929 - accuracy: 0.9733 | |
| 18848/48000 [==========>...................] - ETA: 3s - loss: 0.0925 - accuracy: 0.9733 | |
| 19392/48000 [===========>..................] - ETA: 2s - loss: 0.0923 - accuracy: 0.9732 | |
| 19936/48000 [===========>..................] - ETA: 2s - loss: 0.0920 - accuracy: 0.9732 | |
| 20480/48000 [===========>..................] - ETA: 2s - loss: 0.0922 - accuracy: 0.9730 | |
| 21088/48000 [============>.................] - ETA: 2s - loss: 0.0915 - accuracy: 0.9729 | |
| 21600/48000 [============>.................] - ETA: 2s - loss: 0.0917 - accuracy: 0.9726 | |
| 22144/48000 [============>.................] - ETA: 2s - loss: 0.0913 - accuracy: 0.9727 | |
| 22720/48000 [=============>................] - ETA: 2s - loss: 0.0907 - accuracy: 0.9726 | |
| 23232/48000 [=============>................] - ETA: 2s - loss: 0.0895 - accuracy: 0.9729 | |
| 23776/48000 [=============>................] - ETA: 2s - loss: 0.0896 - accuracy: 0.9729 | |
| 24256/48000 [==============>...............] - ETA: 2s - loss: 0.0904 - accuracy: 0.9728 | |
| 24704/48000 [==============>...............] - ETA: 2s - loss: 0.0898 - accuracy: 0.9730 | |
| 25184/48000 [==============>...............] - ETA: 2s - loss: 0.0896 - accuracy: 0.9730 | |
| 25696/48000 [===============>..............] - ETA: 2s - loss: 0.0897 - accuracy: 0.9730 | |
| 26240/48000 [===============>..............] - ETA: 2s - loss: 0.0901 - accuracy: 0.9729 | |
| 26720/48000 [===============>..............] - ETA: 2s - loss: 0.0902 - accuracy: 0.9729 | |
| 27264/48000 [================>.............] - ETA: 2s - loss: 0.0900 - accuracy: 0.9729 | |
| 27680/48000 [================>.............] - ETA: 2s - loss: 0.0904 - accuracy: 0.9728 | |
| 28160/48000 [================>.............] - ETA: 2s - loss: 0.0904 - accuracy: 0.9728 | |
| 28640/48000 [================>.............] - ETA: 2s - loss: 0.0903 - accuracy: 0.9728 | |
| 29088/48000 [=================>............] - ETA: 1s - loss: 0.0899 - accuracy: 0.9728 | |
| 29568/48000 [=================>............] - ETA: 1s - loss: 0.0898 - accuracy: 0.9728 | |
| 30048/48000 [=================>............] - ETA: 1s - loss: 0.0899 - accuracy: 0.9728 | |
| 30528/48000 [==================>...........] - ETA: 1s - loss: 0.0901 - accuracy: 0.9727 | |
| 31008/48000 [==================>...........] - ETA: 1s - loss: 0.0894 - accuracy: 0.9730 | |
| 31520/48000 [==================>...........] - ETA: 1s - loss: 0.0896 - accuracy: 0.9731 | |
| 32000/48000 [===================>..........] - ETA: 1s - loss: 0.0895 - accuracy: 0.9730 | |
| 32480/48000 [===================>..........] - ETA: 1s - loss: 0.0893 - accuracy: 0.9732 | |
| 32960/48000 [===================>..........] - ETA: 1s - loss: 0.0889 - accuracy: 0.9732 | |
| 33440/48000 [===================>..........] - ETA: 1s - loss: 0.0895 - accuracy: 0.9731 | |
| 33888/48000 [====================>.........] - ETA: 1s - loss: 0.0900 - accuracy: 0.9731 | |
| 34336/48000 [====================>.........] - ETA: 1s - loss: 0.0899 - accuracy: 0.9731 | |
| 34816/48000 [====================>.........] - ETA: 1s - loss: 0.0900 - accuracy: 0.9730 | |
| 35264/48000 [=====================>........] - ETA: 1s - loss: 0.0902 - accuracy: 0.9729 | |
| 35776/48000 [=====================>........] - ETA: 1s - loss: 0.0899 - accuracy: 0.9729 | |
| 36288/48000 [=====================>........] - ETA: 1s - loss: 0.0900 - accuracy: 0.9728 | |
| 36768/48000 [=====================>........] - ETA: 1s - loss: 0.0898 - accuracy: 0.9729 | |
| 37216/48000 [======================>.......] - ETA: 1s - loss: 0.0897 - accuracy: 0.9729 | |
| 37632/48000 [======================>.......] - ETA: 1s - loss: 0.0893 - accuracy: 0.9729 | |
| 38080/48000 [======================>.......] - ETA: 1s - loss: 0.0892 - accuracy: 0.9729 | |
| 38560/48000 [=======================>......] - ETA: 0s - loss: 0.0888 - accuracy: 0.9730 | |
| 39040/48000 [=======================>......] - ETA: 0s - loss: 0.0885 - accuracy: 0.9731 | |
| 39520/48000 [=======================>......] - ETA: 0s - loss: 0.0884 - accuracy: 0.9732 | |
| 40000/48000 [========================>.....] - ETA: 0s - loss: 0.0882 - accuracy: 0.9732 | |
| 40480/48000 [========================>.....] - ETA: 0s - loss: 0.0880 - accuracy: 0.9733 | |
| 40960/48000 [========================>.....] - ETA: 0s - loss: 0.0880 - accuracy: 0.9734 | |
| 41472/48000 [========================>.....] - ETA: 0s - loss: 0.0880 - accuracy: 0.9735 | |
| 41952/48000 [=========================>....] - ETA: 0s - loss: 0.0877 - accuracy: 0.9735 | |
| 42368/48000 [=========================>....] - ETA: 0s - loss: 0.0875 - accuracy: 0.9736 | |
| 42912/48000 [=========================>....] - ETA: 0s - loss: 0.0871 - accuracy: 0.9736 | |
| 43392/48000 [==========================>...] - ETA: 0s - loss: 0.0870 - accuracy: 0.9737 | |
| 43904/48000 [==========================>...] - ETA: 0s - loss: 0.0869 - accuracy: 0.9737 | |
| 44416/48000 [==========================>...] - ETA: 0s - loss: 0.0866 - accuracy: 0.9737 | |
| 44960/48000 [===========================>..] - ETA: 0s - loss: 0.0866 - accuracy: 0.9737 | |
| 45472/48000 [===========================>..] - ETA: 0s - loss: 0.0864 - accuracy: 0.9738 | |
| 45952/48000 [===========================>..] - ETA: 0s - loss: 0.0866 - accuracy: 0.9738 | |
| 46464/48000 [============================>.] - ETA: 0s - loss: 0.0867 - accuracy: 0.9738 | |
| 47040/48000 [============================>.] - ETA: 0s - loss: 0.0865 - accuracy: 0.9739 | |
| 47584/48000 [============================>.] - ETA: 0s - loss: 0.0866 - accuracy: 0.9739 | |
| Epoch 00002: val_accuracy improved from 0.97925 to 0.98650, saving model to /workspace/_pylightnix/tmp/200428-17:54:28:846168+0300_out_af307179_s6kq1b3l/checkpoint.ckpt | |
| 48000/48000 [==============================] - 6s 120us/sample - loss: 0.0864 - accuracy: 0.9739 - val_loss: 0.0452 - val_accuracy: 0.9865 | |
| Epoch 3/6 | |
| 32/48000 [..............................] - ETA: 10s - loss: 0.0230 - accuracy: 1.0000 | |
| 544/48000 [..............................] - ETA: 5s - loss: 0.0635 - accuracy: 0.9853 | |
| 1056/48000 [..............................] - ETA: 4s - loss: 0.0795 - accuracy: 0.9744 | |
| 1504/48000 [..............................] - ETA: 5s - loss: 0.0645 - accuracy: 0.9794 | |
| 2016/48000 [>.............................] - ETA: 4s - loss: 0.0598 - accuracy: 0.9816 | |
| 2528/48000 [>.............................] - ETA: 4s - loss: 0.0622 - accuracy: 0.9822 | |
| 3040/48000 [>.............................] - ETA: 4s - loss: 0.0618 - accuracy: 0.9809 | |
| 3520/48000 [=>............................] - ETA: 4s - loss: 0.0611 - accuracy: 0.9798 | |
| 4032/48000 [=>............................] - ETA: 4s - loss: 0.0642 - accuracy: 0.9784 | |
| 4512/48000 [=>............................] - ETA: 4s - loss: 0.0667 - accuracy: 0.9776 | |
| 4992/48000 [==>...........................] - ETA: 4s - loss: 0.0639 - accuracy: 0.9786 | |
| 5504/48000 [==>...........................] - ETA: 4s - loss: 0.0622 - accuracy: 0.9789 | |
| 6048/48000 [==>...........................] - ETA: 4s - loss: 0.0633 - accuracy: 0.9788 | |
| 6528/48000 [===>..........................] - ETA: 4s - loss: 0.0623 - accuracy: 0.9790 | |
| 7040/48000 [===>..........................] - ETA: 4s - loss: 0.0623 - accuracy: 0.9788 | |
| 7552/48000 [===>..........................] - ETA: 4s - loss: 0.0605 - accuracy: 0.9795 | |
| 8064/48000 [====>.........................] - ETA: 4s - loss: 0.0605 - accuracy: 0.9797 | |
| 8576/48000 [====>.........................] - ETA: 4s - loss: 0.0605 - accuracy: 0.9798 | |
| 9024/48000 [====>.........................] - ETA: 4s - loss: 0.0619 - accuracy: 0.9797 | |
| 9504/48000 [====>.........................] - ETA: 4s - loss: 0.0610 - accuracy: 0.9799 | |
| 9984/48000 [=====>........................] - ETA: 3s - loss: 0.0609 - accuracy: 0.9801 | |
| 10496/48000 [=====>........................] - ETA: 3s - loss: 0.0599 - accuracy: 0.9805 | |
| 11040/48000 [=====>........................] - ETA: 3s - loss: 0.0608 - accuracy: 0.9800 | |
| 11520/48000 [======>.......................] - ETA: 3s - loss: 0.0613 - accuracy: 0.9798 | |
| 12032/48000 [======>.......................] - ETA: 3s - loss: 0.0614 - accuracy: 0.9796 | |
| 12544/48000 [======>.......................] - ETA: 3s - loss: 0.0608 - accuracy: 0.9798 | |
| 13056/48000 [=======>......................] - ETA: 3s - loss: 0.0609 - accuracy: 0.9797 | |
| 13536/48000 [=======>......................] - ETA: 3s - loss: 0.0620 - accuracy: 0.9795 | |
| 14048/48000 [=======>......................] - ETA: 3s - loss: 0.0621 - accuracy: 0.9795 | |
| 14560/48000 [========>.....................] - ETA: 3s - loss: 0.0631 - accuracy: 0.9794 | |
| 15072/48000 [========>.....................] - ETA: 3s - loss: 0.0632 - accuracy: 0.9794 | |
| 15584/48000 [========>.....................] - ETA: 3s - loss: 0.0633 - accuracy: 0.9792 | |
| 16096/48000 [=========>....................] - ETA: 3s - loss: 0.0638 - accuracy: 0.9791 | |
| 16608/48000 [=========>....................] - ETA: 3s - loss: 0.0634 - accuracy: 0.9792 | |
| 17120/48000 [=========>....................] - ETA: 3s - loss: 0.0644 - accuracy: 0.9789 | |
| 17632/48000 [==========>...................] - ETA: 3s - loss: 0.0644 - accuracy: 0.9788 | |
| 18112/48000 [==========>...................] - ETA: 3s - loss: 0.0642 - accuracy: 0.9790 | |
| 18592/48000 [==========>...................] - ETA: 3s - loss: 0.0636 - accuracy: 0.9794 | |
| 19104/48000 [==========>...................] - ETA: 3s - loss: 0.0634 - accuracy: 0.9795 | |
| 19648/48000 [===========>..................] - ETA: 2s - loss: 0.0629 - accuracy: 0.9797 | |
| 20160/48000 [===========>..................] - ETA: 2s - loss: 0.0631 - accuracy: 0.9798 | |
| 20608/48000 [===========>..................] - ETA: 2s - loss: 0.0636 - accuracy: 0.9794 | |
| 21088/48000 [============>.................] - ETA: 2s - loss: 0.0632 - accuracy: 0.9794 | |
| 21536/48000 [============>.................] - ETA: 2s - loss: 0.0640 - accuracy: 0.9792 | |
| 22016/48000 [============>.................] - ETA: 2s - loss: 0.0633 - accuracy: 0.9794 | |
| 22528/48000 [=============>................] - ETA: 2s - loss: 0.0636 - accuracy: 0.9793 | |
| 23040/48000 [=============>................] - ETA: 2s - loss: 0.0640 - accuracy: 0.9793 | |
| 23616/48000 [=============>................] - ETA: 2s - loss: 0.0639 - accuracy: 0.9794 | |
| 24160/48000 [==============>...............] - ETA: 2s - loss: 0.0636 - accuracy: 0.9794 | |
| 24544/48000 [==============>...............] - ETA: 2s - loss: 0.0635 - accuracy: 0.9794 | |
| 25056/48000 [==============>...............] - ETA: 2s - loss: 0.0633 - accuracy: 0.9794 | |
| 25472/48000 [==============>...............] - ETA: 2s - loss: 0.0634 - accuracy: 0.9793 | |
| 25920/48000 [===============>..............] - ETA: 2s - loss: 0.0639 - accuracy: 0.9791 | |
| 26496/48000 [===============>..............] - ETA: 2s - loss: 0.0636 - accuracy: 0.9791 | |
| 27072/48000 [===============>..............] - ETA: 2s - loss: 0.0630 - accuracy: 0.9794 | |
| 27648/48000 [================>.............] - ETA: 2s - loss: 0.0629 - accuracy: 0.9793 | |
| 28192/48000 [================>.............] - ETA: 2s - loss: 0.0636 - accuracy: 0.9791 | |
| 28768/48000 [================>.............] - ETA: 1s - loss: 0.0634 - accuracy: 0.9793 | |
| 29344/48000 [=================>............] - ETA: 1s - loss: 0.0641 - accuracy: 0.9793 | |
| 29888/48000 [=================>............] - ETA: 1s - loss: 0.0642 - accuracy: 0.9794 | |
| 30368/48000 [=================>............] - ETA: 1s - loss: 0.0643 - accuracy: 0.9793 | |
| 30880/48000 [==================>...........] - ETA: 1s - loss: 0.0642 - accuracy: 0.9794 | |
| 31392/48000 [==================>...........] - ETA: 1s - loss: 0.0642 - accuracy: 0.9794 | |
| 31904/48000 [==================>...........] - ETA: 1s - loss: 0.0639 - accuracy: 0.9795 | |
| 32480/48000 [===================>..........] - ETA: 1s - loss: 0.0638 - accuracy: 0.9796 | |
| 33024/48000 [===================>..........] - ETA: 1s - loss: 0.0642 - accuracy: 0.9795 | |
| 33600/48000 [====================>.........] - ETA: 1s - loss: 0.0644 - accuracy: 0.9796 | |
| 34144/48000 [====================>.........] - ETA: 1s - loss: 0.0642 - accuracy: 0.9796 | |
| 34720/48000 [====================>.........] - ETA: 1s - loss: 0.0640 - accuracy: 0.9796 | |
| 35168/48000 [====================>.........] - ETA: 1s - loss: 0.0639 - accuracy: 0.9796 | |
| 35552/48000 [=====================>........] - ETA: 1s - loss: 0.0639 - accuracy: 0.9795 | |
| 36000/48000 [=====================>........] - ETA: 1s - loss: 0.0646 - accuracy: 0.9793 | |
| 36544/48000 [=====================>........] - ETA: 1s - loss: 0.0649 - accuracy: 0.9793 | |
| 37088/48000 [======================>.......] - ETA: 1s - loss: 0.0649 - accuracy: 0.9794 | |
| 37504/48000 [======================>.......] - ETA: 1s - loss: 0.0647 - accuracy: 0.9795 | |
| 37888/48000 [======================>.......] - ETA: 1s - loss: 0.0648 - accuracy: 0.9796 | |
| 38432/48000 [=======================>......] - ETA: 0s - loss: 0.0647 - accuracy: 0.9796 | |
| 38912/48000 [=======================>......] - ETA: 0s - loss: 0.0647 - accuracy: 0.9797 | |
| 39392/48000 [=======================>......] - ETA: 0s - loss: 0.0651 - accuracy: 0.9797 | |
| 39808/48000 [=======================>......] - ETA: 0s - loss: 0.0657 - accuracy: 0.9795 | |
| 40192/48000 [========================>.....] - ETA: 0s - loss: 0.0659 - accuracy: 0.9794 | |
| 40576/48000 [========================>.....] - ETA: 0s - loss: 0.0658 - accuracy: 0.9794 | |
| 40992/48000 [========================>.....] - ETA: 0s - loss: 0.0659 - accuracy: 0.9795 | |
| 41536/48000 [========================>.....] - ETA: 0s - loss: 0.0665 - accuracy: 0.9793 | |
| 42048/48000 [=========================>....] - ETA: 0s - loss: 0.0666 - accuracy: 0.9793 | |
| 42464/48000 [=========================>....] - ETA: 0s - loss: 0.0667 - accuracy: 0.9792 | |
| 42880/48000 [=========================>....] - ETA: 0s - loss: 0.0665 - accuracy: 0.9793 | |
| 43264/48000 [==========================>...] - ETA: 0s - loss: 0.0662 - accuracy: 0.9794 | |
| 43648/48000 [==========================>...] - ETA: 0s - loss: 0.0658 - accuracy: 0.9795 | |
| 44032/48000 [==========================>...] - ETA: 0s - loss: 0.0656 - accuracy: 0.9795 | |
| 44416/48000 [==========================>...] - ETA: 0s - loss: 0.0654 - accuracy: 0.9796 | |
| 44864/48000 [===========================>..] - ETA: 0s - loss: 0.0652 - accuracy: 0.9796 | |
| 45376/48000 [===========================>..] - ETA: 0s - loss: 0.0655 - accuracy: 0.9796 | |
| 45824/48000 [===========================>..] - ETA: 0s - loss: 0.0653 - accuracy: 0.9797 | |
| 46272/48000 [===========================>..] - ETA: 0s - loss: 0.0651 - accuracy: 0.9798 | |
| 46784/48000 [============================>.] - ETA: 0s - loss: 0.0650 - accuracy: 0.9799 | |
| 47232/48000 [============================>.] - ETA: 0s - loss: 0.0650 - accuracy: 0.9799 | |
| 47648/48000 [============================>.] - ETA: 0s - loss: 0.0650 - accuracy: 0.9798 | |
| Epoch 00003: val_accuracy improved from 0.98650 to 0.98933, saving model to /workspace/_pylightnix/tmp/200428-17:54:28:846168+0300_out_af307179_s6kq1b3l/checkpoint.ckpt | |
| 48000/48000 [==============================] - 6s 125us/sample - loss: 0.0650 - accuracy: 0.9799 - val_loss: 0.0385 - val_accuracy: 0.9893 | |
| Epoch 4/6 | |
| 32/48000 [..............................] - ETA: 8s - loss: 0.0679 - accuracy: 0.9688 | |
| 480/48000 [..............................] - ETA: 5s - loss: 0.0393 - accuracy: 0.9833 | |
| 992/48000 [..............................] - ETA: 5s - loss: 0.0318 - accuracy: 0.9869 | |
| 1504/48000 [..............................] - ETA: 4s - loss: 0.0402 - accuracy: 0.9867 | |
| 2048/48000 [>.............................] - ETA: 4s - loss: 0.0418 - accuracy: 0.9873 | |
| 2592/48000 [>.............................] - ETA: 4s - loss: 0.0489 - accuracy: 0.9861 | |
| 3136/48000 [>.............................] - ETA: 4s - loss: 0.0473 - accuracy: 0.9866 | |
| 3712/48000 [=>............................] - ETA: 4s - loss: 0.0480 - accuracy: 0.9863 | |
| 4256/48000 [=>............................] - ETA: 4s - loss: 0.0448 - accuracy: 0.9871 | |
| 4832/48000 [==>...........................] - ETA: 4s - loss: 0.0459 - accuracy: 0.9863 | |
| 5408/48000 [==>...........................] - ETA: 4s - loss: 0.0460 - accuracy: 0.9861 | |
| 5984/48000 [==>...........................] - ETA: 3s - loss: 0.0455 - accuracy: 0.9860 | |
| 6560/48000 [===>..........................] - ETA: 3s - loss: 0.0468 - accuracy: 0.9854 | |
| 7104/48000 [===>..........................] - ETA: 3s - loss: 0.0469 - accuracy: 0.9856 | |
| 7616/48000 [===>..........................] - ETA: 3s - loss: 0.0457 - accuracy: 0.9861 | |
| 8128/48000 [====>.........................] - ETA: 3s - loss: 0.0460 - accuracy: 0.9859 | |
| 8608/48000 [====>.........................] - ETA: 3s - loss: 0.0468 - accuracy: 0.9855 | |
| 9056/48000 [====>.........................] - ETA: 3s - loss: 0.0464 - accuracy: 0.9855 | |
| 9472/48000 [====>.........................] - ETA: 3s - loss: 0.0462 - accuracy: 0.9852 | |
| 9888/48000 [=====>........................] - ETA: 3s - loss: 0.0471 - accuracy: 0.9849 | |
| 10240/48000 [=====>........................] - ETA: 3s - loss: 0.0499 - accuracy: 0.9846 | |
| 10592/48000 [=====>........................] - ETA: 3s - loss: 0.0493 - accuracy: 0.9847 | |
| 11072/48000 [=====>........................] - ETA: 3s - loss: 0.0498 - accuracy: 0.9847 | |
| 11456/48000 [======>.......................] - ETA: 3s - loss: 0.0503 - accuracy: 0.9845 | |
| 11776/48000 [======>.......................] - ETA: 3s - loss: 0.0503 - accuracy: 0.9845 | |
| 12160/48000 [======>.......................] - ETA: 3s - loss: 0.0499 - accuracy: 0.9846 | |
| 12672/48000 [======>.......................] - ETA: 3s - loss: 0.0498 - accuracy: 0.9845 | |
| 13248/48000 [=======>......................] - ETA: 3s - loss: 0.0500 - accuracy: 0.9845 | |
| 13824/48000 [=======>......................] - ETA: 3s - loss: 0.0509 - accuracy: 0.9844 | |
| 14400/48000 [========>.....................] - ETA: 3s - loss: 0.0509 - accuracy: 0.9844 | |
| 14912/48000 [========>.....................] - ETA: 3s - loss: 0.0514 - accuracy: 0.9842 | |
| 15424/48000 [========>.....................] - ETA: 3s - loss: 0.0524 - accuracy: 0.9839 | |
| 16000/48000 [=========>....................] - ETA: 3s - loss: 0.0525 - accuracy: 0.9837 | |
| 16576/48000 [=========>....................] - ETA: 3s - loss: 0.0523 - accuracy: 0.9837 | |
| 17152/48000 [=========>....................] - ETA: 3s - loss: 0.0518 - accuracy: 0.9839 | |
| 17664/48000 [==========>...................] - ETA: 3s - loss: 0.0518 - accuracy: 0.9841 | |
| 18144/48000 [==========>...................] - ETA: 3s - loss: 0.0524 - accuracy: 0.9841 | |
| 18624/48000 [==========>...................] - ETA: 3s - loss: 0.0526 - accuracy: 0.9839 | |
| 18976/48000 [==========>...................] - ETA: 3s - loss: 0.0527 - accuracy: 0.9837 | |
| 19328/48000 [===========>..................] - ETA: 2s - loss: 0.0527 - accuracy: 0.9837 | |
| 19712/48000 [===========>..................] - ETA: 2s - loss: 0.0528 - accuracy: 0.9836 | |
| 20224/48000 [===========>..................] - ETA: 2s - loss: 0.0531 - accuracy: 0.9836 | |
| 20736/48000 [===========>..................] - ETA: 2s - loss: 0.0528 - accuracy: 0.9836 | |
| 21312/48000 [============>.................] - ETA: 2s - loss: 0.0529 - accuracy: 0.9836 | |
| 21824/48000 [============>.................] - ETA: 2s - loss: 0.0527 - accuracy: 0.9837 | |
| 22272/48000 [============>.................] - ETA: 2s - loss: 0.0520 - accuracy: 0.9839 | |
| 22720/48000 [=============>................] - ETA: 2s - loss: 0.0520 - accuracy: 0.9840 | |
| 23264/48000 [=============>................] - ETA: 2s - loss: 0.0516 - accuracy: 0.9841 | |
| 23776/48000 [=============>................] - ETA: 2s - loss: 0.0521 - accuracy: 0.9840 | |
| 24320/48000 [==============>...............] - ETA: 2s - loss: 0.0518 - accuracy: 0.9841 | |
| 24832/48000 [==============>...............] - ETA: 2s - loss: 0.0519 - accuracy: 0.9841 | |
| 25280/48000 [==============>...............] - ETA: 2s - loss: 0.0521 - accuracy: 0.9840 | |
| 25856/48000 [===============>..............] - ETA: 2s - loss: 0.0517 - accuracy: 0.9841 | |
| 26400/48000 [===============>..............] - ETA: 2s - loss: 0.0514 - accuracy: 0.9841 | |
| 26976/48000 [===============>..............] - ETA: 2s - loss: 0.0518 - accuracy: 0.9841 | |
| 27552/48000 [================>.............] - ETA: 2s - loss: 0.0523 - accuracy: 0.9841 | |
| 28096/48000 [================>.............] - ETA: 2s - loss: 0.0520 - accuracy: 0.9841 | |
| 28608/48000 [================>.............] - ETA: 2s - loss: 0.0527 - accuracy: 0.9841 | |
| 29088/48000 [=================>............] - ETA: 1s - loss: 0.0529 - accuracy: 0.9840 | |
| 29536/48000 [=================>............] - ETA: 1s - loss: 0.0528 - accuracy: 0.9841 | |
| 29920/48000 [=================>............] - ETA: 1s - loss: 0.0529 - accuracy: 0.9841 | |
| 30304/48000 [=================>............] - ETA: 1s - loss: 0.0530 - accuracy: 0.9839 | |
| 30784/48000 [==================>...........] - ETA: 1s - loss: 0.0525 - accuracy: 0.9841 | |
| 31232/48000 [==================>...........] - ETA: 1s - loss: 0.0525 - accuracy: 0.9841 | |
| 31584/48000 [==================>...........] - ETA: 1s - loss: 0.0523 - accuracy: 0.9841 | |
| 31904/48000 [==================>...........] - ETA: 1s - loss: 0.0520 - accuracy: 0.9842 | |
| 32256/48000 [===================>..........] - ETA: 1s - loss: 0.0519 - accuracy: 0.9842 | |
| 32640/48000 [===================>..........] - ETA: 1s - loss: 0.0518 - accuracy: 0.9843 | |
| 33024/48000 [===================>..........] - ETA: 1s - loss: 0.0517 - accuracy: 0.9842 | |
| 33536/48000 [===================>..........] - ETA: 1s - loss: 0.0513 - accuracy: 0.9842 | |
| 33984/48000 [====================>.........] - ETA: 1s - loss: 0.0512 - accuracy: 0.9843 | |
| 34464/48000 [====================>.........] - ETA: 1s - loss: 0.0510 - accuracy: 0.9844 | |
| 35008/48000 [====================>.........] - ETA: 1s - loss: 0.0510 - accuracy: 0.9844 | |
| 35584/48000 [=====================>........] - ETA: 1s - loss: 0.0515 - accuracy: 0.9842 | |
| 36128/48000 [=====================>........] - ETA: 1s - loss: 0.0514 - accuracy: 0.9843 | |
| 36672/48000 [=====================>........] - ETA: 1s - loss: 0.0514 - accuracy: 0.9843 | |
| 37248/48000 [======================>.......] - ETA: 1s - loss: 0.0516 - accuracy: 0.9843 | |
| 37760/48000 [======================>.......] - ETA: 1s - loss: 0.0515 - accuracy: 0.9844 | |
| 38336/48000 [======================>.......] - ETA: 1s - loss: 0.0515 - accuracy: 0.9843 | |
| 38848/48000 [=======================>......] - ETA: 0s - loss: 0.0517 - accuracy: 0.9841 | |
| 39424/48000 [=======================>......] - ETA: 0s - loss: 0.0521 - accuracy: 0.9840 | |
| 40000/48000 [========================>.....] - ETA: 0s - loss: 0.0522 - accuracy: 0.9839 | |
| 40576/48000 [========================>.....] - ETA: 0s - loss: 0.0526 - accuracy: 0.9837 | |
| 40992/48000 [========================>.....] - ETA: 0s - loss: 0.0525 - accuracy: 0.9838 | |
| 41344/48000 [========================>.....] - ETA: 0s - loss: 0.0524 - accuracy: 0.9837 | |
| 41728/48000 [=========================>....] - ETA: 0s - loss: 0.0525 - accuracy: 0.9837 | |
| 42240/48000 [=========================>....] - ETA: 0s - loss: 0.0522 - accuracy: 0.9837 | |
| 42688/48000 [=========================>....] - ETA: 0s - loss: 0.0522 - accuracy: 0.9837 | |
| 43200/48000 [==========================>...] - ETA: 0s - loss: 0.0523 - accuracy: 0.9836 | |
| 43648/48000 [==========================>...] - ETA: 0s - loss: 0.0525 - accuracy: 0.9836 | |
| 44096/48000 [==========================>...] - ETA: 0s - loss: 0.0524 - accuracy: 0.9837 | |
| 44544/48000 [==========================>...] - ETA: 0s - loss: 0.0524 - accuracy: 0.9837 | |
| 45056/48000 [===========================>..] - ETA: 0s - loss: 0.0521 - accuracy: 0.9838 | |
| 45472/48000 [===========================>..] - ETA: 0s - loss: 0.0520 - accuracy: 0.9839 | |
| 45984/48000 [===========================>..] - ETA: 0s - loss: 0.0518 - accuracy: 0.9839 | |
| 46496/48000 [============================>.] - ETA: 0s - loss: 0.0518 - accuracy: 0.9838 | |
| 46976/48000 [============================>.] - ETA: 0s - loss: 0.0516 - accuracy: 0.9839 | |
| 47488/48000 [============================>.] - ETA: 0s - loss: 0.0517 - accuracy: 0.9837 | |
| 47872/48000 [============================>.] - ETA: 0s - loss: 0.0516 - accuracy: 0.9837 | |
| Epoch 00004: val_accuracy improved from 0.98933 to 0.98958, saving model to /workspace/_pylightnix/tmp/200428-17:54:28:846168+0300_out_af307179_s6kq1b3l/checkpoint.ckpt | |
| 48000/48000 [==============================] - 6s 122us/sample - loss: 0.0515 - accuracy: 0.9837 - val_loss: 0.0389 - val_accuracy: 0.9896 | |
| Epoch 5/6 | |
| 32/48000 [..............................] - ETA: 11s - loss: 0.0129 - accuracy: 1.0000 | |
| 480/48000 [..............................] - ETA: 5s - loss: 0.0255 - accuracy: 0.9937 | |
| 928/48000 [..............................] - ETA: 5s - loss: 0.0329 - accuracy: 0.9892 | |
| 1376/48000 [..............................] - ETA: 5s - loss: 0.0350 - accuracy: 0.9884 | |
| 1760/48000 [>.............................] - ETA: 5s - loss: 0.0351 - accuracy: 0.9886 | |
| 2208/48000 [>.............................] - ETA: 5s - loss: 0.0359 - accuracy: 0.9882 | |
| 2624/48000 [>.............................] - ETA: 5s - loss: 0.0396 - accuracy: 0.9878 | |
| 2976/48000 [>.............................] - ETA: 5s - loss: 0.0416 - accuracy: 0.9869 | |
| 3456/48000 [=>............................] - ETA: 5s - loss: 0.0455 - accuracy: 0.9867 | |
| 3840/48000 [=>............................] - ETA: 5s - loss: 0.0427 - accuracy: 0.9878 | |
| 4320/48000 [=>............................] - ETA: 5s - loss: 0.0432 - accuracy: 0.9880 | |
| 4832/48000 [==>...........................] - ETA: 5s - loss: 0.0439 - accuracy: 0.9878 | |
| 5344/48000 [==>...........................] - ETA: 5s - loss: 0.0425 - accuracy: 0.9884 | |
| 5696/48000 [==>...........................] - ETA: 5s - loss: 0.0407 - accuracy: 0.9888 | |
| 6080/48000 [==>...........................] - ETA: 5s - loss: 0.0401 - accuracy: 0.9887 | |
| 6432/48000 [===>..........................] - ETA: 5s - loss: 0.0402 - accuracy: 0.9887 | |
| 6752/48000 [===>..........................] - ETA: 5s - loss: 0.0413 - accuracy: 0.9880 | |
| 7104/48000 [===>..........................] - ETA: 5s - loss: 0.0410 - accuracy: 0.9880 | |
| 7552/48000 [===>..........................] - ETA: 5s - loss: 0.0405 - accuracy: 0.9882 | |
| 7968/48000 [===>..........................] - ETA: 4s - loss: 0.0405 - accuracy: 0.9881 | |
| 8512/48000 [====>.........................] - ETA: 4s - loss: 0.0406 - accuracy: 0.9880 | |
| 9088/48000 [====>.........................] - ETA: 4s - loss: 0.0390 - accuracy: 0.9884 | |
| 9632/48000 [=====>........................] - ETA: 4s - loss: 0.0392 - accuracy: 0.9886 | |
| 10144/48000 [=====>........................] - ETA: 4s - loss: 0.0408 - accuracy: 0.9880 | |
| 10688/48000 [=====>........................] - ETA: 4s - loss: 0.0405 - accuracy: 0.9881 | |
| 11264/48000 [======>.......................] - ETA: 4s - loss: 0.0412 - accuracy: 0.9879 | |
| 11840/48000 [======>.......................] - ETA: 4s - loss: 0.0412 - accuracy: 0.9878 | |
| 12416/48000 [======>.......................] - ETA: 4s - loss: 0.0419 - accuracy: 0.9878 | |
| 12992/48000 [=======>......................] - ETA: 3s - loss: 0.0420 - accuracy: 0.9878 | |
| 13568/48000 [=======>......................] - ETA: 3s - loss: 0.0428 - accuracy: 0.9875 | |
| 14048/48000 [=======>......................] - ETA: 3s - loss: 0.0432 - accuracy: 0.9873 | |
| 14592/48000 [========>.....................] - ETA: 3s - loss: 0.0438 - accuracy: 0.9871 | |
| 15104/48000 [========>.....................] - ETA: 3s - loss: 0.0435 - accuracy: 0.9871 | |
| 15680/48000 [========>.....................] - ETA: 3s - loss: 0.0438 - accuracy: 0.9869 | |
| 16256/48000 [=========>....................] - ETA: 3s - loss: 0.0439 - accuracy: 0.9868 | |
| 16736/48000 [=========>....................] - ETA: 3s - loss: 0.0456 - accuracy: 0.9866 | |
| 17280/48000 [=========>....................] - ETA: 3s - loss: 0.0455 - accuracy: 0.9866 | |
| 17824/48000 [==========>...................] - ETA: 3s - loss: 0.0458 - accuracy: 0.9865 | |
| 18368/48000 [==========>...................] - ETA: 3s - loss: 0.0454 - accuracy: 0.9864 | |
| 18912/48000 [==========>...................] - ETA: 3s - loss: 0.0452 - accuracy: 0.9865 | |
| 19456/48000 [===========>..................] - ETA: 3s - loss: 0.0459 - accuracy: 0.9862 | |
| 20000/48000 [===========>..................] - ETA: 2s - loss: 0.0454 - accuracy: 0.9864 | |
| 20576/48000 [===========>..................] - ETA: 2s - loss: 0.0450 - accuracy: 0.9864 | |
| 21120/48000 [============>.................] - ETA: 2s - loss: 0.0450 - accuracy: 0.9865 | |
| 21696/48000 [============>.................] - ETA: 2s - loss: 0.0451 - accuracy: 0.9864 | |
| 22272/48000 [============>.................] - ETA: 2s - loss: 0.0451 - accuracy: 0.9864 | |
| 22880/48000 [=============>................] - ETA: 2s - loss: 0.0453 - accuracy: 0.9863 | |
| 23264/48000 [=============>................] - ETA: 2s - loss: 0.0457 - accuracy: 0.9860 | |
| 23616/48000 [=============>................] - ETA: 2s - loss: 0.0458 - accuracy: 0.9860 | |
| 23968/48000 [=============>................] - ETA: 2s - loss: 0.0461 - accuracy: 0.9858 | |
| 24352/48000 [==============>...............] - ETA: 2s - loss: 0.0459 - accuracy: 0.9858 | |
| 24800/48000 [==============>...............] - ETA: 2s - loss: 0.0460 - accuracy: 0.9857 | |
| 25184/48000 [==============>...............] - ETA: 2s - loss: 0.0459 - accuracy: 0.9858 | |
| 25536/48000 [==============>...............] - ETA: 2s - loss: 0.0461 - accuracy: 0.9858 | |
| 25824/48000 [===============>..............] - ETA: 2s - loss: 0.0458 - accuracy: 0.9859 | |
| 26144/48000 [===============>..............] - ETA: 2s - loss: 0.0455 - accuracy: 0.9860 | |
| 26624/48000 [===============>..............] - ETA: 2s - loss: 0.0454 - accuracy: 0.9860 | |
| 27104/48000 [===============>..............] - ETA: 2s - loss: 0.0456 - accuracy: 0.9859 | |
| 27584/48000 [================>.............] - ETA: 2s - loss: 0.0462 - accuracy: 0.9858 | |
| 28096/48000 [================>.............] - ETA: 2s - loss: 0.0457 - accuracy: 0.9859 | |
| 28608/48000 [================>.............] - ETA: 2s - loss: 0.0456 - accuracy: 0.9859 | |
| 29120/48000 [=================>............] - ETA: 2s - loss: 0.0451 - accuracy: 0.9861 | |
| 29600/48000 [=================>............] - ETA: 1s - loss: 0.0453 - accuracy: 0.9860 | |
| 29984/48000 [=================>............] - ETA: 1s - loss: 0.0450 - accuracy: 0.9861 | |
| 30368/48000 [=================>............] - ETA: 1s - loss: 0.0456 - accuracy: 0.9859 | |
| 30848/48000 [==================>...........] - ETA: 1s - loss: 0.0458 - accuracy: 0.9859 | |
| 31360/48000 [==================>...........] - ETA: 1s - loss: 0.0458 - accuracy: 0.9859 | |
| 31904/48000 [==================>...........] - ETA: 1s - loss: 0.0456 - accuracy: 0.9859 | |
| 32448/48000 [===================>..........] - ETA: 1s - loss: 0.0456 - accuracy: 0.9859 | |
| 32992/48000 [===================>..........] - ETA: 1s - loss: 0.0454 - accuracy: 0.9860 | |
| 33568/48000 [===================>..........] - ETA: 1s - loss: 0.0453 - accuracy: 0.9859 | |
| 34112/48000 [====================>.........] - ETA: 1s - loss: 0.0451 - accuracy: 0.9860 | |
| 34592/48000 [====================>.........] - ETA: 1s - loss: 0.0451 - accuracy: 0.9860 | |
| 35040/48000 [====================>.........] - ETA: 1s - loss: 0.0448 - accuracy: 0.9861 | |
| 35584/48000 [=====================>........] - ETA: 1s - loss: 0.0448 - accuracy: 0.9860 | |
| 36032/48000 [=====================>........] - ETA: 1s - loss: 0.0448 - accuracy: 0.9860 | |
| 36544/48000 [=====================>........] - ETA: 1s - loss: 0.0446 - accuracy: 0.9860 | |
| 37056/48000 [======================>.......] - ETA: 1s - loss: 0.0451 - accuracy: 0.9860 | |
| 37632/48000 [======================>.......] - ETA: 1s - loss: 0.0452 - accuracy: 0.9860 | |
| 38240/48000 [======================>.......] - ETA: 1s - loss: 0.0457 - accuracy: 0.9859 | |
| 38784/48000 [=======================>......] - ETA: 0s - loss: 0.0461 - accuracy: 0.9859 | |
| 39360/48000 [=======================>......] - ETA: 0s - loss: 0.0460 - accuracy: 0.9859 | |
| 39904/48000 [=======================>......] - ETA: 0s - loss: 0.0459 - accuracy: 0.9859 | |
| 40448/48000 [========================>.....] - ETA: 0s - loss: 0.0461 - accuracy: 0.9858 | |
| 40960/48000 [========================>.....] - ETA: 0s - loss: 0.0460 - accuracy: 0.9858 | |
| 41536/48000 [========================>.....] - ETA: 0s - loss: 0.0459 - accuracy: 0.9857 | |
| 42080/48000 [=========================>....] - ETA: 0s - loss: 0.0457 - accuracy: 0.9857 | |
| 42624/48000 [=========================>....] - ETA: 0s - loss: 0.0457 - accuracy: 0.9857 | |
| 43200/48000 [==========================>...] - ETA: 0s - loss: 0.0455 - accuracy: 0.9858 | |
| 43776/48000 [==========================>...] - ETA: 0s - loss: 0.0455 - accuracy: 0.9858 | |
| 44320/48000 [==========================>...] - ETA: 0s - loss: 0.0454 - accuracy: 0.9858 | |
| 44832/48000 [===========================>..] - ETA: 0s - loss: 0.0453 - accuracy: 0.9858 | |
| 45248/48000 [===========================>..] - ETA: 0s - loss: 0.0453 - accuracy: 0.9859 | |
| 45760/48000 [===========================>..] - ETA: 0s - loss: 0.0454 - accuracy: 0.9859 | |
| 46336/48000 [===========================>..] - ETA: 0s - loss: 0.0457 - accuracy: 0.9858 | |
| 46816/48000 [============================>.] - ETA: 0s - loss: 0.0456 - accuracy: 0.9858 | |
| 47360/48000 [============================>.] - ETA: 0s - loss: 0.0456 - accuracy: 0.9859 | |
| 47840/48000 [============================>.] - ETA: 0s - loss: 0.0460 - accuracy: 0.9858 | |
| Epoch 00005: val_accuracy improved from 0.98958 to 0.98992, saving model to /workspace/_pylightnix/tmp/200428-17:54:28:846168+0300_out_af307179_s6kq1b3l/checkpoint.ckpt | |
| 48000/48000 [==============================] - 6s 121us/sample - loss: 0.0459 - accuracy: 0.9858 - val_loss: 0.0344 - val_accuracy: 0.9899 | |
| Epoch 6/6 | |
| 32/48000 [..............................] - ETA: 11s - loss: 2.3236e-04 - accuracy: 1.0000 | |
| 512/48000 [..............................] - ETA: 5s - loss: 0.0340 - accuracy: 0.9883 | |
| 928/48000 [..............................] - ETA: 5s - loss: 0.0370 - accuracy: 0.9871 | |
| 1280/48000 [..............................] - ETA: 5s - loss: 0.0360 - accuracy: 0.9875 | |
| 1664/48000 [>.............................] - ETA: 6s - loss: 0.0321 - accuracy: 0.9892 | |
| 2080/48000 [>.............................] - ETA: 5s - loss: 0.0324 - accuracy: 0.9889 | |
| 2432/48000 [>.............................] - ETA: 5s - loss: 0.0346 - accuracy: 0.9868 | |
| 2944/48000 [>.............................] - ETA: 5s - loss: 0.0308 - accuracy: 0.9885 | |
| 3488/48000 [=>............................] - ETA: 5s - loss: 0.0333 - accuracy: 0.9882 | |
| 4000/48000 [=>............................] - ETA: 5s - loss: 0.0344 - accuracy: 0.9890 | |
| 4544/48000 [=>............................] - ETA: 5s - loss: 0.0333 - accuracy: 0.9890 | |
| 5024/48000 [==>...........................] - ETA: 4s - loss: 0.0333 - accuracy: 0.9891 | |
| 5568/48000 [==>...........................] - ETA: 4s - loss: 0.0326 - accuracy: 0.9894 | |
| 6080/48000 [==>...........................] - ETA: 4s - loss: 0.0337 - accuracy: 0.9890 | |
| 6592/48000 [===>..........................] - ETA: 4s - loss: 0.0335 - accuracy: 0.9894 | |
| 6976/48000 [===>..........................] - ETA: 4s - loss: 0.0327 - accuracy: 0.9897 | |
| 7360/48000 [===>..........................] - ETA: 4s - loss: 0.0319 - accuracy: 0.9898 | |
| 7744/48000 [===>..........................] - ETA: 4s - loss: 0.0329 - accuracy: 0.9895 | |
| 8128/48000 [====>.........................] - ETA: 4s - loss: 0.0323 - accuracy: 0.9898 | |
| 8512/48000 [====>.........................] - ETA: 4s - loss: 0.0325 - accuracy: 0.9895 | |
| 8928/48000 [====>.........................] - ETA: 4s - loss: 0.0325 - accuracy: 0.9895 | |
| 9312/48000 [====>.........................] - ETA: 4s - loss: 0.0329 - accuracy: 0.9893 | |
| 9728/48000 [=====>........................] - ETA: 4s - loss: 0.0334 - accuracy: 0.9891 | |
| 10176/48000 [=====>........................] - ETA: 4s - loss: 0.0338 - accuracy: 0.9887 | |
| 10688/48000 [=====>........................] - ETA: 4s - loss: 0.0341 - accuracy: 0.9886 | |
| 11168/48000 [=====>........................] - ETA: 4s - loss: 0.0337 - accuracy: 0.9888 | |
| 11680/48000 [======>.......................] - ETA: 4s - loss: 0.0339 - accuracy: 0.9887 | |
| 12160/48000 [======>.......................] - ETA: 4s - loss: 0.0347 - accuracy: 0.9887 | |
| 12608/48000 [======>.......................] - ETA: 4s - loss: 0.0345 - accuracy: 0.9887 | |
| 12960/48000 [=======>......................] - ETA: 4s - loss: 0.0346 - accuracy: 0.9886 | |
| 13312/48000 [=======>......................] - ETA: 4s - loss: 0.0353 - accuracy: 0.9885 | |
| 13664/48000 [=======>......................] - ETA: 4s - loss: 0.0358 - accuracy: 0.9883 | |
| 14080/48000 [=======>......................] - ETA: 4s - loss: 0.0356 - accuracy: 0.9883 | |
| 14656/48000 [========>.....................] - ETA: 3s - loss: 0.0357 - accuracy: 0.9881 | |
| 15200/48000 [========>.....................] - ETA: 3s - loss: 0.0353 - accuracy: 0.9882 | |
| 15776/48000 [========>.....................] - ETA: 3s - loss: 0.0356 - accuracy: 0.9880 | |
| 16352/48000 [=========>....................] - ETA: 3s - loss: 0.0350 - accuracy: 0.9882 | |
| 16896/48000 [=========>....................] - ETA: 3s - loss: 0.0364 - accuracy: 0.9876 | |
| 17440/48000 [=========>....................] - ETA: 3s - loss: 0.0371 - accuracy: 0.9873 | |
| 17952/48000 [==========>...................] - ETA: 3s - loss: 0.0371 - accuracy: 0.9872 | |
| 18496/48000 [==========>...................] - ETA: 3s - loss: 0.0379 - accuracy: 0.9869 | |
| 19040/48000 [==========>...................] - ETA: 3s - loss: 0.0382 - accuracy: 0.9868 | |
| 19584/48000 [===========>..................] - ETA: 3s - loss: 0.0384 - accuracy: 0.9867 | |
| 20160/48000 [===========>..................] - ETA: 3s - loss: 0.0385 - accuracy: 0.9868 | |
| 20736/48000 [===========>..................] - ETA: 3s - loss: 0.0391 - accuracy: 0.9865 | |
| 21248/48000 [============>.................] - ETA: 2s - loss: 0.0391 - accuracy: 0.9866 | |
| 21728/48000 [============>.................] - ETA: 2s - loss: 0.0391 - accuracy: 0.9866 | |
| 22208/48000 [============>.................] - ETA: 2s - loss: 0.0393 - accuracy: 0.9864 | |
| 22624/48000 [=============>................] - ETA: 2s - loss: 0.0395 - accuracy: 0.9864 | |
| 23040/48000 [=============>................] - ETA: 2s - loss: 0.0402 - accuracy: 0.9862 | |
| 23456/48000 [=============>................] - ETA: 2s - loss: 0.0399 - accuracy: 0.9863 | |
| 24000/48000 [==============>...............] - ETA: 2s - loss: 0.0396 - accuracy: 0.9864 | |
| 24480/48000 [==============>...............] - ETA: 2s - loss: 0.0400 - accuracy: 0.9862 | |
| 25024/48000 [==============>...............] - ETA: 2s - loss: 0.0401 - accuracy: 0.9862 | |
| 25440/48000 [==============>...............] - ETA: 2s - loss: 0.0402 - accuracy: 0.9862 | |
| 25824/48000 [===============>..............] - ETA: 2s - loss: 0.0399 - accuracy: 0.9863 | |
| 26304/48000 [===============>..............] - ETA: 2s - loss: 0.0404 - accuracy: 0.9862 | |
| 26784/48000 [===============>..............] - ETA: 2s - loss: 0.0405 - accuracy: 0.9862 | |
| 27328/48000 [================>.............] - ETA: 2s - loss: 0.0405 - accuracy: 0.9861 | |
| 27840/48000 [================>.............] - ETA: 2s - loss: 0.0403 - accuracy: 0.9862 | |
| 28352/48000 [================>.............] - ETA: 2s - loss: 0.0408 - accuracy: 0.9860 | |
| 28832/48000 [=================>............] - ETA: 2s - loss: 0.0406 - accuracy: 0.9861 | |
| 29376/48000 [=================>............] - ETA: 2s - loss: 0.0403 - accuracy: 0.9861 | |
| 29856/48000 [=================>............] - ETA: 1s - loss: 0.0399 - accuracy: 0.9863 | |
| 30240/48000 [=================>............] - ETA: 1s - loss: 0.0403 - accuracy: 0.9863 | |
| 30592/48000 [==================>...........] - ETA: 1s - loss: 0.0402 - accuracy: 0.9863 | |
| 30944/48000 [==================>...........] - ETA: 1s - loss: 0.0400 - accuracy: 0.9864 | |
| 31296/48000 [==================>...........] - ETA: 1s - loss: 0.0401 - accuracy: 0.9864 | |
| 31648/48000 [==================>...........] - ETA: 1s - loss: 0.0400 - accuracy: 0.9865 | |
| 32128/48000 [===================>..........] - ETA: 1s - loss: 0.0398 - accuracy: 0.9865 | |
| 32608/48000 [===================>..........] - ETA: 1s - loss: 0.0399 - accuracy: 0.9865 | |
| 33152/48000 [===================>..........] - ETA: 1s - loss: 0.0399 - accuracy: 0.9865 | |
| 33696/48000 [====================>.........] - ETA: 1s - loss: 0.0399 - accuracy: 0.9865 | |
| 34240/48000 [====================>.........] - ETA: 1s - loss: 0.0402 - accuracy: 0.9863 | |
| 34656/48000 [====================>.........] - ETA: 1s - loss: 0.0405 - accuracy: 0.9864 | |
| 35168/48000 [====================>.........] - ETA: 1s - loss: 0.0408 - accuracy: 0.9864 | |
| 35712/48000 [=====================>........] - ETA: 1s - loss: 0.0404 - accuracy: 0.9865 | |
| 36256/48000 [=====================>........] - ETA: 1s - loss: 0.0407 - accuracy: 0.9864 | |
| 36800/48000 [======================>.......] - ETA: 1s - loss: 0.0405 - accuracy: 0.9865 | |
| 37312/48000 [======================>.......] - ETA: 1s - loss: 0.0403 - accuracy: 0.9866 | |
| 37856/48000 [======================>.......] - ETA: 1s - loss: 0.0403 - accuracy: 0.9865 | |
| 38368/48000 [======================>.......] - ETA: 1s - loss: 0.0401 - accuracy: 0.9866 | |
| 38880/48000 [=======================>......] - ETA: 0s - loss: 0.0408 - accuracy: 0.9864 | |
| 39392/48000 [=======================>......] - ETA: 0s - loss: 0.0408 - accuracy: 0.9863 | |
| 39936/48000 [=======================>......] - ETA: 0s - loss: 0.0409 - accuracy: 0.9864 | |
| 40416/48000 [========================>.....] - ETA: 0s - loss: 0.0407 - accuracy: 0.9864 | |
| 40928/48000 [========================>.....] - ETA: 0s - loss: 0.0405 - accuracy: 0.9865 | |
| 41408/48000 [========================>.....] - ETA: 0s - loss: 0.0406 - accuracy: 0.9865 | |
| 41856/48000 [=========================>....] - ETA: 0s - loss: 0.0406 - accuracy: 0.9866 | |
| 42368/48000 [=========================>....] - ETA: 0s - loss: 0.0405 - accuracy: 0.9866 | |
| 42912/48000 [=========================>....] - ETA: 0s - loss: 0.0404 - accuracy: 0.9867 | |
| 43424/48000 [==========================>...] - ETA: 0s - loss: 0.0403 - accuracy: 0.9867 | |
| 43968/48000 [==========================>...] - ETA: 0s - loss: 0.0404 - accuracy: 0.9867 | |
| 44352/48000 [==========================>...] - ETA: 0s - loss: 0.0402 - accuracy: 0.9868 | |
| 44736/48000 [==========================>...] - ETA: 0s - loss: 0.0401 - accuracy: 0.9869 | |
| 45088/48000 [===========================>..] - ETA: 0s - loss: 0.0400 - accuracy: 0.9869 | |
| 45536/48000 [===========================>..] - ETA: 0s - loss: 0.0398 - accuracy: 0.9870 | |
| 45920/48000 [===========================>..] - ETA: 0s - loss: 0.0396 - accuracy: 0.9871 | |
| 46400/48000 [============================>.] - ETA: 0s - loss: 0.0394 - accuracy: 0.9871 | |
| 46848/48000 [============================>.] - ETA: 0s - loss: 0.0394 - accuracy: 0.9871 | |
| 47424/48000 [============================>.] - ETA: 0s - loss: 0.0395 - accuracy: 0.9871 | |
| Epoch 00006: val_accuracy improved from 0.98992 to 0.99117, saving model to /workspace/_pylightnix/tmp/200428-17:54:28:846168+0300_out_af307179_s6kq1b3l/checkpoint.ckpt | |
| 48000/48000 [==============================] - 6s 125us/sample - loss: 0.0396 - accuracy: 0.9870 - val_loss: 0.0358 - val_accuracy: 0.9912</code></pre> | |
| <pre class="stderr"><code>2020-04-28 17:54:29.068670: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 | |
| 2020-04-28 17:54:29.086580: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties: | |
| pciBusID: 0000:65:00.0 name: GeForce GTX 1080 Ti computeCapability: 6.1 | |
| coreClock: 1.6705GHz coreCount: 28 deviceMemorySize: 10.91GiB deviceMemoryBandwidth: 451.17GiB/s | |
| 2020-04-28 17:54:29.086798: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 | |
| 2020-04-28 17:54:29.087843: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 | |
| 2020-04-28 17:54:29.088788: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 | |
| 2020-04-28 17:54:29.089063: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 | |
| 2020-04-28 17:54:29.090293: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 | |
| 2020-04-28 17:54:29.091240: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 | |
| 2020-04-28 17:54:29.094081: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 | |
| 2020-04-28 17:54:29.095224: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0 | |
| 2020-04-28 17:54:29.115775: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3300000000 Hz | |
| 2020-04-28 17:54:29.117609: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x42b0100 initialized for platform Host (this does not guarantee that XLA will be used). Devices: | |
| 2020-04-28 17:54:29.117654: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version | |
| 2020-04-28 17:54:29.200583: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x42a6cf0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: | |
| 2020-04-28 17:54:29.200654: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce GTX 1080 Ti, Compute Capability 6.1 | |
| 2020-04-28 17:54:29.201866: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties: | |
| pciBusID: 0000:65:00.0 name: GeForce GTX 1080 Ti computeCapability: 6.1 | |
| coreClock: 1.6705GHz coreCount: 28 deviceMemorySize: 10.91GiB deviceMemoryBandwidth: 451.17GiB/s | |
| 2020-04-28 17:54:29.201934: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 | |
| 2020-04-28 17:54:29.201959: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 | |
| 2020-04-28 17:54:29.201980: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 | |
| 2020-04-28 17:54:29.202009: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 | |
| 2020-04-28 17:54:29.202030: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 | |
| 2020-04-28 17:54:29.202053: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 | |
| 2020-04-28 17:54:29.202075: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 | |
| 2020-04-28 17:54:29.203998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0 | |
| 2020-04-28 17:54:29.204060: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 | |
| 2020-04-28 17:54:29.206160: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix: | |
| 2020-04-28 17:54:29.206187: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0 | |
| 2020-04-28 17:54:29.206202: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N | |
| 2020-04-28 17:54:29.208244: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9807 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:65:00.0, compute capability: 6.1) | |
| 2020-04-28 17:54:30.069657: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 | |
| 2020-04-28 17:54:30.194051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 | |
| 2020-04-28 17:54:30.849585: I tensorflow/core/profiler/lib/profiler_session.cc:225] Profiler session started. | |
| 2020-04-28 17:54:30.849637: I tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1259] Profiler found 1 GPUs | |
| 2020-04-28 17:54:30.849875: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcupti.so.10.0'; dlerror: libcupti.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/nvidia/lib:/usr/local/nvidia/lib64 | |
| 2020-04-28 17:54:30.849894: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1307] function cupti_interface_->Subscribe( &subscriber_, (CUpti_CallbackFunc)ApiCallback, this)failed with error CUPTI could not be loaded or symbol could not be found. | |
| 2020-04-28 17:54:30.849903: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1346] function cupti_interface_->ActivityRegisterCallbacks( AllocCuptiActivityBuffer, FreeCuptiActivityBuffer)failed with error CUPTI could not be loaded or symbol could not be found. | |
| 2020-04-28 17:54:30.856060: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1329] function cupti_interface_->EnableCallback( 0 , subscriber_, CUPTI_CB_DOMAIN_DRIVER_API, cbid)failed with error CUPTI could not be loaded or symbol could not be found. | |
| 2020-04-28 17:54:30.856104: I tensorflow/core/profiler/internal/gpu/device_tracer.cc:88] GpuTracer has collected 0 callback api events and 0 activity events.</code></pre> | |
| </body> | |
| </html> |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment