Created
January 14, 2020 06:37
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tweetNet train log
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| [step: 0] Accuracy: 14.88315%, Best: 14.88315% | |
| [step: 200] Accuracy: 37.39237%, Best: 37.39237% | |
| [step: 400] Accuracy: 39.85240%, Best: 39.85240% | |
| [step: 600] Accuracy: 55.35055%, Best: 55.35055% | |
| [step: 800] Accuracy: 71.83272%, Best: 71.83272% | |
| [step: 1000] Accuracy: 75.27675%, Best: 75.27675% | |
| [step: 1200] Accuracy: 84.74784%, Best: 84.74784% | |
| [step: 1400] Accuracy: 82.65682%, Best: 84.74784% | |
| [step: 1600] Accuracy: 87.82288%, Best: 87.82288% | |
| [step: 1800] Accuracy: 88.43789%, Best: 88.43789% | |
| [step: 2000] Accuracy: 88.80689%, Best: 88.80689% | |
| [step: 2200] Accuracy: 83.39483%, Best: 88.80689% | |
| [step: 2400] Accuracy: 93.72694%, Best: 93.72694% | |
| [step: 2600] Accuracy: 91.02091%, Best: 93.72694% | |
| [step: 2800] Accuracy: 87.20787%, Best: 93.72694% | |
| [step: 3000] Accuracy: 90.03690%, Best: 93.72694% | |
| [step: 3200] Accuracy: 94.09594%, Best: 94.09594% | |
| [step: 3400] Accuracy: 92.37393%, Best: 94.09594% | |
| [step: 3600] Accuracy: 92.98893%, Best: 94.09594% | |
| [step: 3800] Accuracy: 91.75892%, Best: 94.09594% | |
| [step: 4000] Accuracy: 94.34195%, Best: 94.34195% | |
| [step: 4200] Accuracy: 92.86593%, Best: 94.34195% | |
| [step: 4400] Accuracy: 93.48093%, Best: 94.34195% | |
| [step: 4600] Accuracy: 91.63592%, Best: 94.34195% | |
| [step: 4800] Accuracy: 91.63592%, Best: 94.34195% | |
| [step: 5000] Accuracy: 94.09594%, Best: 94.34195% | |
| [step: 5200] Accuracy: 93.23493%, Best: 94.34195% | |
| [step: 5400] Accuracy: 93.84994%, Best: 94.34195% | |
| [step: 5600] Accuracy: 93.35793%, Best: 94.34195% | |
| [step: 5800] Accuracy: 93.60394%, Best: 94.34195% | |
| [step: 6000] Accuracy: 92.86593%, Best: 94.34195% | |
| [step: 6200] Accuracy: 93.23493%, Best: 94.34195% | |
| [step: 6400] Accuracy: 90.15990%, Best: 94.34195% | |
| [step: 6600] Accuracy: 89.05289%, Best: 94.34195% | |
| [step: 6800] Accuracy: 91.38991%, Best: 94.34195% | |
| [step: 7000] Accuracy: 94.58795%, Best: 94.58795% | |
| [step: 7200] Accuracy: 85.60886%, Best: 94.58795% | |
| [step: 7400] Accuracy: 92.37393%, Best: 94.58795% | |
| [step: 7600] Accuracy: 91.51291%, Best: 94.58795% | |
| [step: 7800] Accuracy: 92.74293%, Best: 94.58795% | |
| [step: 8000] Accuracy: 94.21894%, Best: 94.58795% | |
| [step: 8200] Accuracy: 93.84994%, Best: 94.58795% | |
| [step: 8400] Accuracy: 93.84994%, Best: 94.58795% | |
| [step: 8600] Accuracy: 94.09594%, Best: 94.58795% | |
| [step: 8800] Accuracy: 93.11193%, Best: 94.58795% | |
| [step: 9000] Accuracy: 93.60394%, Best: 94.58795% | |
| [step: 9200] Accuracy: 93.60394%, Best: 94.58795% | |
| [step: 9400] Accuracy: 93.84994%, Best: 94.58795% | |
| [step: 9600] Accuracy: 93.11193%, Best: 94.58795% | |
| [step: 9800] Accuracy: 91.02091%, Best: 94.58795% | |
| [step: 10000] Accuracy: 93.23493%, Best: 94.58795% |
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