LSTM
Training iter #1: Batch Loss = 1.467979, Accuracy = 0.3059999942779541
Training iter #20: Batch Loss = 1.155874, Accuracy = 0.3400000035762787
Training iter #40: Batch Loss = 1.119148, Accuracy = 0.4169999957084656
Training iter #60: Batch Loss = 1.099285, Accuracy = 0.49399998784065247
Training iter #90: Batch Loss = 0.991692, Accuracy = 0.527999997138977
Training iter #140: Batch Loss = 0.940209, Accuracy = 0.5320000052452087
Training iter #190: Batch Loss = 0.907819, Accuracy = 0.5609999895095825
Training iter #220: Batch Loss = 0.869303, Accuracy = 0.578000009059906
Training iter #410: Batch Loss = 0.847943, Accuracy = 0.5979999899864197
Training iter #490: Batch Loss = 0.852090, Accuracy = 0.6129999756813049
Training iter #540: Batch Loss = 0.843135, Accuracy = 0.6389999985694885
Training iter #1490: Batch Loss = 0.836091, Accuracy = 0.6489999890327454
Training iter #1750: Batch Loss = 0.812885, Accuracy = 0.6510000228881836
Training iter #1970: Batch Loss = 0.791033, Accuracy = 0.6679999828338623
Training iter #2110: Batch Loss = 0.739782, Accuracy = 0.6800000071525574
Training iter #2470: Batch Loss = 0.714706, Accuracy = 0.6909999847412109
Training iter #2670: Batch Loss = 0.694483, Accuracy = 0.6919999718666077
Training iter #5290: Batch Loss = 0.681658, Accuracy = 0.7070000171661377
Training iter #5820: Batch Loss = 0.676098, Accuracy = 0.7200000286102295
Training iter #6130: Batch Loss = 0.642826, Accuracy = 0.734000027179718
Training iter #31760: Batch Loss = 0.575368, Accuracy = 0.7400000095367432
Training iter #71890: Batch Loss = 0.577792, Accuracy = 0.7570000290870667
Training iter #72230: Batch Loss = 0.552322, Accuracy = 0.7670000195503235
Training iter #87790: Batch Loss = 0.551816, Accuracy = 0.7789999842643738
Training iter #89180: Batch Loss = 0.542968, Accuracy = 0.7829999923706055
Training iter #90970: Batch Loss = 0.532735, Accuracy = 0.7990000247955322
Training iter #121200: Batch Loss = 0.525607, Accuracy = 0.8040000200271606
Training iter #122180: Batch Loss = 0.516407, Accuracy = 0.8109999895095825
Training iter #149140: Batch Loss = 0.528955, Accuracy = 0.8230000138282776
Training iter #186710: Batch Loss = 0.515277, Accuracy = 0.8349999785423279
Training iter #186960: Batch Loss = 0.512902, Accuracy = 0.8450000286102295
Training iter #188530: Batch Loss = 0.470322, Accuracy = 0.8510000109672546
Training iter #190900: Batch Loss = 0.467161, Accuracy = 0.86473999829229711
Iter: 700, Train Loss: 0.11, Train Acc: 95.31%, Val Loss: 0.36, Test Acc: 90.28%, Time: 2:52:12 *
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