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results.log
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=================================
6/27/2018 0:17:40
SEED: 900
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 40 | BATCH SIZE 4000
RESULTS: LOSS:0.4939669615427653 | ACCURACY:0.7740000003178914
=================================
6/27/2018 0:20:35
SEED: 800
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 40 | BATCH SIZE 4000
RESULTS: LOSS:0.5247865921656291 | ACCURACY:0.7573333330154419
=================================
6/27/2018 0:22:44
SEED: 673
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 40 | BATCH SIZE 4000
RESULTS: LOSS:0.5817099941571554 | ACCURACY:0.7660000003178914
=================================
6/27/2018 0:23:51
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 60 | BATCH SIZE 4000
RESULTS: LOSS:0.49984818013509114 | ACCURACY:0.7493333331743877
=================================
6/27/2018 0:31:37
SEED: 500
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 60 | BATCH SIZE 4000
RESULTS: LOSS:0.4715809990564982 | ACCURACY:0.7706666666666667
=================================
6/27/2018 0:33:42
SEED: 500
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 40 | BATCH SIZE 4000
RESULTS: LOSS:0.5497414876619975 | ACCURACY:0.7746666661898295
=================================
6/27/2018 0:35:30
SEED: 500
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 60 | BATCH SIZE 4000
RESULTS: LOSS:0.482585237344106 | ACCURACY:0.764666666507721
=================================
6/27/2018 0:38:48
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 50 | BATCH SIZE 4000
RESULTS: LOSS:0.4657580803235372 | ACCURACY:0.7953333328564962
=================================
6/27/2018 0:48:30
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 50 | BATCH SIZE 4000
RESULTS: LOSS:0.5221682963371277 | ACCURACY:0.7966666669845581
=================================
6/27/2018 1:0:55
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 50 | BATCH SIZE 4000
RESULTS: LOSS:0.46440774138768515 | ACCURACY:0.7926666661898295
=================================
6/27/2018 1:3:45
SEED: 600
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['1', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 50 | BATCH SIZE 4000
RESULTS: LOSS:0.5870801531473796 | ACCURACY:0.7719999996821085
Comment:
Feed Forward Network
I was playing around with big batch sizes and many epochs
Highest accuracy achieved was 79.6% at 6/27/2018 0:48:30
Accuracy Range : [77 - 79%]
=================================
6/27/2018 10:25:22
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['4', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 50 | BATCH SIZE 4000
RESULTS: LOSS:0.5866669438680013 | ACCURACY:0.6870000004768372
=================================
6/27/2018 10:48:6
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['4', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 3 | BATCH SIZE 128
RESULTS: LOSS:0.5858962899843851 | ACCURACY:0.6981666668256123
=================================
6/27/2018 11:25:15
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['4', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 3 | BATCH SIZE 128
RESULTS: LOSS:0.5768061073621115 | ACCURACY:0.7001666671435038
=================================
6/27/2018 11:25:50
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['4', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 6 | BATCH SIZE 128
RESULTS: LOSS:0.6957056617736816 | ACCURACY:0.6696666671435039
=================================
6/27/2018 11:26:22
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['4', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 2 | BATCH SIZE 128
RESULTS: LOSS:0.5984242766698201 | ACCURACY:0.7069999998410543
=================================
6/27/2018 15:17:54
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['4', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 40 | BATCH SIZE 4000
RESULTS: LOSS:0.6068108436266582 | ACCURACY:0.6931666668256123
=================================
6/27/2018 15:20:58
SEED: 400
Layer1: ['16', 'relu', 10000]
Layer2: ['16', 'relu']
Layer3: ['4', 'sigmoid']
Generalizers:
Compilation: ['rmsprop', 'binary_crossentropy', 'accuracy']
Training: EPOCHS 50 | BATCH SIZE 2000
RESULTS: LOSS:0.6479647378921509 | ACCURACY:0.6700000004768372
=================================================================
7/2/2018 14:57:22
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_1 (Dense) (None, 16) 160016
_________________________________________________________________
dense_2 (Dense) (None, 16) 272
_________________________________________________________________
dense_3 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.5884620765050252, 0.7790000004768372]
Images:
FF/7-2-14-57_CM0.png
FF/7-2-14-57_CM1.png
FF/7-2-14-57_CM2.png
FF/7-2-14-57_CM3.png
FF/7-2-14-57_CM4.png
=================================================================
7/2/2018 15:49:27
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
embedding_2 (Embedding) (None, None, 50) 500000
_________________________________________________________________
lstm_2 (LSTM) (None, 32) 10624
_________________________________________________________________
dense_2 (Dense) (None, 4) 132
=================================================================
Total params: 510,756
Trainable params: 10,756
Non-trainable params: 500,000
_________________________________________________________________
Results: [0.5715791218953254, 0.702884615396842]
Images:
LSTM/7-2-15-49_CM0.png
LSTM/7-2-15-49_CM4.png
LSTM/7-2-15-49_CM2.png
LSTM/7-2-15-49_CM3.png
LSTM/7-2-15-49_CM4.png
=================================================================
7/3/2018 9:37:15
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_1 (Dense) (None, 16) 160016
_________________________________________________________________
dense_2 (Dense) (None, 16) 272
_________________________________________________________________
dense_3 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.5971340266141024, 0.7710011508851661]
Images:
FF/7-3-9-37_CM0.png
FF/7-3-9-37_CM1.png
FF/7-3-9-37_CM2.png
FF/7-3-9-37_CM3.png
FF/7-3-9-37_CM4.png
=================================================================
7/3/2018 11:3:42
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_12 (Dense) (None, 16) 160016
_________________________________________________________________
dense_13 (Dense) (None, 16) 272
_________________________________________________________________
dense_14 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6488769471439585, 0.764384349690208]
Images:
FF/7-3-11-3_CM0.png
FF/7-3-11-3_CM1.png
FF/7-3-11-3_CM2.png
FF/7-3-11-3_CM3.png
FF/7-3-11-3_CM4.png
=================================================================
7/3/2018 11:30:3
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_15 (Dense) (None, 16) 160016
_________________________________________________________________
dense_16 (Dense) (None, 16) 272
_________________________________________________________________
dense_17 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6461068205235331, 0.7597813578140338]
Images:
FF/7-3-11-30_CM0.png
FF/7-3-11-30_CM1.png
FF/7-3-11-30_CM2.png
FF/7-3-11-30_CM3.png
FF/7-3-11-30_CM4.png
=================================================================
7/3/2018 11:33:20
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_18 (Dense) (None, 16) 160016
_________________________________________________________________
dense_19 (Dense) (None, 16) 272
_________________________________________________________________
dense_20 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6906448000456851, 0.7615074797933203]
Images:
FF/7-3-11-33_CM0.png
FF/7-3-11-33_CM1.png
FF/7-3-11-33_CM2.png
FF/7-3-11-33_CM3.png
FF/7-3-11-33_CM4.png
=================================================================
7/3/2018 11:34:34
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_21 (Dense) (None, 16) 160016
_________________________________________________________________
dense_22 (Dense) (None, 16) 272
_________________________________________________________________
dense_23 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6829645161798826, 0.7646720368239356]
Images:
FF/7-3-11-34_CM0.png
FF/7-3-11-34_CM1.png
FF/7-3-11-34_CM2.png
FF/7-3-11-34_CM3.png
FF/7-3-11-34_CM4.png
=================================================================
7/5/2018 11:22:39
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_1 (Dense) (None, 16) 160016
_________________________________________________________________
dense_2 (Dense) (None, 16) 272
_________________________________________________________________
dense_3 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6732935054941473, 0.7617951667212781]
Images:
FF/7-5-11-22_CM0.png
FF/7-5-11-22_CM1.png
FF/7-5-11-22_CM2.png
FF/7-5-11-22_CM3.png
FF/7-5-11-22_CM4.png
=================================================================
7/5/2018 11:33:17
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_4 (Dense) (None, 16) 160016
_________________________________________________________________
dense_5 (Dense) (None, 16) 272
_________________________________________________________________
dense_6 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6898301270532115, 0.7606444187350871]
Images:
FF/7-5-11-33_CM0.png
FF/7-5-11-33_CM1.png
FF/7-5-11-33_CM2.png
FF/7-5-11-33_CM3.png
FF/7-5-11-33_CM4.png
=================================================================
7/6/2018 11:15:27
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_1 (Dense) (None, 16) 160016
_________________________________________________________________
dense_2 (Dense) (None, 16) 272
_________________________________________________________________
dense_3 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6598332810401917, 0.762]
Images:
FF/7-6-11-15_CM0.png
FF/7-6-11-15_CM1.png
FF/7-6-11-15_CM2.png
FF/7-6-11-15_CM3.png
FF/7-6-11-15_CM4.png
=================================================================
7/6/2018 11:23:17
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_4 (Dense) (None, 16) 160016
_________________________________________________________________
dense_5 (Dense) (None, 16) 272
_________________________________________________________________
dense_6 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.6850013946910722, 0.7514384351199186]
Images:
FF/7-6-11-23_CM0.png
FF/7-6-11-23_CM1.png
FF/7-6-11-23_CM2.png
FF/7-6-11-23_CM3.png
FF/7-6-11-23_CM4.png
=================================================================
7/6/2018 11:26:36
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_7 (Dense) (None, 16) 160016
_________________________________________________________________
dense_8 (Dense) (None, 16) 272
_________________________________________________________________
dense_9 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.8142701418956761, 0.7474108168938903]
Images:
FF/7-6-11-26_CM0.png
FF/7-6-11-26_CM1.png
FF/7-6-11-26_CM2.png
FF/7-6-11-26_CM3.png
FF/7-6-11-26_CM4.png
=================================================================
7/6/2018 11:27:28
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_10 (Dense) (None, 16) 160016
_________________________________________________________________
dense_11 (Dense) (None, 16) 272
_________________________________________________________________
dense_12 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.7209200431068693, 0.7361910240971178]
Images:
FF/7-6-11-27_CM0.png
FF/7-6-11-27_CM1.png
FF/7-6-11-27_CM2.png
FF/7-6-11-27_CM3.png
FF/7-6-11-27_CM4.png
=================================================================
7/6/2018 11:28:6
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_13 (Dense) (None, 16) 160016
_________________________________________________________________
dense_14 (Dense) (None, 16) 272
_________________________________________________________________
dense_15 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.695764156424958, 0.7571921748451039]
Images:
FF/7-6-11-28_CM0.png
FF/7-6-11-28_CM1.png
FF/7-6-11-28_CM2.png
FF/7-6-11-28_CM3.png
FF/7-6-11-28_CM4.png
=================================================================
7/6/2018 12:1:7
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_25 (Dense) (None, 16) 160016
_________________________________________________________________
dense_26 (Dense) (None, 16) 272
_________________________________________________________________
dense_27 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.5870739877978458, 0.7686996547070142]
Images:
FF/7-6-12-1_CM0.png
FF/7-6-12-1_CM1.png
FF/7-6-12-1_CM2.png
FF/7-6-12-1_CM3.png
FF/7-6-12-1_CM4.png
=================================================================
7/9/2018 1:23:11
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
embedding_1 (Embedding) (None, None, 50) 500000
_________________________________________________________________
lstm_1 (LSTM) (None, 32) 10624
_________________________________________________________________
dense_1 (Dense) (None, 4) 132
=================================================================
Total params: 510,756
Trainable params: 10,756
Non-trainable params: 500,000
_________________________________________________________________
Results: [0.6826294231414795, 0.5608125]
Images:
LSTM/7-9-1-23_CM0.png
LSTM/7-9-1-23_CM4.png
LSTM/7-9-1-23_CM2.png
LSTM/7-9-1-23_CM3.png
LSTM/7-9-1-23_CM4.png
=================================================================
7/16/2018 15:29:58
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_60 (Dense) (None, 16) 160016
_________________________________________________________________
dense_61 (Dense) (None, 16) 272
_________________________________________________________________
dense_62 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.5682332816123963, 0.7473333330154419]
Images:
FF/7-16-15-29_CM0.png
FF/7-16-15-29_CM1.png
FF/7-16-15-29_CM2.png
FF/7-16-15-29_CM3.png
FF/7-16-15-29_CM4.png
=================================================================
7/16/2018 15:50:9
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_13 (Dense) (None, 16) 160016
_________________________________________________________________
dense_14 (Dense) (None, 16) 272
_________________________________________________________________
dense_15 (Dense) (None, 4) 68
=================================================================
Total params: 160,356
Trainable params: 160,356
Non-trainable params: 0
_________________________________________________________________
Results: [0.609076922041363, 0.7597813578140338]
Images:
FF/7-16-15-50_CM0.png
FF/7-16-15-50_CM1.png
FF/7-16-15-50_CM2.png
FF/7-16-15-50_CM3.png
FF/7-16-15-50_CM4.png