## How to classify Flowers (iris data) using a keras deep learning model

def Snippet_337(): 

    print()
    print(format('How to classify Flowers (iris data) using a keras deep learning model','*^88'))

    import warnings
    warnings.filterwarnings("ignore")

    # load libraries
    from sklearn import datasets
    from sklearn.model_selection import train_test_split
    from keras.utils import np_utils
    from keras.models import Sequential
    from keras.layers.core import Dense, Activation
    from keras.optimizers import SGD, RMSprop, Adam
    from keras.regularizers import l2
    import matplotlib.pyplot as plt    

    import time
    start_time = time.time()

    # set parameters
    NB_CLASSES = 3
    VALIDATION_SPLIT = 0.25
    VERBOSE = 1
    BATCH_SIZE = 128

    # load Dataset    
    iris = datasets.load_iris()

    X = iris.data
    y = iris.target

    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)  

    # -----------------------------------------------
    # convert class vectors to binary class matrices
    # -----------------------------------------------
    Y_train = np_utils.to_categorical(y_train, NB_CLASSES)
    Y_test  = np_utils.to_categorical(y_test, NB_CLASSES)

    # ---------------------------------------------------------------------
    # setup a deep learning model
    # ---------------------------------------------------------------------
    accuracy = []
    for OPTIMIZER in [SGD(), RMSprop(), Adam()]: 
        for NB_EPOCH in [5,10,20]:
            for N_Units_in_Multiple_Layers in [64, 128, 256]:
                model = Sequential()
                model.add(Dense(units = N_Units_in_Multiple_Layers, input_shape=(X_train.shape[1],), 
                                kernel_regularizer=l2())) 
                model.add(Activation('relu'))
                model.add(Dense(units = N_Units_in_Multiple_Layers, kernel_regularizer=l2()))
                model.add(Activation('relu'))
                model.add(Dense(units = NB_CLASSES))
                model.add(Activation('softmax'))

                model.summary()
                
                model.compile(loss='categorical_crossentropy', optimizer=OPTIMIZER, metrics=['accuracy'])
                
                model.fit(X_train, Y_train, batch_size=BATCH_SIZE, epochs=NB_EPOCH,
                          verbose=VERBOSE, validation_split=VALIDATION_SPLIT)
                
                score = model.evaluate(X_test, Y_test, verbose=VERBOSE)
                
                print()
                print('Optimizers: ', OPTIMIZER)
                print('Epoch Sizes: ', NB_EPOCH)            
                print('Neurons or Units: ', N_Units_in_Multiple_Layers)            
                print("Test score:", score[0])
                print('Test accuracy:', score[1])
                
                accuracy.append(score[1])
                print()

    print(accuracy)
    y = accuracy; N = len(y); x = range(N); width = 1./1.5;
    plt.ylim(0.0,1.2)
    plt.bar(x,y,width); plt.show()

    print()
    print("Execution Time %s seconds: " % (time.time() - start_time))    

Snippet_337()    

*********How to classify Flowers (iris data) using a keras deep learning model**********
Model: "sequential_28"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_82 (Dense)             (None, 64)                320       
_________________________________________________________________
activation_82 (Activation)   (None, 64)                0         
_________________________________________________________________
dense_83 (Dense)             (None, 64)                4160      
_________________________________________________________________
activation_83 (Activation)   (None, 64)                0         
_________________________________________________________________
dense_84 (Dense)             (None, 3)                 195       
_________________________________________________________________
activation_84 (Activation)   (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 1ms/step - loss: 2.0551 - accuracy: 0.1923 - val_loss: 1.9237 - val_accuracy: 0.4074
Epoch 2/5
78/78 [==============================] - 0s 37us/step - loss: 1.9781 - accuracy: 0.2949 - val_loss: 1.8766 - val_accuracy: 0.4074
Epoch 3/5
78/78 [==============================] - 0s 32us/step - loss: 1.9157 - accuracy: 0.3205 - val_loss: 1.8419 - val_accuracy: 0.4074
Epoch 4/5
78/78 [==============================] - 0s 43us/step - loss: 1.8669 - accuracy: 0.3205 - val_loss: 1.8143 - val_accuracy: 0.4074
Epoch 5/5
78/78 [==============================] - 0s 69us/step - loss: 1.8287 - accuracy: 0.3205 - val_loss: 1.7914 - val_accuracy: 0.4074
45/45 [==============================] - 0s 63us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  5
Neurons or Units:  64
Test score: 1.8051131963729858
Test accuracy: 0.35555556416511536

Model: "sequential_29"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_85 (Dense)             (None, 128)               640       
_________________________________________________________________
activation_85 (Activation)   (None, 128)               0         
_________________________________________________________________
dense_86 (Dense)             (None, 128)               16512     
_________________________________________________________________
activation_86 (Activation)   (None, 128)               0         
_________________________________________________________________
dense_87 (Dense)             (None, 3)                 387       
_________________________________________________________________
activation_87 (Activation)   (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 1ms/step - loss: 3.2778 - accuracy: 0.3077 - val_loss: 2.7424 - val_accuracy: 0.3333
Epoch 2/5
78/78 [==============================] - 0s 46us/step - loss: 2.8163 - accuracy: 0.3077 - val_loss: 2.5422 - val_accuracy: 0.3333
Epoch 3/5
78/78 [==============================] - 0s 47us/step - loss: 2.5878 - accuracy: 0.3077 - val_loss: 2.4509 - val_accuracy: 0.3333
Epoch 4/5
78/78 [==============================] - 0s 52us/step - loss: 2.4764 - accuracy: 0.3077 - val_loss: 2.4064 - val_accuracy: 0.6667
Epoch 5/5
78/78 [==============================] - 0s 54us/step - loss: 2.4168 - accuracy: 0.5385 - val_loss: 2.3808 - val_accuracy: 0.4074
45/45 [==============================] - 0s 45us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  5
Neurons or Units:  128
Test score: 2.3723203447129992
Test accuracy: 0.5777778029441833

Model: "sequential_30"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_88 (Dense)             (None, 256)               1280      
_________________________________________________________________
activation_88 (Activation)   (None, 256)               0         
_________________________________________________________________
dense_89 (Dense)             (None, 256)               65792     
_________________________________________________________________
activation_89 (Activation)   (None, 256)               0         
_________________________________________________________________
dense_90 (Dense)             (None, 3)                 771       
_________________________________________________________________
activation_90 (Activation)   (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 2ms/step - loss: 3.8108 - accuracy: 0.0385 - val_loss: 3.8015 - val_accuracy: 0.2593
Epoch 2/5
78/78 [==============================] - 0s 93us/step - loss: 3.7545 - accuracy: 0.3718 - val_loss: 3.7627 - val_accuracy: 0.2593
Epoch 3/5
78/78 [==============================] - 0s 48us/step - loss: 3.7196 - accuracy: 0.3718 - val_loss: 3.7339 - val_accuracy: 0.2593
Epoch 4/5
78/78 [==============================] - 0s 44us/step - loss: 3.6944 - accuracy: 0.3718 - val_loss: 3.7105 - val_accuracy: 0.2593
Epoch 5/5
78/78 [==============================] - 0s 68us/step - loss: 3.6740 - accuracy: 0.3718 - val_loss: 3.6906 - val_accuracy: 0.2593
45/45 [==============================] - 0s 74us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  5
Neurons or Units:  256
Test score: 3.6750347985161675
Test accuracy: 0.31111112236976624

Model: "sequential_31"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_91 (Dense)             (None, 64)                320       
_________________________________________________________________
activation_91 (Activation)   (None, 64)                0         
_________________________________________________________________
dense_92 (Dense)             (None, 64)                4160      
_________________________________________________________________
activation_92 (Activation)   (None, 64)                0         
_________________________________________________________________
dense_93 (Dense)             (None, 3)                 195       
_________________________________________________________________
activation_93 (Activation)   (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 2.4398 - accuracy: 0.3077 - val_loss: 2.0908 - val_accuracy: 0.3333
Epoch 2/10
78/78 [==============================] - 0s 33us/step - loss: 2.0885 - accuracy: 0.3077 - val_loss: 1.9447 - val_accuracy: 0.3333
Epoch 3/10
78/78 [==============================] - 0s 37us/step - loss: 1.9282 - accuracy: 0.3077 - val_loss: 1.8706 - val_accuracy: 0.3333
Epoch 4/10
78/78 [==============================] - 0s 65us/step - loss: 1.8462 - accuracy: 0.3077 - val_loss: 1.8208 - val_accuracy: 0.5926
Epoch 5/10
78/78 [==============================] - 0s 44us/step - loss: 1.7947 - accuracy: 0.6795 - val_loss: 1.7865 - val_accuracy: 0.5556
Epoch 6/10
78/78 [==============================] - 0s 52us/step - loss: 1.7596 - accuracy: 0.6667 - val_loss: 1.7615 - val_accuracy: 0.2593
Epoch 7/10
78/78 [==============================] - 0s 56us/step - loss: 1.7342 - accuracy: 0.5128 - val_loss: 1.7438 - val_accuracy: 0.2593
Epoch 8/10
78/78 [==============================] - 0s 78us/step - loss: 1.7146 - accuracy: 0.4487 - val_loss: 1.7298 - val_accuracy: 0.2593
Epoch 9/10
78/78 [==============================] - 0s 37us/step - loss: 1.7006 - accuracy: 0.3974 - val_loss: 1.7178 - val_accuracy: 0.3333
Epoch 10/10
78/78 [==============================] - 0s 76us/step - loss: 1.6888 - accuracy: 0.4615 - val_loss: 1.7067 - val_accuracy: 0.4444
45/45 [==============================] - 0s 104us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  10
Neurons or Units:  64
Test score: 1.6943550321790908
Test accuracy: 0.46666666865348816

Model: "sequential_32"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_94 (Dense)             (None, 128)               640       
_________________________________________________________________
activation_94 (Activation)   (None, 128)               0         
_________________________________________________________________
dense_95 (Dense)             (None, 128)               16512     
_________________________________________________________________
activation_95 (Activation)   (None, 128)               0         
_________________________________________________________________
dense_96 (Dense)             (None, 3)                 387       
_________________________________________________________________
activation_96 (Activation)   (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 2.5021 - accuracy: 0.3205 - val_loss: 2.4141 - val_accuracy: 0.4074
Epoch 2/10
78/78 [==============================] - 0s 70us/step - loss: 2.4228 - accuracy: 0.3205 - val_loss: 2.3951 - val_accuracy: 0.2963
Epoch 3/10
78/78 [==============================] - 0s 38us/step - loss: 2.3800 - accuracy: 0.3974 - val_loss: 2.3828 - val_accuracy: 0.2593
Epoch 4/10
78/78 [==============================] - 0s 56us/step - loss: 2.3541 - accuracy: 0.3718 - val_loss: 2.3712 - val_accuracy: 0.2593
Epoch 5/10
78/78 [==============================] - 0s 80us/step - loss: 2.3351 - accuracy: 0.3718 - val_loss: 2.3596 - val_accuracy: 0.2593
Epoch 6/10
78/78 [==============================] - 0s 57us/step - loss: 2.3189 - accuracy: 0.3718 - val_loss: 2.3471 - val_accuracy: 0.2593
Epoch 7/10
78/78 [==============================] - 0s 74us/step - loss: 2.3037 - accuracy: 0.3718 - val_loss: 2.3337 - val_accuracy: 0.2593
Epoch 8/10
78/78 [==============================] - 0s 32us/step - loss: 2.2889 - accuracy: 0.3718 - val_loss: 2.3210 - val_accuracy: 0.2593
Epoch 9/10
78/78 [==============================] - 0s 54us/step - loss: 2.2754 - accuracy: 0.3718 - val_loss: 2.3088 - val_accuracy: 0.2593
Epoch 10/10
78/78 [==============================] - 0s 80us/step - loss: 2.2628 - accuracy: 0.3718 - val_loss: 2.2971 - val_accuracy: 0.3704
45/45 [==============================] - 0s 54us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  10
Neurons or Units:  128
Test score: 2.2671533955468073
Test accuracy: 0.5111111402511597

Model: "sequential_33"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_97 (Dense)             (None, 256)               1280      
_________________________________________________________________
activation_97 (Activation)   (None, 256)               0         
_________________________________________________________________
dense_98 (Dense)             (None, 256)               65792     
_________________________________________________________________
activation_98 (Activation)   (None, 256)               0         
_________________________________________________________________
dense_99 (Dense)             (None, 3)                 771       
_________________________________________________________________
activation_99 (Activation)   (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 3.8187 - accuracy: 0.0000e+00 - val_loss: 3.7997 - val_accuracy: 0.2593
Epoch 2/10
78/78 [==============================] - 0s 82us/step - loss: 3.7491 - accuracy: 0.3718 - val_loss: 3.7469 - val_accuracy: 0.2593
Epoch 3/10
78/78 [==============================] - 0s 64us/step - loss: 3.7025 - accuracy: 0.3718 - val_loss: 3.7079 - val_accuracy: 0.2593
Epoch 4/10
78/78 [==============================] - 0s 51us/step - loss: 3.6694 - accuracy: 0.3718 - val_loss: 3.6790 - val_accuracy: 0.2593
Epoch 5/10
78/78 [==============================] - 0s 46us/step - loss: 3.6443 - accuracy: 0.3718 - val_loss: 3.6558 - val_accuracy: 0.2593
Epoch 6/10
78/78 [==============================] - 0s 97us/step - loss: 3.6234 - accuracy: 0.3718 - val_loss: 3.6360 - val_accuracy: 0.3333
Epoch 7/10
78/78 [==============================] - 0s 99us/step - loss: 3.6053 - accuracy: 0.4231 - val_loss: 3.6181 - val_accuracy: 0.5185
Epoch 8/10
78/78 [==============================] - 0s 48us/step - loss: 3.5882 - accuracy: 0.6282 - val_loss: 3.6018 - val_accuracy: 0.5556
Epoch 9/10
78/78 [==============================] - 0s 58us/step - loss: 3.5726 - accuracy: 0.6795 - val_loss: 3.5860 - val_accuracy: 0.5926
Epoch 10/10
78/78 [==============================] - 0s 85us/step - loss: 3.5576 - accuracy: 0.6795 - val_loss: 3.5711 - val_accuracy: 0.5926
45/45 [==============================] - 0s 52us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  10
Neurons or Units:  256
Test score: 3.5490816805097793
Test accuracy: 0.6888889074325562

Model: "sequential_34"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_100 (Dense)            (None, 64)                320       
_________________________________________________________________
activation_100 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_101 (Dense)            (None, 64)                4160      
_________________________________________________________________
activation_101 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_102 (Dense)            (None, 3)                 195       
_________________________________________________________________
activation_102 (Activation)  (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 1.9116 - accuracy: 0.6795 - val_loss: 1.9235 - val_accuracy: 0.5926
Epoch 2/20
78/78 [==============================] - 0s 60us/step - loss: 1.8226 - accuracy: 0.6795 - val_loss: 1.8430 - val_accuracy: 0.5926
Epoch 3/20
78/78 [==============================] - 0s 72us/step - loss: 1.7571 - accuracy: 0.6795 - val_loss: 1.7885 - val_accuracy: 0.5926
Epoch 4/20
78/78 [==============================] - 0s 54us/step - loss: 1.7132 - accuracy: 0.6795 - val_loss: 1.7491 - val_accuracy: 0.5926
Epoch 5/20
78/78 [==============================] - 0s 44us/step - loss: 1.6831 - accuracy: 0.6795 - val_loss: 1.7188 - val_accuracy: 0.5926
Epoch 6/20
78/78 [==============================] - 0s 38us/step - loss: 1.6601 - accuracy: 0.6795 - val_loss: 1.6947 - val_accuracy: 0.5926
Epoch 7/20
78/78 [==============================] - 0s 36us/step - loss: 1.6421 - accuracy: 0.6795 - val_loss: 1.6760 - val_accuracy: 0.5926
Epoch 8/20
78/78 [==============================] - 0s 56us/step - loss: 1.6281 - accuracy: 0.6795 - val_loss: 1.6609 - val_accuracy: 0.5926
Epoch 9/20
78/78 [==============================] - 0s 39us/step - loss: 1.6166 - accuracy: 0.6795 - val_loss: 1.6484 - val_accuracy: 0.5926
Epoch 10/20
78/78 [==============================] - 0s 48us/step - loss: 1.6064 - accuracy: 0.6795 - val_loss: 1.6363 - val_accuracy: 0.5926
Epoch 11/20
78/78 [==============================] - 0s 51us/step - loss: 1.5968 - accuracy: 0.6795 - val_loss: 1.6258 - val_accuracy: 0.5926
Epoch 12/20
78/78 [==============================] - 0s 41us/step - loss: 1.5879 - accuracy: 0.6795 - val_loss: 1.6169 - val_accuracy: 0.5926
Epoch 13/20
78/78 [==============================] - 0s 39us/step - loss: 1.5800 - accuracy: 0.6795 - val_loss: 1.6082 - val_accuracy: 0.5926
Epoch 14/20
78/78 [==============================] - 0s 53us/step - loss: 1.5722 - accuracy: 0.6795 - val_loss: 1.5999 - val_accuracy: 0.5926
Epoch 15/20
78/78 [==============================] - 0s 57us/step - loss: 1.5649 - accuracy: 0.6795 - val_loss: 1.5917 - val_accuracy: 0.5926
Epoch 16/20
78/78 [==============================] - 0s 53us/step - loss: 1.5578 - accuracy: 0.6795 - val_loss: 1.5839 - val_accuracy: 0.5926
Epoch 17/20
78/78 [==============================] - 0s 55us/step - loss: 1.5511 - accuracy: 0.6795 - val_loss: 1.5771 - val_accuracy: 0.5926
Epoch 18/20
78/78 [==============================] - 0s 38us/step - loss: 1.5447 - accuracy: 0.6795 - val_loss: 1.5705 - val_accuracy: 0.5926
Epoch 19/20
78/78 [==============================] - 0s 41us/step - loss: 1.5385 - accuracy: 0.6795 - val_loss: 1.5644 - val_accuracy: 0.5926
Epoch 20/20
78/78 [==============================] - 0s 69us/step - loss: 1.5325 - accuracy: 0.6795 - val_loss: 1.5583 - val_accuracy: 0.5926
45/45 [==============================] - 0s 45us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  20
Neurons or Units:  64
Test score: 1.532747787899441
Test accuracy: 0.6888889074325562

Model: "sequential_35"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_103 (Dense)            (None, 128)               640       
_________________________________________________________________
activation_103 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_104 (Dense)            (None, 128)               16512     
_________________________________________________________________
activation_104 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_105 (Dense)            (None, 3)                 387       
_________________________________________________________________
activation_105 (Activation)  (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 1ms/step - loss: 2.4506 - accuracy: 0.3718 - val_loss: 2.4683 - val_accuracy: 0.2593
Epoch 2/20
78/78 [==============================] - 0s 39us/step - loss: 2.4311 - accuracy: 0.3718 - val_loss: 2.4496 - val_accuracy: 0.2593
Epoch 3/20
78/78 [==============================] - 0s 59us/step - loss: 2.4126 - accuracy: 0.3718 - val_loss: 2.4316 - val_accuracy: 0.2593
Epoch 4/20
78/78 [==============================] - 0s 72us/step - loss: 2.3948 - accuracy: 0.3718 - val_loss: 2.4141 - val_accuracy: 0.2593
Epoch 5/20
78/78 [==============================] - 0s 40us/step - loss: 2.3779 - accuracy: 0.3718 - val_loss: 2.4006 - val_accuracy: 0.2593
Epoch 6/20
78/78 [==============================] - 0s 63us/step - loss: 2.3642 - accuracy: 0.3718 - val_loss: 2.3879 - val_accuracy: 0.2593
Epoch 7/20
78/78 [==============================] - 0s 55us/step - loss: 2.3519 - accuracy: 0.3718 - val_loss: 2.3759 - val_accuracy: 0.2593
Epoch 8/20
78/78 [==============================] - 0s 51us/step - loss: 2.3404 - accuracy: 0.3718 - val_loss: 2.3651 - val_accuracy: 0.2593
Epoch 9/20
78/78 [==============================] - 0s 47us/step - loss: 2.3295 - accuracy: 0.3718 - val_loss: 2.3546 - val_accuracy: 0.2593
Epoch 10/20
78/78 [==============================] - 0s 48us/step - loss: 2.3190 - accuracy: 0.3718 - val_loss: 2.3448 - val_accuracy: 0.2593
Epoch 11/20
78/78 [==============================] - 0s 38us/step - loss: 2.3091 - accuracy: 0.3718 - val_loss: 2.3352 - val_accuracy: 0.2593
Epoch 12/20
78/78 [==============================] - 0s 77us/step - loss: 2.2994 - accuracy: 0.3718 - val_loss: 2.3259 - val_accuracy: 0.2593
Epoch 13/20
78/78 [==============================] - 0s 46us/step - loss: 2.2899 - accuracy: 0.3718 - val_loss: 2.3165 - val_accuracy: 0.2593
Epoch 14/20
78/78 [==============================] - 0s 63us/step - loss: 2.2809 - accuracy: 0.4103 - val_loss: 2.3079 - val_accuracy: 0.4444
Epoch 15/20
78/78 [==============================] - 0s 69us/step - loss: 2.2725 - accuracy: 0.6538 - val_loss: 2.2998 - val_accuracy: 0.5556
Epoch 16/20
78/78 [==============================] - 0s 72us/step - loss: 2.2646 - accuracy: 0.6795 - val_loss: 2.2919 - val_accuracy: 0.5926
Epoch 17/20
78/78 [==============================] - 0s 52us/step - loss: 2.2570 - accuracy: 0.6795 - val_loss: 2.2844 - val_accuracy: 0.5926
Epoch 18/20
78/78 [==============================] - 0s 45us/step - loss: 2.2496 - accuracy: 0.6795 - val_loss: 2.2771 - val_accuracy: 0.5926
Epoch 19/20
78/78 [==============================] - 0s 47us/step - loss: 2.2423 - accuracy: 0.6795 - val_loss: 2.2700 - val_accuracy: 0.5926
Epoch 20/20
78/78 [==============================] - 0s 66us/step - loss: 2.2352 - accuracy: 0.6795 - val_loss: 2.2631 - val_accuracy: 0.5926
45/45 [==============================] - 0s 57us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  20
Neurons or Units:  128
Test score: 2.2401612917582194
Test accuracy: 0.6888889074325562

Model: "sequential_36"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_106 (Dense)            (None, 256)               1280      
_________________________________________________________________
activation_106 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_107 (Dense)            (None, 256)               65792     
_________________________________________________________________
activation_107 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_108 (Dense)            (None, 3)                 771       
_________________________________________________________________
activation_108 (Activation)  (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 3.8435 - accuracy: 0.3077 - val_loss: 3.7631 - val_accuracy: 0.4815
Epoch 2/20
78/78 [==============================] - 0s 61us/step - loss: 3.7351 - accuracy: 0.4744 - val_loss: 3.7191 - val_accuracy: 0.5926
Epoch 3/20
78/78 [==============================] - 0s 54us/step - loss: 3.6821 - accuracy: 0.6795 - val_loss: 3.6894 - val_accuracy: 0.4444
Epoch 4/20
78/78 [==============================] - 0s 68us/step - loss: 3.6490 - accuracy: 0.6282 - val_loss: 3.6650 - val_accuracy: 0.4815
Epoch 5/20
78/78 [==============================] - 0s 49us/step - loss: 3.6242 - accuracy: 0.6410 - val_loss: 3.6444 - val_accuracy: 0.5926
Epoch 6/20
78/78 [==============================] - 0s 84us/step - loss: 3.6039 - accuracy: 0.6795 - val_loss: 3.6257 - val_accuracy: 0.5926
Epoch 7/20
78/78 [==============================] - 0s 74us/step - loss: 3.5858 - accuracy: 0.6795 - val_loss: 3.6084 - val_accuracy: 0.5926
Epoch 8/20
78/78 [==============================] - 0s 49us/step - loss: 3.5691 - accuracy: 0.6795 - val_loss: 3.5922 - val_accuracy: 0.5926
Epoch 9/20
78/78 [==============================] - 0s 70us/step - loss: 3.5534 - accuracy: 0.6795 - val_loss: 3.5768 - val_accuracy: 0.5926
Epoch 10/20
78/78 [==============================] - 0s 48us/step - loss: 3.5384 - accuracy: 0.6795 - val_loss: 3.5624 - val_accuracy: 0.5926
Epoch 11/20
78/78 [==============================] - 0s 57us/step - loss: 3.5242 - accuracy: 0.6795 - val_loss: 3.5483 - val_accuracy: 0.5926
Epoch 12/20
78/78 [==============================] - 0s 80us/step - loss: 3.5106 - accuracy: 0.6795 - val_loss: 3.5349 - val_accuracy: 0.5926
Epoch 13/20
78/78 [==============================] - 0s 59us/step - loss: 3.4977 - accuracy: 0.6795 - val_loss: 3.5221 - val_accuracy: 0.5926
Epoch 14/20
78/78 [==============================] - 0s 54us/step - loss: 3.4852 - accuracy: 0.6795 - val_loss: 3.5097 - val_accuracy: 0.5926
Epoch 15/20
78/78 [==============================] - 0s 86us/step - loss: 3.4731 - accuracy: 0.6795 - val_loss: 3.4979 - val_accuracy: 0.5926
Epoch 16/20
78/78 [==============================] - 0s 60us/step - loss: 3.4616 - accuracy: 0.6795 - val_loss: 3.4866 - val_accuracy: 0.5926
Epoch 17/20
78/78 [==============================] - 0s 68us/step - loss: 3.4504 - accuracy: 0.6795 - val_loss: 3.4756 - val_accuracy: 0.5926
Epoch 18/20
78/78 [==============================] - 0s 49us/step - loss: 3.4397 - accuracy: 0.6795 - val_loss: 3.4649 - val_accuracy: 0.5926
Epoch 19/20
78/78 [==============================] - 0s 50us/step - loss: 3.4292 - accuracy: 0.6795 - val_loss: 3.4546 - val_accuracy: 0.5926
Epoch 20/20
78/78 [==============================] - 0s 60us/step - loss: 3.4191 - accuracy: 0.6795 - val_loss: 3.4443 - val_accuracy: 0.5926
45/45 [==============================] - 0s 52us/step

Optimizers:  <keras.optimizers.SGD object at 0x10bb1ddd0>
Epoch Sizes:  20
Neurons or Units:  256
Test score: 3.4089132997724745
Test accuracy: 0.6888889074325562

Model: "sequential_37"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_109 (Dense)            (None, 64)                320       
_________________________________________________________________
activation_109 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_110 (Dense)            (None, 64)                4160      
_________________________________________________________________
activation_110 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_111 (Dense)            (None, 3)                 195       
_________________________________________________________________
activation_111 (Activation)  (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 2ms/step - loss: 2.0433 - accuracy: 0.3077 - val_loss: 1.6760 - val_accuracy: 0.3333
Epoch 2/5
78/78 [==============================] - 0s 43us/step - loss: 1.7025 - accuracy: 0.3590 - val_loss: 1.5887 - val_accuracy: 0.5926
Epoch 3/5
78/78 [==============================] - 0s 66us/step - loss: 1.5839 - accuracy: 0.6795 - val_loss: 1.5280 - val_accuracy: 0.5926
Epoch 4/5
78/78 [==============================] - 0s 53us/step - loss: 1.5131 - accuracy: 0.6795 - val_loss: 1.4771 - val_accuracy: 0.5926
Epoch 5/5
78/78 [==============================] - 0s 43us/step - loss: 1.4578 - accuracy: 0.6795 - val_loss: 1.4312 - val_accuracy: 0.5926
45/45 [==============================] - 0s 131us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  5
Neurons or Units:  64
Test score: 1.3850537300109864
Test accuracy: 0.6888889074325562

Model: "sequential_38"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_112 (Dense)            (None, 128)               640       
_________________________________________________________________
activation_112 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_113 (Dense)            (None, 128)               16512     
_________________________________________________________________
activation_113 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_114 (Dense)            (None, 3)                 387       
_________________________________________________________________
activation_114 (Activation)  (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 2ms/step - loss: 2.3740 - accuracy: 0.3718 - val_loss: 2.2265 - val_accuracy: 0.4074
Epoch 2/5
78/78 [==============================] - 0s 54us/step - loss: 2.2774 - accuracy: 0.3205 - val_loss: 2.2092 - val_accuracy: 0.5926
Epoch 3/5
78/78 [==============================] - 0s 45us/step - loss: 2.1155 - accuracy: 0.6795 - val_loss: 2.0119 - val_accuracy: 1.0000
Epoch 4/5
78/78 [==============================] - 0s 73us/step - loss: 2.0079 - accuracy: 0.9615 - val_loss: 1.9816 - val_accuracy: 0.5926
Epoch 5/5
78/78 [==============================] - 0s 44us/step - loss: 1.9306 - accuracy: 0.6795 - val_loss: 1.8854 - val_accuracy: 0.8889
45/45 [==============================] - 0s 46us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  5
Neurons or Units:  128
Test score: 1.86493980884552
Test accuracy: 0.8666666746139526

Model: "sequential_39"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_115 (Dense)            (None, 256)               1280      
_________________________________________________________________
activation_115 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_116 (Dense)            (None, 256)               65792     
_________________________________________________________________
activation_116 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_117 (Dense)            (None, 3)                 771       
_________________________________________________________________
activation_117 (Activation)  (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 2ms/step - loss: 3.9818 - accuracy: 0.3205 - val_loss: 3.8592 - val_accuracy: 0.2593
Epoch 2/5
78/78 [==============================] - 0s 85us/step - loss: 3.6788 - accuracy: 0.3718 - val_loss: 3.2717 - val_accuracy: 0.8148
Epoch 3/5
78/78 [==============================] - 0s 66us/step - loss: 3.2813 - accuracy: 0.7308 - val_loss: 3.1324 - val_accuracy: 0.5926
Epoch 4/5
78/78 [==============================] - 0s 53us/step - loss: 3.0880 - accuracy: 0.6795 - val_loss: 2.9690 - val_accuracy: 0.6296
Epoch 5/5
78/78 [==============================] - 0s 60us/step - loss: 2.9451 - accuracy: 0.6795 - val_loss: 2.8615 - val_accuracy: 0.5926
45/45 [==============================] - 0s 71us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  5
Neurons or Units:  256
Test score: 2.833940935134888
Test accuracy: 0.6888889074325562

Model: "sequential_40"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_118 (Dense)            (None, 64)                320       
_________________________________________________________________
activation_118 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_119 (Dense)            (None, 64)                4160      
_________________________________________________________________
activation_119 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_120 (Dense)            (None, 3)                 195       
_________________________________________________________________
activation_120 (Activation)  (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 1.9152 - accuracy: 0.3718 - val_loss: 1.8711 - val_accuracy: 0.2593
Epoch 2/10
78/78 [==============================] - 0s 62us/step - loss: 1.8077 - accuracy: 0.3718 - val_loss: 1.7852 - val_accuracy: 0.4815
Epoch 3/10
78/78 [==============================] - 0s 41us/step - loss: 1.7527 - accuracy: 0.5256 - val_loss: 1.8036 - val_accuracy: 0.2593
Epoch 4/10
78/78 [==============================] - 0s 75us/step - loss: 1.7116 - accuracy: 0.3718 - val_loss: 1.6839 - val_accuracy: 0.4444
Epoch 5/10
78/78 [==============================] - 0s 48us/step - loss: 1.6598 - accuracy: 0.5128 - val_loss: 1.6825 - val_accuracy: 0.2593
Epoch 6/10
78/78 [==============================] - 0s 38us/step - loss: 1.6192 - accuracy: 0.3718 - val_loss: 1.6210 - val_accuracy: 0.2593
Epoch 7/10
78/78 [==============================] - 0s 44us/step - loss: 1.5837 - accuracy: 0.3718 - val_loss: 1.6003 - val_accuracy: 0.2593
Epoch 8/10
78/78 [==============================] - 0s 58us/step - loss: 1.5498 - accuracy: 0.3718 - val_loss: 1.5597 - val_accuracy: 0.2593
Epoch 9/10
78/78 [==============================] - 0s 52us/step - loss: 1.5203 - accuracy: 0.3718 - val_loss: 1.5383 - val_accuracy: 0.4815
Epoch 10/10
78/78 [==============================] - 0s 46us/step - loss: 1.4929 - accuracy: 0.6410 - val_loss: 1.5045 - val_accuracy: 0.5926
45/45 [==============================] - 0s 67us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  10
Neurons or Units:  64
Test score: 1.4838784164852565
Test accuracy: 0.6222222447395325

Model: "sequential_41"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_121 (Dense)            (None, 128)               640       
_________________________________________________________________
activation_121 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_122 (Dense)            (None, 128)               16512     
_________________________________________________________________
activation_122 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_123 (Dense)            (None, 3)                 387       
_________________________________________________________________
activation_123 (Activation)  (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 2.5889 - accuracy: 0.3205 - val_loss: 2.4009 - val_accuracy: 0.2593
Epoch 2/10
78/78 [==============================] - 0s 67us/step - loss: 2.3228 - accuracy: 0.3718 - val_loss: 2.1901 - val_accuracy: 0.6296
Epoch 3/10
78/78 [==============================] - 0s 47us/step - loss: 2.1709 - accuracy: 0.7051 - val_loss: 2.1059 - val_accuracy: 0.5926
Epoch 4/10
78/78 [==============================] - 0s 74us/step - loss: 2.0716 - accuracy: 0.6795 - val_loss: 2.0208 - val_accuracy: 0.5926
Epoch 5/10
78/78 [==============================] - 0s 41us/step - loss: 1.9924 - accuracy: 0.6795 - val_loss: 1.9540 - val_accuracy: 0.5926
Epoch 6/10
78/78 [==============================] - 0s 95us/step - loss: 1.9246 - accuracy: 0.6795 - val_loss: 1.8926 - val_accuracy: 0.6296
Epoch 7/10
78/78 [==============================] - 0s 69us/step - loss: 1.8658 - accuracy: 0.6795 - val_loss: 1.8393 - val_accuracy: 0.6296
Epoch 8/10
78/78 [==============================] - 0s 47us/step - loss: 1.8128 - accuracy: 0.6795 - val_loss: 1.7872 - val_accuracy: 0.6667
Epoch 9/10
78/78 [==============================] - 0s 72us/step - loss: 1.7638 - accuracy: 0.7692 - val_loss: 1.7431 - val_accuracy: 0.7037
Epoch 10/10
78/78 [==============================] - 0s 49us/step - loss: 1.7188 - accuracy: 0.7692 - val_loss: 1.6972 - val_accuracy: 0.7407
45/45 [==============================] - 0s 54us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  10
Neurons or Units:  128
Test score: 1.6669380452897813
Test accuracy: 0.800000011920929

Model: "sequential_42"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_124 (Dense)            (None, 256)               1280      
_________________________________________________________________
activation_124 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_125 (Dense)            (None, 256)               65792     
_________________________________________________________________
activation_125 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_126 (Dense)            (None, 3)                 771       
_________________________________________________________________
activation_126 (Activation)  (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 3.9308 - accuracy: 0.3077 - val_loss: 3.5686 - val_accuracy: 0.2593
Epoch 2/10
78/78 [==============================] - 0s 57us/step - loss: 3.4952 - accuracy: 0.3718 - val_loss: 3.2113 - val_accuracy: 0.7037
Epoch 3/10
78/78 [==============================] - 0s 49us/step - loss: 3.2526 - accuracy: 0.6282 - val_loss: 3.2729 - val_accuracy: 0.5926
Epoch 4/10
78/78 [==============================] - 0s 84us/step - loss: 3.1460 - accuracy: 0.6795 - val_loss: 2.9348 - val_accuracy: 0.7407
Epoch 5/10
78/78 [==============================] - 0s 55us/step - loss: 2.9673 - accuracy: 0.6282 - val_loss: 2.9056 - val_accuracy: 0.5926
Epoch 6/10
78/78 [==============================] - 0s 61us/step - loss: 2.8362 - accuracy: 0.6795 - val_loss: 2.7247 - val_accuracy: 1.0000
Epoch 7/10
78/78 [==============================] - 0s 76us/step - loss: 2.7268 - accuracy: 0.9487 - val_loss: 2.6825 - val_accuracy: 0.5926
Epoch 8/10
78/78 [==============================] - 0s 65us/step - loss: 2.6352 - accuracy: 0.6795 - val_loss: 2.5535 - val_accuracy: 1.0000
Epoch 9/10
78/78 [==============================] - 0s 85us/step - loss: 2.5528 - accuracy: 0.9359 - val_loss: 2.5218 - val_accuracy: 0.5926
Epoch 10/10
78/78 [==============================] - 0s 92us/step - loss: 2.4786 - accuracy: 0.6795 - val_loss: 2.4022 - val_accuracy: 1.0000
45/45 [==============================] - 0s 84us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  10
Neurons or Units:  256
Test score: 2.3823694864908855
Test accuracy: 0.9777777791023254

Model: "sequential_43"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_127 (Dense)            (None, 64)                320       
_________________________________________________________________
activation_127 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_128 (Dense)            (None, 64)                4160      
_________________________________________________________________
activation_128 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_129 (Dense)            (None, 3)                 195       
_________________________________________________________________
activation_129 (Activation)  (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 1.6949 - accuracy: 0.6795 - val_loss: 1.5914 - val_accuracy: 0.5926
Epoch 2/20
78/78 [==============================] - 0s 34us/step - loss: 1.5618 - accuracy: 0.6795 - val_loss: 1.5570 - val_accuracy: 0.5926
Epoch 3/20
78/78 [==============================] - 0s 43us/step - loss: 1.4964 - accuracy: 0.6795 - val_loss: 1.4758 - val_accuracy: 0.5926
Epoch 4/20
78/78 [==============================] - 0s 30us/step - loss: 1.4475 - accuracy: 0.6795 - val_loss: 1.4571 - val_accuracy: 0.5926
Epoch 5/20
78/78 [==============================] - 0s 66us/step - loss: 1.4070 - accuracy: 0.6795 - val_loss: 1.4057 - val_accuracy: 0.5926
Epoch 6/20
78/78 [==============================] - 0s 32us/step - loss: 1.3729 - accuracy: 0.6795 - val_loss: 1.3862 - val_accuracy: 0.5926
Epoch 7/20
78/78 [==============================] - 0s 87us/step - loss: 1.3434 - accuracy: 0.6795 - val_loss: 1.3492 - val_accuracy: 0.5926
Epoch 8/20
78/78 [==============================] - 0s 42us/step - loss: 1.3167 - accuracy: 0.6923 - val_loss: 1.3299 - val_accuracy: 0.5926
Epoch 9/20
78/78 [==============================] - 0s 47us/step - loss: 1.2912 - accuracy: 0.6795 - val_loss: 1.2994 - val_accuracy: 0.5926
Epoch 10/20
78/78 [==============================] - 0s 32us/step - loss: 1.2679 - accuracy: 0.7051 - val_loss: 1.2816 - val_accuracy: 0.5926
Epoch 11/20
78/78 [==============================] - 0s 73us/step - loss: 1.2461 - accuracy: 0.6923 - val_loss: 1.2545 - val_accuracy: 0.5926
Epoch 12/20
78/78 [==============================] - 0s 38us/step - loss: 1.2256 - accuracy: 0.7051 - val_loss: 1.2393 - val_accuracy: 0.5926
Epoch 13/20
78/78 [==============================] - 0s 41us/step - loss: 1.2061 - accuracy: 0.7051 - val_loss: 1.2133 - val_accuracy: 0.6667
Epoch 14/20
78/78 [==============================] - 0s 74us/step - loss: 1.1875 - accuracy: 0.7051 - val_loss: 1.2028 - val_accuracy: 0.5926
Epoch 15/20
78/78 [==============================] - 0s 52us/step - loss: 1.1703 - accuracy: 0.7051 - val_loss: 1.1745 - val_accuracy: 0.7037
Epoch 16/20
78/78 [==============================] - 0s 38us/step - loss: 1.1532 - accuracy: 0.7436 - val_loss: 1.1708 - val_accuracy: 0.5926
Epoch 17/20
78/78 [==============================] - 0s 69us/step - loss: 1.1375 - accuracy: 0.7051 - val_loss: 1.1367 - val_accuracy: 0.8148
Epoch 18/20
78/78 [==============================] - 0s 47us/step - loss: 1.1228 - accuracy: 0.8590 - val_loss: 1.1454 - val_accuracy: 0.5926
Epoch 19/20
78/78 [==============================] - 0s 57us/step - loss: 1.1089 - accuracy: 0.6923 - val_loss: 1.1025 - val_accuracy: 0.9630
Epoch 20/20
78/78 [==============================] - 0s 39us/step - loss: 1.0952 - accuracy: 0.9103 - val_loss: 1.1171 - val_accuracy: 0.5926
45/45 [==============================] - 0s 53us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  20
Neurons or Units:  64
Test score: 1.0631668859057957
Test accuracy: 0.6888889074325562

Model: "sequential_44"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_130 (Dense)            (None, 128)               640       
_________________________________________________________________
activation_130 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_131 (Dense)            (None, 128)               16512     
_________________________________________________________________
activation_131 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_132 (Dense)            (None, 3)                 387       
_________________________________________________________________
activation_132 (Activation)  (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 2.4248 - accuracy: 0.3718 - val_loss: 2.3232 - val_accuracy: 0.3333
Epoch 2/20
78/78 [==============================] - 0s 57us/step - loss: 2.2338 - accuracy: 0.5641 - val_loss: 2.1166 - val_accuracy: 0.4074
Epoch 3/20
78/78 [==============================] - 0s 63us/step - loss: 2.1444 - accuracy: 0.3462 - val_loss: 2.1053 - val_accuracy: 0.5926
Epoch 4/20
78/78 [==============================] - 0s 49us/step - loss: 2.0278 - accuracy: 0.6795 - val_loss: 1.9494 - val_accuracy: 1.0000
Epoch 5/20
78/78 [==============================] - 0s 43us/step - loss: 1.9401 - accuracy: 0.9487 - val_loss: 1.9205 - val_accuracy: 0.5926
Epoch 6/20
78/78 [==============================] - 0s 50us/step - loss: 1.8753 - accuracy: 0.6795 - val_loss: 1.8380 - val_accuracy: 0.8889
Epoch 7/20
78/78 [==============================] - 0s 52us/step - loss: 1.8201 - accuracy: 0.8718 - val_loss: 1.8063 - val_accuracy: 0.6296
Epoch 8/20
78/78 [==============================] - 0s 48us/step - loss: 1.7706 - accuracy: 0.7179 - val_loss: 1.7417 - val_accuracy: 0.8889
Epoch 9/20
78/78 [==============================] - 0s 67us/step - loss: 1.7256 - accuracy: 0.8846 - val_loss: 1.7154 - val_accuracy: 0.7037
Epoch 10/20
78/78 [==============================] - 0s 51us/step - loss: 1.6836 - accuracy: 0.7821 - val_loss: 1.6565 - val_accuracy: 0.9630
Epoch 11/20
78/78 [==============================] - 0s 45us/step - loss: 1.6437 - accuracy: 0.9103 - val_loss: 1.6369 - val_accuracy: 0.7407
Epoch 12/20
78/78 [==============================] - 0s 50us/step - loss: 1.6071 - accuracy: 0.8077 - val_loss: 1.5768 - val_accuracy: 1.0000
Epoch 13/20
78/78 [==============================] - 0s 43us/step - loss: 1.5735 - accuracy: 0.9487 - val_loss: 1.5784 - val_accuracy: 0.6667
Epoch 14/20
78/78 [==============================] - 0s 67us/step - loss: 1.5436 - accuracy: 0.7821 - val_loss: 1.5049 - val_accuracy: 1.0000
Epoch 15/20
78/78 [==============================] - 0s 42us/step - loss: 1.5159 - accuracy: 0.9487 - val_loss: 1.5327 - val_accuracy: 0.6296
Epoch 16/20
78/78 [==============================] - 0s 40us/step - loss: 1.4919 - accuracy: 0.7179 - val_loss: 1.4454 - val_accuracy: 1.0000
Epoch 17/20
78/78 [==============================] - 0s 38us/step - loss: 1.4635 - accuracy: 0.9487 - val_loss: 1.4720 - val_accuracy: 0.6667
Epoch 18/20
78/78 [==============================] - 0s 52us/step - loss: 1.4359 - accuracy: 0.7692 - val_loss: 1.3910 - val_accuracy: 1.0000
Epoch 19/20
78/78 [==============================] - 0s 41us/step - loss: 1.4047 - accuracy: 0.9487 - val_loss: 1.4047 - val_accuracy: 0.7407
Epoch 20/20
78/78 [==============================] - 0s 48us/step - loss: 1.3784 - accuracy: 0.8205 - val_loss: 1.3395 - val_accuracy: 1.0000
45/45 [==============================] - 0s 65us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  20
Neurons or Units:  128
Test score: 1.3295740604400634
Test accuracy: 1.0

Model: "sequential_45"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_133 (Dense)            (None, 256)               1280      
_________________________________________________________________
activation_133 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_134 (Dense)            (None, 256)               65792     
_________________________________________________________________
activation_134 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_135 (Dense)            (None, 3)                 771       
_________________________________________________________________
activation_135 (Activation)  (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 3.8746 - accuracy: 0.3077 - val_loss: 3.7770 - val_accuracy: 0.2593
Epoch 2/20
78/78 [==============================] - 0s 47us/step - loss: 3.6066 - accuracy: 0.3718 - val_loss: 3.1880 - val_accuracy: 0.7407
Epoch 3/20
78/78 [==============================] - 0s 73us/step - loss: 3.2801 - accuracy: 0.6282 - val_loss: 3.1415 - val_accuracy: 0.5926
Epoch 4/20
78/78 [==============================] - 0s 61us/step - loss: 3.0458 - accuracy: 0.6795 - val_loss: 2.8805 - val_accuracy: 0.7778
Epoch 5/20
78/78 [==============================] - 0s 84us/step - loss: 2.8931 - accuracy: 0.6667 - val_loss: 2.8369 - val_accuracy: 0.5926
Epoch 6/20
78/78 [==============================] - 0s 69us/step - loss: 2.7837 - accuracy: 0.6795 - val_loss: 2.6878 - val_accuracy: 1.0000
Epoch 7/20
78/78 [==============================] - 0s 60us/step - loss: 2.6907 - accuracy: 0.9487 - val_loss: 2.6576 - val_accuracy: 0.5926
Epoch 8/20
78/78 [==============================] - 0s 75us/step - loss: 2.6139 - accuracy: 0.6795 - val_loss: 2.5308 - val_accuracy: 1.0000
Epoch 9/20
78/78 [==============================] - 0s 90us/step - loss: 2.5422 - accuracy: 0.9487 - val_loss: 2.5252 - val_accuracy: 0.5926
Epoch 10/20
78/78 [==============================] - 0s 69us/step - loss: 2.4801 - accuracy: 0.6795 - val_loss: 2.3982 - val_accuracy: 0.8889
Epoch 11/20
78/78 [==============================] - 0s 66us/step - loss: 2.4241 - accuracy: 0.8590 - val_loss: 2.4290 - val_accuracy: 0.5926
Epoch 12/20
78/78 [==============================] - 0s 75us/step - loss: 2.3754 - accuracy: 0.6795 - val_loss: 2.2862 - val_accuracy: 0.8148
Epoch 13/20
78/78 [==============================] - 0s 51us/step - loss: 2.3284 - accuracy: 0.7692 - val_loss: 2.3473 - val_accuracy: 0.5926
Epoch 14/20
78/78 [==============================] - 0s 100us/step - loss: 2.2874 - accuracy: 0.6795 - val_loss: 2.1846 - val_accuracy: 0.8148
Epoch 15/20
78/78 [==============================] - 0s 62us/step - loss: 2.2314 - accuracy: 0.7692 - val_loss: 2.2348 - val_accuracy: 0.5926
Epoch 16/20
78/78 [==============================] - 0s 59us/step - loss: 2.1836 - accuracy: 0.6795 - val_loss: 2.0865 - val_accuracy: 0.8889
Epoch 17/20
78/78 [==============================] - 0s 85us/step - loss: 2.1270 - accuracy: 0.8462 - val_loss: 2.1243 - val_accuracy: 0.6296
Epoch 18/20
78/78 [==============================] - 0s 73us/step - loss: 2.0839 - accuracy: 0.6923 - val_loss: 1.9972 - val_accuracy: 0.9259
Epoch 19/20
78/78 [==============================] - 0s 69us/step - loss: 2.0362 - accuracy: 0.9103 - val_loss: 2.0318 - val_accuracy: 0.6296
Epoch 20/20
78/78 [==============================] - 0s 50us/step - loss: 1.9974 - accuracy: 0.6923 - val_loss: 1.9141 - val_accuracy: 0.9259
45/45 [==============================] - 0s 67us/step

Optimizers:  <keras.optimizers.RMSprop object at 0x10bb1dd50>
Epoch Sizes:  20
Neurons or Units:  256
Test score: 1.9176063802507188
Test accuracy: 0.8666666746139526

Model: "sequential_46"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_136 (Dense)            (None, 64)                320       
_________________________________________________________________
activation_136 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_137 (Dense)            (None, 64)                4160      
_________________________________________________________________
activation_137 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_138 (Dense)            (None, 3)                 195       
_________________________________________________________________
activation_138 (Activation)  (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 2ms/step - loss: 2.4989 - accuracy: 0.2692 - val_loss: 2.1248 - val_accuracy: 0.2963
Epoch 2/5
78/78 [==============================] - 0s 37us/step - loss: 2.3592 - accuracy: 0.2308 - val_loss: 2.0312 - val_accuracy: 0.2593
Epoch 3/5
78/78 [==============================] - 0s 49us/step - loss: 2.2293 - accuracy: 0.1795 - val_loss: 1.9458 - val_accuracy: 0.2222
Epoch 4/5
78/78 [==============================] - 0s 41us/step - loss: 2.1091 - accuracy: 0.1795 - val_loss: 1.8694 - val_accuracy: 0.2963
Epoch 5/5
78/78 [==============================] - 0s 50us/step - loss: 1.9991 - accuracy: 0.2051 - val_loss: 1.8037 - val_accuracy: 0.4444
45/45 [==============================] - 0s 57us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  5
Neurons or Units:  64
Test score: 1.8516281233893501
Test accuracy: 0.4444444477558136

Model: "sequential_47"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_139 (Dense)            (None, 128)               640       
_________________________________________________________________
activation_139 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_140 (Dense)            (None, 128)               16512     
_________________________________________________________________
activation_140 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_141 (Dense)            (None, 3)                 387       
_________________________________________________________________
activation_141 (Activation)  (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 2ms/step - loss: 2.5233 - accuracy: 0.3718 - val_loss: 2.5465 - val_accuracy: 0.2593
Epoch 2/5
78/78 [==============================] - 0s 94us/step - loss: 2.4363 - accuracy: 0.3718 - val_loss: 2.4241 - val_accuracy: 0.2593
Epoch 3/5
78/78 [==============================] - 0s 51us/step - loss: 2.3479 - accuracy: 0.3718 - val_loss: 2.3179 - val_accuracy: 0.2593
Epoch 4/5
78/78 [==============================] - 0s 53us/step - loss: 2.2770 - accuracy: 0.3718 - val_loss: 2.2378 - val_accuracy: 0.5185
Epoch 5/5
78/78 [==============================] - 0s 48us/step - loss: 2.2275 - accuracy: 0.5769 - val_loss: 2.1790 - val_accuracy: 0.7407
45/45 [==============================] - 0s 67us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  5
Neurons or Units:  128
Test score: 2.1748369375864667
Test accuracy: 0.6888889074325562

Model: "sequential_48"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_142 (Dense)            (None, 256)               1280      
_________________________________________________________________
activation_142 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_143 (Dense)            (None, 256)               65792     
_________________________________________________________________
activation_143 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_144 (Dense)            (None, 3)                 771       
_________________________________________________________________
activation_144 (Activation)  (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/5
78/78 [==============================] - 0s 2ms/step - loss: 4.2136 - accuracy: 0.3077 - val_loss: 3.9368 - val_accuracy: 0.3333
Epoch 2/5
78/78 [==============================] - 0s 54us/step - loss: 3.9460 - accuracy: 0.3077 - val_loss: 3.7127 - val_accuracy: 0.3333
Epoch 3/5
78/78 [==============================] - 0s 71us/step - loss: 3.7055 - accuracy: 0.3077 - val_loss: 3.5877 - val_accuracy: 0.2593
Epoch 4/5
78/78 [==============================] - 0s 59us/step - loss: 3.5642 - accuracy: 0.3718 - val_loss: 3.5341 - val_accuracy: 0.2593
Epoch 5/5
78/78 [==============================] - 0s 60us/step - loss: 3.4930 - accuracy: 0.3718 - val_loss: 3.4952 - val_accuracy: 0.2593
45/45 [==============================] - 0s 70us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  5
Neurons or Units:  256
Test score: 3.501838535732693
Test accuracy: 0.31111112236976624

Model: "sequential_49"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_145 (Dense)            (None, 64)                320       
_________________________________________________________________
activation_145 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_146 (Dense)            (None, 64)                4160      
_________________________________________________________________
activation_146 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_147 (Dense)            (None, 3)                 195       
_________________________________________________________________
activation_147 (Activation)  (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 1.9195 - accuracy: 0.3077 - val_loss: 1.8632 - val_accuracy: 0.3333
Epoch 2/10
78/78 [==============================] - 0s 47us/step - loss: 1.8655 - accuracy: 0.3077 - val_loss: 1.7998 - val_accuracy: 0.3333
Epoch 3/10
78/78 [==============================] - 0s 37us/step - loss: 1.8002 - accuracy: 0.3077 - val_loss: 1.7400 - val_accuracy: 0.3333
Epoch 4/10
78/78 [==============================] - 0s 52us/step - loss: 1.7370 - accuracy: 0.3205 - val_loss: 1.6853 - val_accuracy: 0.5185
Epoch 5/10
78/78 [==============================] - 0s 74us/step - loss: 1.6791 - accuracy: 0.6026 - val_loss: 1.6392 - val_accuracy: 0.5926
Epoch 6/10
78/78 [==============================] - 0s 46us/step - loss: 1.6308 - accuracy: 0.6923 - val_loss: 1.6025 - val_accuracy: 0.6667
Epoch 7/10
78/78 [==============================] - 0s 48us/step - loss: 1.5906 - accuracy: 0.6923 - val_loss: 1.5739 - val_accuracy: 0.6667
Epoch 8/10
78/78 [==============================] - 0s 47us/step - loss: 1.5578 - accuracy: 0.6923 - val_loss: 1.5509 - val_accuracy: 0.6296
Epoch 9/10
78/78 [==============================] - 0s 39us/step - loss: 1.5303 - accuracy: 0.6923 - val_loss: 1.5317 - val_accuracy: 0.5926
Epoch 10/10
78/78 [==============================] - 0s 44us/step - loss: 1.5063 - accuracy: 0.6795 - val_loss: 1.5143 - val_accuracy: 0.5926
45/45 [==============================] - 0s 78us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  10
Neurons or Units:  64
Test score: 1.5002677069769965
Test accuracy: 0.6888889074325562

Model: "sequential_50"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_148 (Dense)            (None, 128)               640       
_________________________________________________________________
activation_148 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_149 (Dense)            (None, 128)               16512     
_________________________________________________________________
activation_149 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_150 (Dense)            (None, 3)                 387       
_________________________________________________________________
activation_150 (Activation)  (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 2.7264 - accuracy: 0.3205 - val_loss: 2.5248 - val_accuracy: 0.4074
Epoch 2/10
78/78 [==============================] - 0s 48us/step - loss: 2.6144 - accuracy: 0.3205 - val_loss: 2.4512 - val_accuracy: 0.4074
Epoch 3/10
78/78 [==============================] - 0s 51us/step - loss: 2.4935 - accuracy: 0.3205 - val_loss: 2.4005 - val_accuracy: 0.2222
Epoch 4/10
78/78 [==============================] - 0s 43us/step - loss: 2.3944 - accuracy: 0.2564 - val_loss: 2.3841 - val_accuracy: 0.2593
Epoch 5/10
78/78 [==============================] - 0s 62us/step - loss: 2.3344 - accuracy: 0.3718 - val_loss: 2.3842 - val_accuracy: 0.2593
Epoch 6/10
78/78 [==============================] - 0s 79us/step - loss: 2.3028 - accuracy: 0.3718 - val_loss: 2.3717 - val_accuracy: 0.2593
Epoch 7/10
78/78 [==============================] - 0s 62us/step - loss: 2.2731 - accuracy: 0.3718 - val_loss: 2.3359 - val_accuracy: 0.2593
Epoch 8/10
78/78 [==============================] - 0s 53us/step - loss: 2.2316 - accuracy: 0.3718 - val_loss: 2.2743 - val_accuracy: 0.2593
Epoch 9/10
78/78 [==============================] - 0s 46us/step - loss: 2.1754 - accuracy: 0.3974 - val_loss: 2.1966 - val_accuracy: 0.5926
Epoch 10/10
78/78 [==============================] - 0s 66us/step - loss: 2.1109 - accuracy: 0.6795 - val_loss: 2.1154 - val_accuracy: 0.5926
45/45 [==============================] - 0s 57us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  10
Neurons or Units:  128
Test score: 2.059154423077901
Test accuracy: 0.6888889074325562

Model: "sequential_51"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_151 (Dense)            (None, 256)               1280      
_________________________________________________________________
activation_151 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_152 (Dense)            (None, 256)               65792     
_________________________________________________________________
activation_152 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_153 (Dense)            (None, 3)                 771       
_________________________________________________________________
activation_153 (Activation)  (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/10
78/78 [==============================] - 0s 2ms/step - loss: 3.7432 - accuracy: 0.3205 - val_loss: 3.6621 - val_accuracy: 0.2593
Epoch 2/10
78/78 [==============================] - 0s 78us/step - loss: 3.6286 - accuracy: 0.3718 - val_loss: 3.5790 - val_accuracy: 0.2963
Epoch 3/10
78/78 [==============================] - 0s 51us/step - loss: 3.5159 - accuracy: 0.3846 - val_loss: 3.4599 - val_accuracy: 0.5556
Epoch 4/10
78/78 [==============================] - 0s 93us/step - loss: 3.3955 - accuracy: 0.6667 - val_loss: 3.3123 - val_accuracy: 0.5926
Epoch 5/10
78/78 [==============================] - 0s 55us/step - loss: 3.2672 - accuracy: 0.6795 - val_loss: 3.1702 - val_accuracy: 0.5926
Epoch 6/10
78/78 [==============================] - 0s 99us/step - loss: 3.1486 - accuracy: 0.6795 - val_loss: 3.0447 - val_accuracy: 0.8148
Epoch 7/10
78/78 [==============================] - 0s 63us/step - loss: 3.0364 - accuracy: 0.8333 - val_loss: 2.9356 - val_accuracy: 0.6296
Epoch 8/10
78/78 [==============================] - 0s 69us/step - loss: 2.9233 - accuracy: 0.7051 - val_loss: 2.8403 - val_accuracy: 0.5926
Epoch 9/10
78/78 [==============================] - 0s 72us/step - loss: 2.8162 - accuracy: 0.6795 - val_loss: 2.7473 - val_accuracy: 0.5926
Epoch 10/10
78/78 [==============================] - 0s 102us/step - loss: 2.7169 - accuracy: 0.6795 - val_loss: 2.6480 - val_accuracy: 0.5926
45/45 [==============================] - 0s 69us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  10
Neurons or Units:  256
Test score: 2.590741772121853
Test accuracy: 0.6888889074325562

Model: "sequential_52"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_154 (Dense)            (None, 64)                320       
_________________________________________________________________
activation_154 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_155 (Dense)            (None, 64)                4160      
_________________________________________________________________
activation_155 (Activation)  (None, 64)                0         
_________________________________________________________________
dense_156 (Dense)            (None, 3)                 195       
_________________________________________________________________
activation_156 (Activation)  (None, 3)                 0         
=================================================================
Total params: 4,675
Trainable params: 4,675
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 1.8313 - accuracy: 0.6282 - val_loss: 1.7679 - val_accuracy: 0.7407
Epoch 2/20
78/78 [==============================] - 0s 39us/step - loss: 1.8039 - accuracy: 0.6282 - val_loss: 1.7421 - val_accuracy: 0.7407
Epoch 3/20
78/78 [==============================] - 0s 62us/step - loss: 1.7693 - accuracy: 0.6282 - val_loss: 1.7135 - val_accuracy: 0.7407
Epoch 4/20
78/78 [==============================] - 0s 43us/step - loss: 1.7310 - accuracy: 0.6282 - val_loss: 1.6862 - val_accuracy: 0.7037
Epoch 5/20
78/78 [==============================] - 0s 46us/step - loss: 1.6932 - accuracy: 0.6282 - val_loss: 1.6602 - val_accuracy: 0.5185
Epoch 6/20
78/78 [==============================] - 0s 66us/step - loss: 1.6570 - accuracy: 0.5513 - val_loss: 1.6347 - val_accuracy: 0.5926
Epoch 7/20
78/78 [==============================] - 0s 55us/step - loss: 1.6216 - accuracy: 0.6795 - val_loss: 1.6097 - val_accuracy: 0.5926
Epoch 8/20
78/78 [==============================] - 0s 56us/step - loss: 1.5880 - accuracy: 0.6795 - val_loss: 1.5864 - val_accuracy: 0.5556
Epoch 9/20
78/78 [==============================] - 0s 74us/step - loss: 1.5575 - accuracy: 0.6795 - val_loss: 1.5638 - val_accuracy: 0.5556
Epoch 10/20
78/78 [==============================] - 0s 40us/step - loss: 1.5297 - accuracy: 0.6795 - val_loss: 1.5392 - val_accuracy: 0.5556
Epoch 11/20
78/78 [==============================] - 0s 63us/step - loss: 1.5019 - accuracy: 0.6795 - val_loss: 1.5119 - val_accuracy: 0.5926
Epoch 12/20
78/78 [==============================] - 0s 64us/step - loss: 1.4734 - accuracy: 0.6795 - val_loss: 1.4825 - val_accuracy: 0.5926
Epoch 13/20
78/78 [==============================] - 0s 36us/step - loss: 1.4442 - accuracy: 0.6795 - val_loss: 1.4519 - val_accuracy: 0.5926
Epoch 14/20
78/78 [==============================] - 0s 46us/step - loss: 1.4153 - accuracy: 0.6795 - val_loss: 1.4204 - val_accuracy: 0.5926
Epoch 15/20
78/78 [==============================] - 0s 62us/step - loss: 1.3863 - accuracy: 0.6795 - val_loss: 1.3899 - val_accuracy: 0.5926
Epoch 16/20
78/78 [==============================] - 0s 36us/step - loss: 1.3588 - accuracy: 0.6795 - val_loss: 1.3614 - val_accuracy: 0.5926
Epoch 17/20
78/78 [==============================] - 0s 41us/step - loss: 1.3322 - accuracy: 0.6795 - val_loss: 1.3334 - val_accuracy: 0.5926
Epoch 18/20
78/78 [==============================] - 0s 67us/step - loss: 1.3063 - accuracy: 0.6795 - val_loss: 1.3054 - val_accuracy: 0.5926
Epoch 19/20
78/78 [==============================] - 0s 40us/step - loss: 1.2805 - accuracy: 0.6795 - val_loss: 1.2780 - val_accuracy: 0.5926
Epoch 20/20
78/78 [==============================] - 0s 51us/step - loss: 1.2552 - accuracy: 0.6795 - val_loss: 1.2513 - val_accuracy: 0.5926
45/45 [==============================] - 0s 91us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  20
Neurons or Units:  64
Test score: 1.2064275688595243
Test accuracy: 0.6888889074325562

Model: "sequential_53"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_157 (Dense)            (None, 128)               640       
_________________________________________________________________
activation_157 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_158 (Dense)            (None, 128)               16512     
_________________________________________________________________
activation_158 (Activation)  (None, 128)               0         
_________________________________________________________________
dense_159 (Dense)            (None, 3)                 387       
_________________________________________________________________
activation_159 (Activation)  (None, 3)                 0         
=================================================================
Total params: 17,539
Trainable params: 17,539
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 2.5479 - accuracy: 0.3077 - val_loss: 2.4061 - val_accuracy: 0.7407
Epoch 2/20
78/78 [==============================] - 0s 36us/step - loss: 2.4386 - accuracy: 0.6282 - val_loss: 2.3313 - val_accuracy: 0.3704
Epoch 3/20
78/78 [==============================] - 0s 64us/step - loss: 2.3326 - accuracy: 0.2692 - val_loss: 2.2839 - val_accuracy: 0.2593
Epoch 4/20
78/78 [==============================] - 0s 37us/step - loss: 2.2524 - accuracy: 0.3718 - val_loss: 2.2362 - val_accuracy: 0.2593
Epoch 5/20
78/78 [==============================] - 0s 51us/step - loss: 2.1847 - accuracy: 0.3718 - val_loss: 2.1708 - val_accuracy: 0.2963
Epoch 6/20
78/78 [==============================] - 0s 54us/step - loss: 2.1153 - accuracy: 0.4103 - val_loss: 2.0854 - val_accuracy: 0.5556
Epoch 7/20
78/78 [==============================] - 0s 49us/step - loss: 2.0382 - accuracy: 0.6538 - val_loss: 1.9912 - val_accuracy: 0.5926
Epoch 8/20
78/78 [==============================] - 0s 48us/step - loss: 1.9596 - accuracy: 0.6795 - val_loss: 1.9078 - val_accuracy: 0.5926
Epoch 9/20
78/78 [==============================] - 0s 68us/step - loss: 1.8899 - accuracy: 0.6795 - val_loss: 1.8384 - val_accuracy: 0.5926
Epoch 10/20
78/78 [==============================] - 0s 72us/step - loss: 1.8264 - accuracy: 0.6795 - val_loss: 1.7850 - val_accuracy: 0.5926
Epoch 11/20
78/78 [==============================] - 0s 44us/step - loss: 1.7718 - accuracy: 0.6795 - val_loss: 1.7377 - val_accuracy: 0.5926
Epoch 12/20
78/78 [==============================] - 0s 47us/step - loss: 1.7209 - accuracy: 0.6795 - val_loss: 1.6863 - val_accuracy: 0.5926
Epoch 13/20
78/78 [==============================] - 0s 40us/step - loss: 1.6698 - accuracy: 0.6795 - val_loss: 1.6304 - val_accuracy: 0.5926
Epoch 14/20
78/78 [==============================] - 0s 50us/step - loss: 1.6179 - accuracy: 0.6795 - val_loss: 1.5754 - val_accuracy: 0.7037
Epoch 15/20
78/78 [==============================] - 0s 53us/step - loss: 1.5675 - accuracy: 0.7821 - val_loss: 1.5248 - val_accuracy: 0.7407
Epoch 16/20
78/78 [==============================] - 0s 42us/step - loss: 1.5185 - accuracy: 0.8205 - val_loss: 1.4812 - val_accuracy: 0.7407
Epoch 17/20
78/78 [==============================] - 0s 83us/step - loss: 1.4727 - accuracy: 0.7949 - val_loss: 1.4453 - val_accuracy: 0.6296
Epoch 18/20
78/78 [==============================] - 0s 62us/step - loss: 1.4330 - accuracy: 0.7179 - val_loss: 1.4096 - val_accuracy: 0.6667
Epoch 19/20
78/78 [==============================] - 0s 43us/step - loss: 1.3966 - accuracy: 0.7308 - val_loss: 1.3695 - val_accuracy: 0.7407
Epoch 20/20
78/78 [==============================] - 0s 68us/step - loss: 1.3607 - accuracy: 0.8077 - val_loss: 1.3278 - val_accuracy: 0.7778
45/45 [==============================] - 0s 76us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  20
Neurons or Units:  128
Test score: 1.3010031700134277
Test accuracy: 0.8444444537162781

Model: "sequential_54"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_160 (Dense)            (None, 256)               1280      
_________________________________________________________________
activation_160 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_161 (Dense)            (None, 256)               65792     
_________________________________________________________________
activation_161 (Activation)  (None, 256)               0         
_________________________________________________________________
dense_162 (Dense)            (None, 3)                 771       
_________________________________________________________________
activation_162 (Activation)  (None, 3)                 0         
=================================================================
Total params: 67,843
Trainable params: 67,843
Non-trainable params: 0
_________________________________________________________________
Train on 78 samples, validate on 27 samples
Epoch 1/20
78/78 [==============================] - 0s 2ms/step - loss: 3.9109 - accuracy: 0.3077 - val_loss: 3.7773 - val_accuracy: 0.2593
Epoch 2/20
78/78 [==============================] - 0s 88us/step - loss: 3.7095 - accuracy: 0.3718 - val_loss: 3.6473 - val_accuracy: 0.2593
Epoch 3/20
78/78 [==============================] - 0s 56us/step - loss: 3.5556 - accuracy: 0.3718 - val_loss: 3.4186 - val_accuracy: 0.2963
Epoch 4/20
78/78 [==============================] - 0s 50us/step - loss: 3.3622 - accuracy: 0.5256 - val_loss: 3.2128 - val_accuracy: 0.9630
Epoch 5/20
78/78 [==============================] - 0s 90us/step - loss: 3.2022 - accuracy: 0.9103 - val_loss: 3.0561 - val_accuracy: 1.0000
Epoch 6/20
78/78 [==============================] - 0s 142us/step - loss: 3.0569 - accuracy: 0.9615 - val_loss: 2.9233 - val_accuracy: 0.6667
Epoch 7/20
78/78 [==============================] - 0s 66us/step - loss: 2.9026 - accuracy: 0.7821 - val_loss: 2.8141 - val_accuracy: 0.5926
Epoch 8/20
78/78 [==============================] - 0s 80us/step - loss: 2.7709 - accuracy: 0.6795 - val_loss: 2.6873 - val_accuracy: 0.6296
Epoch 9/20
78/78 [==============================] - 0s 62us/step - loss: 2.6444 - accuracy: 0.6923 - val_loss: 2.5355 - val_accuracy: 0.7037
Epoch 10/20
78/78 [==============================] - 0s 55us/step - loss: 2.5147 - accuracy: 0.8077 - val_loss: 2.3946 - val_accuracy: 1.0000
Epoch 11/20
78/78 [==============================] - 0s 94us/step - loss: 2.4021 - accuracy: 0.9359 - val_loss: 2.2815 - val_accuracy: 1.0000
Epoch 12/20
78/78 [==============================] - 0s 65us/step - loss: 2.3021 - accuracy: 0.9487 - val_loss: 2.1864 - val_accuracy: 1.0000
Epoch 13/20
78/78 [==============================] - 0s 84us/step - loss: 2.2005 - accuracy: 0.9359 - val_loss: 2.1067 - val_accuracy: 0.9259
Epoch 14/20
78/78 [==============================] - 0s 87us/step - loss: 2.1100 - accuracy: 0.8718 - val_loss: 2.0218 - val_accuracy: 0.9259
Epoch 15/20
78/78 [==============================] - 0s 76us/step - loss: 2.0253 - accuracy: 0.8718 - val_loss: 1.9224 - val_accuracy: 1.0000
Epoch 16/20
78/78 [==============================] - 0s 51us/step - loss: 1.9393 - accuracy: 0.9359 - val_loss: 1.8307 - val_accuracy: 1.0000
Epoch 17/20
78/78 [==============================] - 0s 102us/step - loss: 1.8632 - accuracy: 0.9487 - val_loss: 1.7526 - val_accuracy: 1.0000
Epoch 18/20
78/78 [==============================] - 0s 59us/step - loss: 1.7900 - accuracy: 0.9615 - val_loss: 1.6851 - val_accuracy: 1.0000
Epoch 19/20
78/78 [==============================] - 0s 100us/step - loss: 1.7170 - accuracy: 0.9487 - val_loss: 1.6251 - val_accuracy: 1.0000
Epoch 20/20
78/78 [==============================] - 0s 79us/step - loss: 1.6522 - accuracy: 0.9359 - val_loss: 1.5573 - val_accuracy: 1.0000
45/45 [==============================] - 0s 99us/step

Optimizers:  <keras.optimizers.Adam object at 0x14771c590>
Epoch Sizes:  20
Neurons or Units:  256
Test score: 1.5625050597720676
Test accuracy: 0.9555555582046509

[0.35555556416511536, 0.5777778029441833, 0.31111112236976624, 0.46666666865348816, 0.5111111402511597, 0.6888889074325562, 0.6888889074325562, 0.6888889074325562, 0.6888889074325562, 0.6888889074325562, 0.8666666746139526, 0.6888889074325562, 0.6222222447395325, 0.800000011920929, 0.9777777791023254, 0.6888889074325562, 1.0, 0.8666666746139526, 0.4444444477558136, 0.6888889074325562, 0.31111112236976624, 0.6888889074325562, 0.6888889074325562, 0.6888889074325562, 0.6888889074325562, 0.8444444537162781, 0.9555555582046509]

Execution Time 18.440472841262817 seconds: