from car_speech.fname_processing import load_fnames
from car_speech.pipeline import *

import string
from random import shuffle
from copy import deepcopy
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import tensorflow as tf
from tensorflow.keras.layers.experimental import preprocessing
from tensorflow.keras import layers
from tensorflow.keras import models
from sklearn.model_selection import train_test_split, KFold

Configuration

DATASET_TYPE = 'digits' # 'digits' or 'letters' or 'mixed'
LEVEL_NAME = 'IDL' # 'IDL' or '35U' or '35D' or '55U' or '55D'

EPOCHS = 100

if DATASET_TYPE == 'digits':
    label_strings = np.array([str(num) for num in range(0,10)])
    fname_str = 'digit'
elif DATASET_TYPE == 'letters':
    label_strings = np.array(list(string.ascii_uppercase))
    fname_str = 'letter'
elif DATASET_TYPE == 'mixed':
    label_strings = np.array([str(num) for num in range(0,10)] + list(string.ascii_uppercase))
    fname_str = 'mixed'
    
# load classified filenames
filenames = load_fnames('noise_levels/' + fname_str + '_noise_levels/' + LEVEL_NAME + '.data')
num_samples = len(filenames)
print('number of files:', len(filenames))

# shuffle
shuffle(filenames)

fold_no = 1
acc_per_fold = []

number of files: 2677

Loop for 10-fold

beg_ratio = 0
while beg_ratio < 0.9:
    test_beg = int(beg_ratio*num_samples)
    test_end = int((beg_ratio+0.1)*num_samples)
    
    fnames_copy = deepcopy(filenames)
    test_files = fnames_copy[test_beg:test_end]
    del fnames_copy[test_beg:test_end]
    
    val_len = len(test_files)
    val_files = fnames_copy[-val_len:]
    del fnames_copy[-val_len:]
    
    train_files = fnames_copy
    
    beg_ratio += 0.1
    
    train_files = shuffle_data(train_files)
    val_files = shuffle_data(val_files)
    test_files = shuffle_data(test_files)
    

    # Process data using the combined pipeline
    spectrogram_ds = preprocess_dataset(train_files, DATASET_TYPE)
    train_ds = spectrogram_ds
    val_ds = preprocess_dataset(val_files, DATASET_TYPE)
    test_ds = preprocess_dataset(test_files, DATASET_TYPE)
    print("Pipeline Completed")
    
    # batch
    batch_size = 64
    train_ds = train_ds.batch(batch_size)
    val_ds = val_ds.batch(batch_size)
    
    AUTOTUNE = tf.data.experimental.AUTOTUNE
    train_ds = train_ds.cache().prefetch(AUTOTUNE)
    val_ds = val_ds.cache().prefetch(AUTOTUNE)
    
    # model
    for spectrogram, _ in spectrogram_ds.take(1):
        input_shape = spectrogram.shape
#     print('Input shape:', input_shape)
    num_labels = len(label_strings)

    norm_layer = preprocessing.Normalization()
    norm_layer.adapt(spectrogram_ds.map(lambda x, _: x))

#     model = models.Sequential([
#         layers.Input(shape=input_shape),
#         preprocessing.Resizing(32, 32), 
#         norm_layer,
#         layers.Conv2D(32, 3, activation='relu'),
#         layers.Conv2D(64, 3, activation='relu'),
#         layers.MaxPooling2D(),
#         layers.Dropout(0.25),
#         layers.Flatten(),
#         layers.Dense(128, activation='relu'),
#         layers.Dropout(0.5),
#         layers.Dense(num_labels),
#     ])

    model = models.Sequential([
        layers.Input(shape=input_shape),
        preprocessing.Resizing(32, 32), 
        norm_layer,
        layers.Conv2D(128, 3, activation='relu'),
        layers.MaxPooling2D(),
        layers.Dropout(0.25),
        layers.Conv2D(128, 3, activation='relu'),
        layers.MaxPooling2D(),
        layers.Dropout(0.25),
        layers.Conv2D(128, 3, activation='relu'),
        layers.MaxPooling2D(),
        layers.Dropout(0.25),
        layers.Flatten(),
        layers.Dense(128, activation='relu'),
        layers.Dropout(0.5),
        layers.Dense(num_labels),
    ])
    
    model.compile(
        optimizer=tf.keras.optimizers.Adam(),
        loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
        metrics=['accuracy'],
    )
    
    # Train
    history = model.fit(
        train_ds, 
        validation_data=val_ds,  
        epochs=EPOCHS,
        callbacks=tf.keras.callbacks.EarlyStopping(verbose=1, patience=3),
    )
    
    # Test
    test_audio = []
    test_labels = []

    for audio, label in test_ds:
        test_audio.append(audio.numpy())
        test_labels.append(label.numpy())

    test_audio = np.array(test_audio)
    test_labels = np.array(test_labels)
    
    y_pred = np.argmax(model.predict(test_audio), axis=1)
    y_true = test_labels

    test_acc = sum(y_pred == y_true) / len(y_true)
    print(f'Fold {fold_no} - Test set accuracy: {test_acc:.0%}')
    acc_per_fold.append(round(test_acc, 2))
    fold_no += 1

print(acc_per_fold)
print('mean score:', round(np.mean(acc_per_fold), 2))

Pipeline Completed
Epoch 1/100
34/34 [==============================] - 6s 174ms/step - loss: 3.2555 - accuracy: 0.0532 - val_loss: 3.2160 - val_accuracy: 0.0487
Epoch 2/100
34/34 [==============================] - 4s 132ms/step - loss: 3.1845 - accuracy: 0.0700 - val_loss: 3.0995 - val_accuracy: 0.0787
Epoch 3/100
34/34 [==============================] - 4s 125ms/step - loss: 3.0935 - accuracy: 0.0849 - val_loss: 3.0073 - val_accuracy: 0.0974
Epoch 4/100
34/34 [==============================] - 4s 126ms/step - loss: 3.0126 - accuracy: 0.0980 - val_loss: 2.9042 - val_accuracy: 0.1199
Epoch 5/100
34/34 [==============================] - 4s 118ms/step - loss: 2.9480 - accuracy: 0.1134 - val_loss: 2.7988 - val_accuracy: 0.1386
Epoch 6/100
34/34 [==============================] - 5s 134ms/step - loss: 2.8675 - accuracy: 0.1321 - val_loss: 2.7338 - val_accuracy: 0.1536
Epoch 7/100
34/34 [==============================] - 5s 139ms/step - loss: 2.7600 - accuracy: 0.1475 - val_loss: 2.6301 - val_accuracy: 0.1723
Epoch 8/100
34/34 [==============================] - 4s 132ms/step - loss: 2.6644 - accuracy: 0.1727 - val_loss: 2.5235 - val_accuracy: 0.1835
Epoch 9/100
34/34 [==============================] - 5s 155ms/step - loss: 2.5892 - accuracy: 0.1913 - val_loss: 2.4457 - val_accuracy: 0.2547
Epoch 10/100
34/34 [==============================] - 5s 135ms/step - loss: 2.4967 - accuracy: 0.2142 - val_loss: 2.3813 - val_accuracy: 0.2434
Epoch 11/100
34/34 [==============================] - 5s 133ms/step - loss: 2.3975 - accuracy: 0.2408 - val_loss: 2.2852 - val_accuracy: 0.2547
Epoch 12/100
34/34 [==============================] - 4s 126ms/step - loss: 2.3294 - accuracy: 0.2552 - val_loss: 2.2137 - val_accuracy: 0.2959
Epoch 13/100
34/34 [==============================] - 4s 126ms/step - loss: 2.2316 - accuracy: 0.2800 - val_loss: 2.1292 - val_accuracy: 0.3371
Epoch 14/100
34/34 [==============================] - 4s 129ms/step - loss: 2.1795 - accuracy: 0.3056 - val_loss: 2.0842 - val_accuracy: 0.3521
Epoch 15/100
34/34 [==============================] - 6s 167ms/step - loss: 2.1368 - accuracy: 0.2907 - val_loss: 2.0203 - val_accuracy: 0.3296
Epoch 16/100
34/34 [==============================] - 5s 154ms/step - loss: 2.0308 - accuracy: 0.3308 - val_loss: 1.9655 - val_accuracy: 0.3745
Epoch 17/100
34/34 [==============================] - 5s 140ms/step - loss: 1.9703 - accuracy: 0.3537 - val_loss: 1.9107 - val_accuracy: 0.3596
Epoch 18/100
34/34 [==============================] - 5s 133ms/step - loss: 1.9355 - accuracy: 0.3621 - val_loss: 1.8525 - val_accuracy: 0.3933
Epoch 19/100
34/34 [==============================] - 4s 131ms/step - loss: 1.8588 - accuracy: 0.3682 - val_loss: 1.8453 - val_accuracy: 0.3670
Epoch 20/100
34/34 [==============================] - 4s 130ms/step - loss: 1.8340 - accuracy: 0.3803 - val_loss: 1.8238 - val_accuracy: 0.4232
Epoch 21/100
34/34 [==============================] - 5s 135ms/step - loss: 1.7585 - accuracy: 0.4106 - val_loss: 1.7902 - val_accuracy: 0.3970
Epoch 22/100
34/34 [==============================] - 5s 159ms/step - loss: 1.7125 - accuracy: 0.4195 - val_loss: 1.7775 - val_accuracy: 0.3745
Epoch 23/100
34/34 [==============================] - 4s 123ms/step - loss: 1.6946 - accuracy: 0.4172 - val_loss: 1.7812 - val_accuracy: 0.3858
Epoch 24/100
34/34 [==============================] - 4s 121ms/step - loss: 1.6298 - accuracy: 0.4615 - val_loss: 1.7240 - val_accuracy: 0.4270
Epoch 25/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6198 - accuracy: 0.4400 - val_loss: 1.7368 - val_accuracy: 0.4457
Epoch 26/100
34/34 [==============================] - 4s 125ms/step - loss: 1.5914 - accuracy: 0.4503 - val_loss: 1.7227 - val_accuracy: 0.4345
Epoch 27/100
34/34 [==============================] - 4s 125ms/step - loss: 1.5609 - accuracy: 0.4666 - val_loss: 1.6887 - val_accuracy: 0.4270
Epoch 28/100
34/34 [==============================] - 4s 125ms/step - loss: 1.5584 - accuracy: 0.4666 - val_loss: 1.7066 - val_accuracy: 0.3970
Epoch 29/100
34/34 [==============================] - 5s 138ms/step - loss: 1.4817 - accuracy: 0.4830 - val_loss: 1.6624 - val_accuracy: 0.4382
Epoch 30/100
34/34 [==============================] - 5s 150ms/step - loss: 1.4239 - accuracy: 0.5114 - val_loss: 1.6534 - val_accuracy: 0.4232
Epoch 31/100
34/34 [==============================] - 5s 148ms/step - loss: 1.4353 - accuracy: 0.5058 - val_loss: 1.6566 - val_accuracy: 0.4270
Epoch 32/100
34/34 [==============================] - 4s 130ms/step - loss: 1.4179 - accuracy: 0.5147 - val_loss: 1.6464 - val_accuracy: 0.4419
Epoch 33/100
34/34 [==============================] - 4s 130ms/step - loss: 1.3836 - accuracy: 0.5245 - val_loss: 1.6141 - val_accuracy: 0.4494
Epoch 34/100
34/34 [==============================] - 4s 131ms/step - loss: 1.3350 - accuracy: 0.5296 - val_loss: 1.5975 - val_accuracy: 0.4419
Epoch 35/100
34/34 [==============================] - 4s 132ms/step - loss: 1.3630 - accuracy: 0.5226 - val_loss: 1.6118 - val_accuracy: 0.4494
Epoch 36/100
34/34 [==============================] - 5s 160ms/step - loss: 1.3185 - accuracy: 0.5362 - val_loss: 1.6292 - val_accuracy: 0.4494
Epoch 37/100
34/34 [==============================] - 5s 144ms/step - loss: 1.3006 - accuracy: 0.5474 - val_loss: 1.6150 - val_accuracy: 0.4345
Epoch 00037: early stopping
Fold 1 - Test set accuracy: 48%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 157ms/step - loss: 3.2635 - accuracy: 0.0369 - val_loss: 3.2337 - val_accuracy: 0.0448
Epoch 2/100
34/34 [==============================] - 4s 115ms/step - loss: 3.1923 - accuracy: 0.0570 - val_loss: 3.0986 - val_accuracy: 0.0672
Epoch 3/100
34/34 [==============================] - 4s 125ms/step - loss: 3.0993 - accuracy: 0.0887 - val_loss: 2.9721 - val_accuracy: 0.0970
Epoch 4/100
34/34 [==============================] - 4s 125ms/step - loss: 2.9987 - accuracy: 0.0986 - val_loss: 2.8529 - val_accuracy: 0.1343
Epoch 5/100
34/34 [==============================] - 4s 130ms/step - loss: 2.9297 - accuracy: 0.1191 - val_loss: 2.7741 - val_accuracy: 0.1269
Epoch 6/100
34/34 [==============================] - 4s 131ms/step - loss: 2.8765 - accuracy: 0.1177 - val_loss: 2.7424 - val_accuracy: 0.1791
Epoch 7/100
34/34 [==============================] - 4s 127ms/step - loss: 2.7730 - accuracy: 0.1513 - val_loss: 2.6010 - val_accuracy: 0.1940
Epoch 8/100
34/34 [==============================] - 4s 131ms/step - loss: 2.6788 - accuracy: 0.1803 - val_loss: 2.5227 - val_accuracy: 0.1903
Epoch 9/100
34/34 [==============================] - 5s 135ms/step - loss: 2.5999 - accuracy: 0.1798 - val_loss: 2.5184 - val_accuracy: 0.2127
Epoch 10/100
34/34 [==============================] - 4s 126ms/step - loss: 2.5485 - accuracy: 0.2041 - val_loss: 2.4522 - val_accuracy: 0.2127
Epoch 11/100
34/34 [==============================] - 4s 125ms/step - loss: 2.4187 - accuracy: 0.2261 - val_loss: 2.4272 - val_accuracy: 0.2276
Epoch 12/100
34/34 [==============================] - 4s 131ms/step - loss: 2.3546 - accuracy: 0.2368 - val_loss: 2.2693 - val_accuracy: 0.2463
Epoch 13/100
34/34 [==============================] - 4s 126ms/step - loss: 2.2897 - accuracy: 0.2527 - val_loss: 2.2471 - val_accuracy: 0.2687
Epoch 14/100
34/34 [==============================] - 4s 125ms/step - loss: 2.2315 - accuracy: 0.2723 - val_loss: 2.1794 - val_accuracy: 0.2836
Epoch 15/100
34/34 [==============================] - 4s 128ms/step - loss: 2.1485 - accuracy: 0.3134 - val_loss: 2.1600 - val_accuracy: 0.3097
Epoch 16/100
34/34 [==============================] - 4s 130ms/step - loss: 2.0998 - accuracy: 0.3083 - val_loss: 2.0515 - val_accuracy: 0.3396
Epoch 17/100
34/34 [==============================] - 5s 138ms/step - loss: 2.0497 - accuracy: 0.3185 - val_loss: 2.0302 - val_accuracy: 0.2985
Epoch 18/100
34/34 [==============================] - 4s 125ms/step - loss: 2.0057 - accuracy: 0.3302 - val_loss: 1.9602 - val_accuracy: 0.3358
Epoch 19/100
34/34 [==============================] - 4s 126ms/step - loss: 1.9468 - accuracy: 0.3456 - val_loss: 1.9266 - val_accuracy: 0.3470
Epoch 20/100
34/34 [==============================] - 4s 128ms/step - loss: 1.8912 - accuracy: 0.3699 - val_loss: 1.9168 - val_accuracy: 0.3470
Epoch 21/100
34/34 [==============================] - 4s 126ms/step - loss: 1.8710 - accuracy: 0.3741 - val_loss: 1.8806 - val_accuracy: 0.3694
Epoch 22/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7884 - accuracy: 0.3914 - val_loss: 1.8565 - val_accuracy: 0.3731
Epoch 23/100
34/34 [==============================] - 5s 133ms/step - loss: 1.7474 - accuracy: 0.4101 - val_loss: 1.7856 - val_accuracy: 0.3769
Epoch 24/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7314 - accuracy: 0.4208 - val_loss: 1.8156 - val_accuracy: 0.3881
Epoch 25/100
34/34 [==============================] - 4s 118ms/step - loss: 1.7158 - accuracy: 0.4138 - val_loss: 1.7560 - val_accuracy: 0.4142
Epoch 26/100
34/34 [==============================] - 5s 135ms/step - loss: 1.6849 - accuracy: 0.4162 - val_loss: 1.7770 - val_accuracy: 0.4030
Epoch 27/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6436 - accuracy: 0.4180 - val_loss: 1.7245 - val_accuracy: 0.3918
Epoch 28/100
34/34 [==============================] - 4s 125ms/step - loss: 1.6135 - accuracy: 0.4549 - val_loss: 1.7407 - val_accuracy: 0.4030
Epoch 29/100
34/34 [==============================] - 4s 123ms/step - loss: 1.5815 - accuracy: 0.4507 - val_loss: 1.6988 - val_accuracy: 0.4142
Epoch 30/100
34/34 [==============================] - 4s 125ms/step - loss: 1.5816 - accuracy: 0.4465 - val_loss: 1.7169 - val_accuracy: 0.3843
Epoch 31/100
34/34 [==============================] - 4s 123ms/step - loss: 1.5648 - accuracy: 0.4437 - val_loss: 1.7093 - val_accuracy: 0.4142
Epoch 32/100
34/34 [==============================] - 4s 127ms/step - loss: 1.4998 - accuracy: 0.4787 - val_loss: 1.6692 - val_accuracy: 0.4254
Epoch 33/100
34/34 [==============================] - 4s 125ms/step - loss: 1.4824 - accuracy: 0.4876 - val_loss: 1.6742 - val_accuracy: 0.4142
Epoch 34/100
34/34 [==============================] - 4s 132ms/step - loss: 1.4755 - accuracy: 0.4750 - val_loss: 1.6568 - val_accuracy: 0.4440
Epoch 35/100
34/34 [==============================] - 4s 123ms/step - loss: 1.4196 - accuracy: 0.4881 - val_loss: 1.6952 - val_accuracy: 0.4701
Epoch 36/100
34/34 [==============================] - 4s 125ms/step - loss: 1.3980 - accuracy: 0.5082 - val_loss: 1.6949 - val_accuracy: 0.4478
Epoch 37/100
34/34 [==============================] - 4s 127ms/step - loss: 1.4384 - accuracy: 0.4867 - val_loss: 1.6595 - val_accuracy: 0.4403
Epoch 00037: early stopping
Fold 2 - Test set accuracy: 43%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 160ms/step - loss: 3.2602 - accuracy: 0.0518 - val_loss: 3.2360 - val_accuracy: 0.0634
Epoch 2/100
34/34 [==============================] - 4s 124ms/step - loss: 3.2107 - accuracy: 0.0556 - val_loss: 3.1230 - val_accuracy: 0.0560
Epoch 3/100
34/34 [==============================] - 4s 126ms/step - loss: 3.1349 - accuracy: 0.0757 - val_loss: 3.0136 - val_accuracy: 0.0784
Epoch 4/100
34/34 [==============================] - 4s 127ms/step - loss: 3.0454 - accuracy: 0.0953 - val_loss: 2.8814 - val_accuracy: 0.1045
Epoch 5/100
34/34 [==============================] - 5s 139ms/step - loss: 2.9808 - accuracy: 0.1037 - val_loss: 2.8276 - val_accuracy: 0.1866
Epoch 6/100
34/34 [==============================] - 4s 127ms/step - loss: 2.8531 - accuracy: 0.1284 - val_loss: 2.7055 - val_accuracy: 0.2052
Epoch 7/100
34/34 [==============================] - 4s 127ms/step - loss: 2.7482 - accuracy: 0.1663 - val_loss: 2.5776 - val_accuracy: 0.2463
Epoch 8/100
34/34 [==============================] - 4s 125ms/step - loss: 2.6147 - accuracy: 0.1831 - val_loss: 2.4634 - val_accuracy: 0.2276
Epoch 9/100
34/34 [==============================] - 4s 114ms/step - loss: 2.5217 - accuracy: 0.2032 - val_loss: 2.3525 - val_accuracy: 0.2612
Epoch 10/100
34/34 [==============================] - 4s 114ms/step - loss: 2.4450 - accuracy: 0.2298 - val_loss: 2.2939 - val_accuracy: 0.2836
Epoch 11/100
34/34 [==============================] - 4s 115ms/step - loss: 2.3561 - accuracy: 0.2541 - val_loss: 2.2336 - val_accuracy: 0.2761
Epoch 12/100
34/34 [==============================] - 4s 123ms/step - loss: 2.2535 - accuracy: 0.2774 - val_loss: 2.1523 - val_accuracy: 0.2985
Epoch 13/100
34/34 [==============================] - 4s 125ms/step - loss: 2.1990 - accuracy: 0.2947 - val_loss: 2.0940 - val_accuracy: 0.2948
Epoch 14/100
34/34 [==============================] - 4s 127ms/step - loss: 2.1403 - accuracy: 0.2957 - val_loss: 2.0573 - val_accuracy: 0.2873
Epoch 15/100
34/34 [==============================] - 4s 128ms/step - loss: 2.0688 - accuracy: 0.3139 - val_loss: 1.9646 - val_accuracy: 0.3396
Epoch 16/100
34/34 [==============================] - 4s 125ms/step - loss: 2.0224 - accuracy: 0.3298 - val_loss: 1.9983 - val_accuracy: 0.3619
Epoch 17/100
34/34 [==============================] - 4s 126ms/step - loss: 1.9678 - accuracy: 0.3461 - val_loss: 1.9237 - val_accuracy: 0.3545
Epoch 18/100
34/34 [==============================] - 4s 126ms/step - loss: 1.8881 - accuracy: 0.3723 - val_loss: 1.9198 - val_accuracy: 0.3470
Epoch 19/100
34/34 [==============================] - 4s 127ms/step - loss: 1.8558 - accuracy: 0.3807 - val_loss: 1.8770 - val_accuracy: 0.4030
Epoch 20/100
34/34 [==============================] - 4s 127ms/step - loss: 1.7999 - accuracy: 0.4026 - val_loss: 1.7978 - val_accuracy: 0.3843
Epoch 21/100
34/34 [==============================] - 4s 127ms/step - loss: 1.7794 - accuracy: 0.3984 - val_loss: 1.8096 - val_accuracy: 0.4067
Epoch 22/100
34/34 [==============================] - 4s 119ms/step - loss: 1.7063 - accuracy: 0.4274 - val_loss: 1.7703 - val_accuracy: 0.3806
Epoch 23/100
34/34 [==============================] - 4s 125ms/step - loss: 1.6987 - accuracy: 0.4143 - val_loss: 1.7525 - val_accuracy: 0.3806
Epoch 24/100
34/34 [==============================] - 4s 124ms/step - loss: 1.6355 - accuracy: 0.4418 - val_loss: 1.8045 - val_accuracy: 0.3806
Epoch 25/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6391 - accuracy: 0.4404 - val_loss: 1.7394 - val_accuracy: 0.3955
Epoch 26/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6115 - accuracy: 0.4526 - val_loss: 1.7107 - val_accuracy: 0.4030
Epoch 27/100
34/34 [==============================] - 4s 126ms/step - loss: 1.5514 - accuracy: 0.4657 - val_loss: 1.6656 - val_accuracy: 0.4030
Epoch 28/100
34/34 [==============================] - 4s 126ms/step - loss: 1.5168 - accuracy: 0.4769 - val_loss: 1.7033 - val_accuracy: 0.3769
Epoch 29/100
34/34 [==============================] - 4s 125ms/step - loss: 1.4997 - accuracy: 0.4909 - val_loss: 1.7227 - val_accuracy: 0.3955
Epoch 30/100
34/34 [==============================] - 4s 128ms/step - loss: 1.5125 - accuracy: 0.4839 - val_loss: 1.6730 - val_accuracy: 0.4328
Epoch 00030: early stopping
Fold 3 - Test set accuracy: 40%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 160ms/step - loss: 3.2662 - accuracy: 0.0401 - val_loss: 3.2353 - val_accuracy: 0.0449
Epoch 2/100
34/34 [==============================] - 4s 130ms/step - loss: 3.2135 - accuracy: 0.0574 - val_loss: 3.1285 - val_accuracy: 0.0936
Epoch 3/100
34/34 [==============================] - 5s 133ms/step - loss: 3.1213 - accuracy: 0.0845 - val_loss: 3.0166 - val_accuracy: 0.1199
Epoch 4/100
34/34 [==============================] - 4s 130ms/step - loss: 3.0284 - accuracy: 0.0915 - val_loss: 2.9143 - val_accuracy: 0.1049
Epoch 5/100
34/34 [==============================] - 4s 125ms/step - loss: 2.9587 - accuracy: 0.1008 - val_loss: 2.8404 - val_accuracy: 0.1161
Epoch 6/100
34/34 [==============================] - 4s 129ms/step - loss: 2.8539 - accuracy: 0.1311 - val_loss: 2.7454 - val_accuracy: 0.1536
Epoch 7/100
34/34 [==============================] - 4s 129ms/step - loss: 2.7706 - accuracy: 0.1517 - val_loss: 2.6426 - val_accuracy: 0.1873
Epoch 8/100
34/34 [==============================] - 4s 127ms/step - loss: 2.6930 - accuracy: 0.1671 - val_loss: 2.5384 - val_accuracy: 0.1948
Epoch 9/100
34/34 [==============================] - 4s 132ms/step - loss: 2.6035 - accuracy: 0.1825 - val_loss: 2.4528 - val_accuracy: 0.2584
Epoch 10/100
34/34 [==============================] - 4s 127ms/step - loss: 2.5125 - accuracy: 0.2133 - val_loss: 2.3889 - val_accuracy: 0.2659
Epoch 11/100
34/34 [==============================] - 4s 126ms/step - loss: 2.4191 - accuracy: 0.2287 - val_loss: 2.3631 - val_accuracy: 0.2247
Epoch 12/100
34/34 [==============================] - 4s 125ms/step - loss: 2.3511 - accuracy: 0.2515 - val_loss: 2.3111 - val_accuracy: 0.2584
Epoch 13/100
34/34 [==============================] - 4s 125ms/step - loss: 2.2848 - accuracy: 0.2613 - val_loss: 2.1911 - val_accuracy: 0.2959
Epoch 14/100
34/34 [==============================] - 4s 125ms/step - loss: 2.2069 - accuracy: 0.2912 - val_loss: 2.1609 - val_accuracy: 0.3146
Epoch 15/100
34/34 [==============================] - 4s 126ms/step - loss: 2.1582 - accuracy: 0.2944 - val_loss: 2.1292 - val_accuracy: 0.3184
Epoch 16/100
34/34 [==============================] - 4s 132ms/step - loss: 2.0908 - accuracy: 0.3182 - val_loss: 2.0662 - val_accuracy: 0.3296
Epoch 17/100
34/34 [==============================] - 4s 130ms/step - loss: 2.0343 - accuracy: 0.3271 - val_loss: 2.0863 - val_accuracy: 0.3296
Epoch 18/100
34/34 [==============================] - 4s 126ms/step - loss: 1.9439 - accuracy: 0.3500 - val_loss: 1.9550 - val_accuracy: 0.3670
Epoch 19/100
34/34 [==============================] - 4s 128ms/step - loss: 1.9150 - accuracy: 0.3560 - val_loss: 1.9505 - val_accuracy: 0.3895
Epoch 20/100
34/34 [==============================] - 5s 135ms/step - loss: 1.8709 - accuracy: 0.3724 - val_loss: 1.8893 - val_accuracy: 0.3933
Epoch 21/100
34/34 [==============================] - 4s 132ms/step - loss: 1.8423 - accuracy: 0.3677 - val_loss: 1.8688 - val_accuracy: 0.4007
Epoch 22/100
34/34 [==============================] - 5s 135ms/step - loss: 1.7817 - accuracy: 0.4130 - val_loss: 1.8334 - val_accuracy: 0.4270
Epoch 23/100
34/34 [==============================] - 4s 131ms/step - loss: 1.7333 - accuracy: 0.4167 - val_loss: 1.8058 - val_accuracy: 0.4045
Epoch 24/100
34/34 [==============================] - 4s 130ms/step - loss: 1.7135 - accuracy: 0.4106 - val_loss: 1.7826 - val_accuracy: 0.4045
Epoch 25/100
34/34 [==============================] - 4s 130ms/step - loss: 1.6346 - accuracy: 0.4466 - val_loss: 1.7971 - val_accuracy: 0.3745
Epoch 26/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6292 - accuracy: 0.4372 - val_loss: 1.7454 - val_accuracy: 0.4195
Epoch 27/100
34/34 [==============================] - 4s 125ms/step - loss: 1.5902 - accuracy: 0.4428 - val_loss: 1.7327 - val_accuracy: 0.4270
Epoch 28/100
34/34 [==============================] - 4s 125ms/step - loss: 1.5658 - accuracy: 0.4727 - val_loss: 1.7117 - val_accuracy: 0.4607
Epoch 29/100
34/34 [==============================] - 4s 128ms/step - loss: 1.5208 - accuracy: 0.4764 - val_loss: 1.7288 - val_accuracy: 0.4382
Epoch 30/100
34/34 [==============================] - 5s 133ms/step - loss: 1.5091 - accuracy: 0.4778 - val_loss: 1.7516 - val_accuracy: 0.4120
Epoch 31/100
34/34 [==============================] - 4s 123ms/step - loss: 1.5125 - accuracy: 0.4858 - val_loss: 1.6692 - val_accuracy: 0.4382
Epoch 32/100
34/34 [==============================] - 4s 114ms/step - loss: 1.4878 - accuracy: 0.4760 - val_loss: 1.7314 - val_accuracy: 0.4270
Epoch 33/100
34/34 [==============================] - 4s 115ms/step - loss: 1.4443 - accuracy: 0.5082 - val_loss: 1.6318 - val_accuracy: 0.4644
Epoch 34/100
34/34 [==============================] - 4s 115ms/step - loss: 1.4147 - accuracy: 0.5026 - val_loss: 1.6183 - val_accuracy: 0.4457
Epoch 35/100
34/34 [==============================] - 4s 125ms/step - loss: 1.4106 - accuracy: 0.5091 - val_loss: 1.6358 - val_accuracy: 0.4232
Epoch 36/100
34/34 [==============================] - 4s 126ms/step - loss: 1.3746 - accuracy: 0.5175 - val_loss: 1.6135 - val_accuracy: 0.4419
Epoch 37/100
34/34 [==============================] - 4s 127ms/step - loss: 1.3662 - accuracy: 0.5156 - val_loss: 1.5874 - val_accuracy: 0.4719
Epoch 38/100
34/34 [==============================] - 4s 126ms/step - loss: 1.3179 - accuracy: 0.5404 - val_loss: 1.6342 - val_accuracy: 0.4120
Epoch 39/100
34/34 [==============================] - 4s 125ms/step - loss: 1.2955 - accuracy: 0.5488 - val_loss: 1.5764 - val_accuracy: 0.4494
Epoch 40/100
34/34 [==============================] - 4s 126ms/step - loss: 1.2794 - accuracy: 0.5380 - val_loss: 1.6133 - val_accuracy: 0.4457
Epoch 41/100
34/34 [==============================] - 4s 125ms/step - loss: 1.2385 - accuracy: 0.5791 - val_loss: 1.5526 - val_accuracy: 0.4757
Epoch 42/100
34/34 [==============================] - 4s 131ms/step - loss: 1.2340 - accuracy: 0.5842 - val_loss: 1.6459 - val_accuracy: 0.4120
Epoch 43/100
34/34 [==============================] - 5s 135ms/step - loss: 1.2253 - accuracy: 0.5623 - val_loss: 1.5847 - val_accuracy: 0.4307
Epoch 44/100
34/34 [==============================] - 4s 130ms/step - loss: 1.2301 - accuracy: 0.5702 - val_loss: 1.5877 - val_accuracy: 0.4719
Epoch 00044: early stopping
Fold 4 - Test set accuracy: 43%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 158ms/step - loss: 3.2667 - accuracy: 0.0416 - val_loss: 3.2491 - val_accuracy: 0.0448
Epoch 2/100
34/34 [==============================] - 4s 128ms/step - loss: 3.2231 - accuracy: 0.0589 - val_loss: 3.1538 - val_accuracy: 0.0709
Epoch 3/100
34/34 [==============================] - 4s 126ms/step - loss: 3.1415 - accuracy: 0.0827 - val_loss: 3.0459 - val_accuracy: 0.1157
Epoch 4/100
34/34 [==============================] - 4s 132ms/step - loss: 3.0660 - accuracy: 0.0929 - val_loss: 2.9447 - val_accuracy: 0.1007
Epoch 5/100
34/34 [==============================] - 4s 126ms/step - loss: 2.9917 - accuracy: 0.1210 - val_loss: 2.8372 - val_accuracy: 0.1530
Epoch 6/100
34/34 [==============================] - 4s 129ms/step - loss: 2.8907 - accuracy: 0.1340 - val_loss: 2.7248 - val_accuracy: 0.2052
Epoch 7/100
34/34 [==============================] - 5s 135ms/step - loss: 2.7798 - accuracy: 0.1574 - val_loss: 2.6602 - val_accuracy: 0.2052
Epoch 8/100
34/34 [==============================] - 5s 137ms/step - loss: 2.7025 - accuracy: 0.1677 - val_loss: 2.5903 - val_accuracy: 0.2276
Epoch 9/100
34/34 [==============================] - 4s 128ms/step - loss: 2.5619 - accuracy: 0.2121 - val_loss: 2.4044 - val_accuracy: 0.3022
Epoch 10/100
34/34 [==============================] - 4s 128ms/step - loss: 2.4898 - accuracy: 0.2219 - val_loss: 2.3211 - val_accuracy: 0.2985
Epoch 11/100
34/34 [==============================] - 4s 125ms/step - loss: 2.3639 - accuracy: 0.2401 - val_loss: 2.2142 - val_accuracy: 0.3134
Epoch 12/100
34/34 [==============================] - 5s 133ms/step - loss: 2.2993 - accuracy: 0.2676 - val_loss: 2.1901 - val_accuracy: 0.2985
Epoch 13/100
34/34 [==============================] - 5s 134ms/step - loss: 2.2449 - accuracy: 0.2905 - val_loss: 2.1168 - val_accuracy: 0.3209
Epoch 14/100
34/34 [==============================] - 5s 139ms/step - loss: 2.1605 - accuracy: 0.2999 - val_loss: 1.9910 - val_accuracy: 0.3806
Epoch 15/100
34/34 [==============================] - 4s 128ms/step - loss: 2.0797 - accuracy: 0.3139 - val_loss: 2.0061 - val_accuracy: 0.3209
Epoch 16/100
34/34 [==============================] - 4s 125ms/step - loss: 2.0196 - accuracy: 0.3466 - val_loss: 1.9265 - val_accuracy: 0.3769
Epoch 17/100
34/34 [==============================] - 4s 129ms/step - loss: 1.9776 - accuracy: 0.3391 - val_loss: 1.9193 - val_accuracy: 0.3433
Epoch 18/100
34/34 [==============================] - 4s 127ms/step - loss: 1.9069 - accuracy: 0.3620 - val_loss: 1.8587 - val_accuracy: 0.3769
Epoch 19/100
34/34 [==============================] - 4s 126ms/step - loss: 1.8439 - accuracy: 0.3779 - val_loss: 1.8293 - val_accuracy: 0.3731
Epoch 20/100
34/34 [==============================] - 4s 128ms/step - loss: 1.8149 - accuracy: 0.3895 - val_loss: 1.8029 - val_accuracy: 0.3769
Epoch 21/100
34/34 [==============================] - 4s 126ms/step - loss: 1.8082 - accuracy: 0.3858 - val_loss: 1.7861 - val_accuracy: 0.3918
Epoch 22/100
34/34 [==============================] - 4s 125ms/step - loss: 1.7665 - accuracy: 0.4012 - val_loss: 1.7489 - val_accuracy: 0.4216
Epoch 23/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7138 - accuracy: 0.4213 - val_loss: 1.7137 - val_accuracy: 0.4328
Epoch 24/100
34/34 [==============================] - 4s 123ms/step - loss: 1.6326 - accuracy: 0.4367 - val_loss: 1.7099 - val_accuracy: 0.4291
Epoch 25/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6359 - accuracy: 0.4381 - val_loss: 1.6848 - val_accuracy: 0.4328
Epoch 26/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6062 - accuracy: 0.4675 - val_loss: 1.6807 - val_accuracy: 0.4142
Epoch 27/100
34/34 [==============================] - 4s 126ms/step - loss: 1.5800 - accuracy: 0.4587 - val_loss: 1.6395 - val_accuracy: 0.4366
Epoch 28/100
34/34 [==============================] - 4s 128ms/step - loss: 1.5578 - accuracy: 0.4596 - val_loss: 1.6069 - val_accuracy: 0.4403
Epoch 29/100
34/34 [==============================] - 4s 126ms/step - loss: 1.4795 - accuracy: 0.4909 - val_loss: 1.6020 - val_accuracy: 0.4515
Epoch 30/100
34/34 [==============================] - 4s 127ms/step - loss: 1.4857 - accuracy: 0.4946 - val_loss: 1.6100 - val_accuracy: 0.4291
Epoch 31/100
34/34 [==============================] - 4s 127ms/step - loss: 1.4686 - accuracy: 0.4876 - val_loss: 1.6144 - val_accuracy: 0.4478
Epoch 32/100
34/34 [==============================] - 4s 126ms/step - loss: 1.4465 - accuracy: 0.5044 - val_loss: 1.6063 - val_accuracy: 0.4552
Epoch 00032: early stopping
Fold 5 - Test set accuracy: 39%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 160ms/step - loss: 3.2672 - accuracy: 0.0364 - val_loss: 3.2514 - val_accuracy: 0.0373
Epoch 2/100
34/34 [==============================] - 4s 125ms/step - loss: 3.2381 - accuracy: 0.0546 - val_loss: 3.1719 - val_accuracy: 0.0560
Epoch 3/100
34/34 [==============================] - 4s 125ms/step - loss: 3.1688 - accuracy: 0.0780 - val_loss: 3.0701 - val_accuracy: 0.0933
Epoch 4/100
34/34 [==============================] - 5s 133ms/step - loss: 3.0888 - accuracy: 0.0901 - val_loss: 2.9710 - val_accuracy: 0.1082
Epoch 5/100
34/34 [==============================] - 5s 138ms/step - loss: 3.0173 - accuracy: 0.0906 - val_loss: 2.8568 - val_accuracy: 0.1194
Epoch 6/100
34/34 [==============================] - 4s 130ms/step - loss: 2.9251 - accuracy: 0.1214 - val_loss: 2.8180 - val_accuracy: 0.1269
Epoch 7/100
34/34 [==============================] - 4s 130ms/step - loss: 2.8415 - accuracy: 0.1345 - val_loss: 2.7054 - val_accuracy: 0.1716
Epoch 8/100
34/34 [==============================] - 4s 128ms/step - loss: 2.7579 - accuracy: 0.1467 - val_loss: 2.6322 - val_accuracy: 0.1978
Epoch 9/100
34/34 [==============================] - 4s 127ms/step - loss: 2.6750 - accuracy: 0.1630 - val_loss: 2.5316 - val_accuracy: 0.2575
Epoch 10/100
34/34 [==============================] - 5s 134ms/step - loss: 2.5584 - accuracy: 0.1873 - val_loss: 2.4439 - val_accuracy: 0.2425
Epoch 11/100
34/34 [==============================] - 4s 129ms/step - loss: 2.4745 - accuracy: 0.2116 - val_loss: 2.3937 - val_accuracy: 0.2948
Epoch 12/100
34/34 [==============================] - 4s 125ms/step - loss: 2.4085 - accuracy: 0.2461 - val_loss: 2.3011 - val_accuracy: 0.2948
Epoch 13/100
34/34 [==============================] - 4s 125ms/step - loss: 2.3547 - accuracy: 0.2499 - val_loss: 2.2325 - val_accuracy: 0.3097
Epoch 14/100
34/34 [==============================] - 4s 125ms/step - loss: 2.2540 - accuracy: 0.2756 - val_loss: 2.1390 - val_accuracy: 0.3246
Epoch 15/100
34/34 [==============================] - 4s 125ms/step - loss: 2.1760 - accuracy: 0.2924 - val_loss: 2.0999 - val_accuracy: 0.3470
Epoch 16/100
34/34 [==============================] - 4s 124ms/step - loss: 2.0973 - accuracy: 0.3176 - val_loss: 2.0725 - val_accuracy: 0.3545
Epoch 17/100
34/34 [==============================] - 4s 125ms/step - loss: 2.0517 - accuracy: 0.3260 - val_loss: 1.9733 - val_accuracy: 0.3619
Epoch 18/100
34/34 [==============================] - 4s 130ms/step - loss: 2.0207 - accuracy: 0.3288 - val_loss: 1.9383 - val_accuracy: 0.3657
Epoch 19/100
34/34 [==============================] - 4s 126ms/step - loss: 1.9707 - accuracy: 0.3419 - val_loss: 1.9221 - val_accuracy: 0.3731
Epoch 20/100
34/34 [==============================] - 4s 124ms/step - loss: 1.8885 - accuracy: 0.3695 - val_loss: 1.8890 - val_accuracy: 0.3694
Epoch 21/100
34/34 [==============================] - 4s 125ms/step - loss: 1.8416 - accuracy: 0.3830 - val_loss: 1.8371 - val_accuracy: 0.3993
Epoch 22/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7947 - accuracy: 0.3919 - val_loss: 1.8223 - val_accuracy: 0.3993
Epoch 23/100
34/34 [==============================] - 4s 125ms/step - loss: 1.7631 - accuracy: 0.3984 - val_loss: 1.7949 - val_accuracy: 0.3955
Epoch 24/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7420 - accuracy: 0.4171 - val_loss: 1.7796 - val_accuracy: 0.3806
Epoch 25/100
34/34 [==============================] - 4s 132ms/step - loss: 1.6992 - accuracy: 0.4222 - val_loss: 1.7558 - val_accuracy: 0.4216
Epoch 26/100
34/34 [==============================] - 4s 125ms/step - loss: 1.6725 - accuracy: 0.4306 - val_loss: 1.7290 - val_accuracy: 0.3843
Epoch 27/100
34/34 [==============================] - 5s 138ms/step - loss: 1.6057 - accuracy: 0.4362 - val_loss: 1.7186 - val_accuracy: 0.4104
Epoch 28/100
34/34 [==============================] - 5s 135ms/step - loss: 1.6203 - accuracy: 0.4428 - val_loss: 1.7001 - val_accuracy: 0.4216
Epoch 29/100
34/34 [==============================] - 5s 136ms/step - loss: 1.5819 - accuracy: 0.4512 - val_loss: 1.6539 - val_accuracy: 0.4366
Epoch 30/100
34/34 [==============================] - 5s 134ms/step - loss: 1.5266 - accuracy: 0.4713 - val_loss: 1.6312 - val_accuracy: 0.4179
Epoch 31/100
34/34 [==============================] - 4s 130ms/step - loss: 1.5084 - accuracy: 0.4657 - val_loss: 1.6788 - val_accuracy: 0.4104
Epoch 32/100
34/34 [==============================] - 4s 127ms/step - loss: 1.4603 - accuracy: 0.4918 - val_loss: 1.6212 - val_accuracy: 0.4515
Epoch 33/100
34/34 [==============================] - 4s 126ms/step - loss: 1.4797 - accuracy: 0.4895 - val_loss: 1.6242 - val_accuracy: 0.4216
Epoch 34/100
34/34 [==============================] - 4s 127ms/step - loss: 1.4100 - accuracy: 0.5026 - val_loss: 1.5913 - val_accuracy: 0.4664
Epoch 35/100
34/34 [==============================] - 4s 127ms/step - loss: 1.4094 - accuracy: 0.5147 - val_loss: 1.6621 - val_accuracy: 0.4403
Epoch 36/100
34/34 [==============================] - 4s 126ms/step - loss: 1.3758 - accuracy: 0.5194 - val_loss: 1.6314 - val_accuracy: 0.4403
Epoch 37/100
34/34 [==============================] - 4s 126ms/step - loss: 1.3784 - accuracy: 0.5142 - val_loss: 1.6309 - val_accuracy: 0.4403
Epoch 00037: early stopping
Fold 6 - Test set accuracy: 43%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 159ms/step - loss: 3.2650 - accuracy: 0.0373 - val_loss: 3.2462 - val_accuracy: 0.0524
Epoch 2/100
34/34 [==============================] - 4s 126ms/step - loss: 3.2206 - accuracy: 0.0625 - val_loss: 3.1509 - val_accuracy: 0.1049
Epoch 3/100
34/34 [==============================] - 4s 126ms/step - loss: 3.1378 - accuracy: 0.0681 - val_loss: 3.0487 - val_accuracy: 0.0974
Epoch 4/100
34/34 [==============================] - 4s 126ms/step - loss: 3.0414 - accuracy: 0.0807 - val_loss: 2.9849 - val_accuracy: 0.1124
Epoch 5/100
34/34 [==============================] - 4s 125ms/step - loss: 2.9551 - accuracy: 0.1003 - val_loss: 2.8266 - val_accuracy: 0.1386
Epoch 6/100
34/34 [==============================] - 4s 126ms/step - loss: 2.8777 - accuracy: 0.1209 - val_loss: 2.7420 - val_accuracy: 0.1311
Epoch 7/100
34/34 [==============================] - 4s 127ms/step - loss: 2.7832 - accuracy: 0.1437 - val_loss: 2.6606 - val_accuracy: 0.1798
Epoch 8/100
34/34 [==============================] - 4s 126ms/step - loss: 2.7108 - accuracy: 0.1540 - val_loss: 2.5505 - val_accuracy: 0.2434
Epoch 9/100
34/34 [==============================] - 4s 120ms/step - loss: 2.6186 - accuracy: 0.1839 - val_loss: 2.4615 - val_accuracy: 0.2772
Epoch 10/100
34/34 [==============================] - 4s 127ms/step - loss: 2.5082 - accuracy: 0.2151 - val_loss: 2.3165 - val_accuracy: 0.2996
Epoch 11/100
34/34 [==============================] - 4s 126ms/step - loss: 2.4749 - accuracy: 0.2198 - val_loss: 2.3135 - val_accuracy: 0.2584
Epoch 12/100
34/34 [==============================] - 4s 125ms/step - loss: 2.4096 - accuracy: 0.2389 - val_loss: 2.2483 - val_accuracy: 0.2884
Epoch 13/100
34/34 [==============================] - 4s 125ms/step - loss: 2.2550 - accuracy: 0.2678 - val_loss: 2.1701 - val_accuracy: 0.3034
Epoch 14/100
34/34 [==============================] - 4s 127ms/step - loss: 2.1982 - accuracy: 0.2996 - val_loss: 2.0726 - val_accuracy: 0.3034
Epoch 15/100
34/34 [==============================] - 4s 126ms/step - loss: 2.1457 - accuracy: 0.3150 - val_loss: 2.0555 - val_accuracy: 0.3408
Epoch 16/100
34/34 [==============================] - 5s 143ms/step - loss: 2.0736 - accuracy: 0.3271 - val_loss: 1.9778 - val_accuracy: 0.3670
Epoch 17/100
34/34 [==============================] - 4s 126ms/step - loss: 2.0063 - accuracy: 0.3364 - val_loss: 1.9419 - val_accuracy: 0.3670
Epoch 18/100
34/34 [==============================] - 4s 126ms/step - loss: 1.9806 - accuracy: 0.3439 - val_loss: 1.8687 - val_accuracy: 0.4157
Epoch 19/100
34/34 [==============================] - 4s 126ms/step - loss: 1.9385 - accuracy: 0.3668 - val_loss: 1.8607 - val_accuracy: 0.3858
Epoch 20/100
34/34 [==============================] - 4s 124ms/step - loss: 1.8757 - accuracy: 0.3682 - val_loss: 1.8278 - val_accuracy: 0.3895
Epoch 21/100
34/34 [==============================] - 4s 122ms/step - loss: 1.8320 - accuracy: 0.3724 - val_loss: 1.8058 - val_accuracy: 0.3933
Epoch 22/100
34/34 [==============================] - 4s 127ms/step - loss: 1.7679 - accuracy: 0.3934 - val_loss: 1.7815 - val_accuracy: 0.3820
Epoch 23/100
34/34 [==============================] - 5s 133ms/step - loss: 1.7622 - accuracy: 0.4036 - val_loss: 1.7678 - val_accuracy: 0.4082
Epoch 24/100
34/34 [==============================] - 4s 130ms/step - loss: 1.7117 - accuracy: 0.4139 - val_loss: 1.7756 - val_accuracy: 0.3783
Epoch 25/100
34/34 [==============================] - 4s 127ms/step - loss: 1.6940 - accuracy: 0.4256 - val_loss: 1.7379 - val_accuracy: 0.4007
Epoch 26/100
34/34 [==============================] - 5s 133ms/step - loss: 1.6417 - accuracy: 0.4414 - val_loss: 1.7140 - val_accuracy: 0.4270
Epoch 27/100
34/34 [==============================] - 4s 130ms/step - loss: 1.6079 - accuracy: 0.4648 - val_loss: 1.6731 - val_accuracy: 0.4120
Epoch 28/100
34/34 [==============================] - 5s 134ms/step - loss: 1.5619 - accuracy: 0.4578 - val_loss: 1.6427 - val_accuracy: 0.4232
Epoch 29/100
34/34 [==============================] - 4s 127ms/step - loss: 1.5551 - accuracy: 0.4536 - val_loss: 1.6682 - val_accuracy: 0.4195
Epoch 30/100
34/34 [==============================] - 4s 125ms/step - loss: 1.5046 - accuracy: 0.4568 - val_loss: 1.6446 - val_accuracy: 0.4232
Epoch 31/100
34/34 [==============================] - 4s 125ms/step - loss: 1.4852 - accuracy: 0.4783 - val_loss: 1.6480 - val_accuracy: 0.4082
Epoch 00031: early stopping
Fold 7 - Test set accuracy: 44%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 144ms/step - loss: 3.2609 - accuracy: 0.0420 - val_loss: 3.2266 - val_accuracy: 0.0448
Epoch 2/100
34/34 [==============================] - 4s 114ms/step - loss: 3.2037 - accuracy: 0.0617 - val_loss: 3.1099 - val_accuracy: 0.0821
Epoch 3/100
34/34 [==============================] - 4s 126ms/step - loss: 3.1275 - accuracy: 0.0827 - val_loss: 2.9962 - val_accuracy: 0.1045
Epoch 4/100
34/34 [==============================] - 4s 127ms/step - loss: 3.0397 - accuracy: 0.0972 - val_loss: 2.9439 - val_accuracy: 0.0970
Epoch 5/100
34/34 [==============================] - 4s 123ms/step - loss: 2.9565 - accuracy: 0.1004 - val_loss: 2.8261 - val_accuracy: 0.1306
Epoch 6/100
34/34 [==============================] - 4s 127ms/step - loss: 2.8423 - accuracy: 0.1275 - val_loss: 2.7197 - val_accuracy: 0.1604
Epoch 7/100
34/34 [==============================] - 5s 134ms/step - loss: 2.7726 - accuracy: 0.1509 - val_loss: 2.6977 - val_accuracy: 0.1754
Epoch 8/100
34/34 [==============================] - 5s 134ms/step - loss: 2.6537 - accuracy: 0.1756 - val_loss: 2.5404 - val_accuracy: 0.2015
Epoch 9/100
34/34 [==============================] - 5s 133ms/step - loss: 2.5679 - accuracy: 0.2064 - val_loss: 2.4720 - val_accuracy: 0.2090
Epoch 10/100
34/34 [==============================] - 4s 122ms/step - loss: 2.5162 - accuracy: 0.2172 - val_loss: 2.4371 - val_accuracy: 0.2537
Epoch 11/100
34/34 [==============================] - 4s 123ms/step - loss: 2.3877 - accuracy: 0.2504 - val_loss: 2.2668 - val_accuracy: 0.2985
Epoch 12/100
34/34 [==============================] - 4s 129ms/step - loss: 2.3053 - accuracy: 0.2644 - val_loss: 2.2533 - val_accuracy: 0.3060
Epoch 13/100
34/34 [==============================] - 4s 124ms/step - loss: 2.2416 - accuracy: 0.2606 - val_loss: 2.1617 - val_accuracy: 0.3172
Epoch 14/100
34/34 [==============================] - 4s 124ms/step - loss: 2.1751 - accuracy: 0.2896 - val_loss: 2.1574 - val_accuracy: 0.2910
Epoch 15/100
34/34 [==============================] - 4s 123ms/step - loss: 2.1076 - accuracy: 0.3101 - val_loss: 2.0862 - val_accuracy: 0.3321
Epoch 16/100
34/34 [==============================] - 4s 123ms/step - loss: 2.0234 - accuracy: 0.3382 - val_loss: 2.0035 - val_accuracy: 0.3321
Epoch 17/100
34/34 [==============================] - 4s 128ms/step - loss: 2.0058 - accuracy: 0.3461 - val_loss: 1.9560 - val_accuracy: 0.3731
Epoch 18/100
34/34 [==============================] - 4s 127ms/step - loss: 1.9474 - accuracy: 0.3718 - val_loss: 1.9169 - val_accuracy: 0.3843
Epoch 19/100
34/34 [==============================] - 4s 113ms/step - loss: 1.8822 - accuracy: 0.3718 - val_loss: 1.8764 - val_accuracy: 0.3806
Epoch 20/100
34/34 [==============================] - 4s 126ms/step - loss: 1.8369 - accuracy: 0.3797 - val_loss: 1.8610 - val_accuracy: 0.3843
Epoch 21/100
34/34 [==============================] - 4s 129ms/step - loss: 1.7644 - accuracy: 0.4120 - val_loss: 1.7916 - val_accuracy: 0.3955
Epoch 22/100
34/34 [==============================] - 4s 124ms/step - loss: 1.7163 - accuracy: 0.4246 - val_loss: 1.8062 - val_accuracy: 0.4067
Epoch 23/100
34/34 [==============================] - 4s 128ms/step - loss: 1.7014 - accuracy: 0.4264 - val_loss: 1.7566 - val_accuracy: 0.4142
Epoch 24/100
34/34 [==============================] - 4s 123ms/step - loss: 1.6756 - accuracy: 0.4404 - val_loss: 1.7116 - val_accuracy: 0.4328
Epoch 25/100
34/34 [==============================] - 4s 128ms/step - loss: 1.6288 - accuracy: 0.4376 - val_loss: 1.7471 - val_accuracy: 0.4067
Epoch 26/100
34/34 [==============================] - 5s 136ms/step - loss: 1.5721 - accuracy: 0.4563 - val_loss: 1.6785 - val_accuracy: 0.4366
Epoch 27/100
34/34 [==============================] - 4s 130ms/step - loss: 1.5051 - accuracy: 0.4787 - val_loss: 1.6946 - val_accuracy: 0.4478
Epoch 28/100
34/34 [==============================] - 4s 128ms/step - loss: 1.5261 - accuracy: 0.4689 - val_loss: 1.6948 - val_accuracy: 0.4478
Epoch 29/100
34/34 [==============================] - 4s 127ms/step - loss: 1.5353 - accuracy: 0.4717 - val_loss: 1.6964 - val_accuracy: 0.4552
Epoch 00029: early stopping
Fold 8 - Test set accuracy: 45%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 150ms/step - loss: 3.2689 - accuracy: 0.0369 - val_loss: 3.2577 - val_accuracy: 0.0336
Epoch 2/100
34/34 [==============================] - 4s 115ms/step - loss: 3.2461 - accuracy: 0.0500 - val_loss: 3.2259 - val_accuracy: 0.0522
Epoch 3/100
34/34 [==============================] - 4s 114ms/step - loss: 3.2008 - accuracy: 0.0635 - val_loss: 3.1230 - val_accuracy: 0.0896
Epoch 4/100
34/34 [==============================] - 4s 116ms/step - loss: 3.1061 - accuracy: 0.0892 - val_loss: 2.9919 - val_accuracy: 0.1157
Epoch 5/100
34/34 [==============================] - 4s 124ms/step - loss: 3.0177 - accuracy: 0.0897 - val_loss: 2.8838 - val_accuracy: 0.1306
Epoch 6/100
34/34 [==============================] - 4s 124ms/step - loss: 2.9043 - accuracy: 0.1168 - val_loss: 2.8322 - val_accuracy: 0.1343
Epoch 7/100
34/34 [==============================] - 4s 127ms/step - loss: 2.8170 - accuracy: 0.1369 - val_loss: 2.7128 - val_accuracy: 0.1940
Epoch 8/100
34/34 [==============================] - 4s 118ms/step - loss: 2.6915 - accuracy: 0.1831 - val_loss: 2.6737 - val_accuracy: 0.1828
Epoch 9/100
34/34 [==============================] - 4s 114ms/step - loss: 2.6176 - accuracy: 0.1878 - val_loss: 2.5085 - val_accuracy: 0.2649
Epoch 10/100
34/34 [==============================] - 4s 116ms/step - loss: 2.4814 - accuracy: 0.2335 - val_loss: 2.3691 - val_accuracy: 0.2836
Epoch 11/100
34/34 [==============================] - 4s 128ms/step - loss: 2.3763 - accuracy: 0.2518 - val_loss: 2.3323 - val_accuracy: 0.2612
Epoch 12/100
34/34 [==============================] - 4s 126ms/step - loss: 2.2681 - accuracy: 0.2672 - val_loss: 2.1891 - val_accuracy: 0.3060
Epoch 13/100
34/34 [==============================] - 4s 125ms/step - loss: 2.1904 - accuracy: 0.2905 - val_loss: 2.1469 - val_accuracy: 0.3209
Epoch 14/100
34/34 [==============================] - 4s 122ms/step - loss: 2.1282 - accuracy: 0.3106 - val_loss: 2.1206 - val_accuracy: 0.3134
Epoch 15/100
34/34 [==============================] - 4s 129ms/step - loss: 2.0566 - accuracy: 0.3386 - val_loss: 2.0676 - val_accuracy: 0.3582
Epoch 16/100
34/34 [==============================] - 4s 126ms/step - loss: 1.9980 - accuracy: 0.3568 - val_loss: 1.9513 - val_accuracy: 0.3582
Epoch 17/100
34/34 [==============================] - 4s 125ms/step - loss: 1.8888 - accuracy: 0.3545 - val_loss: 1.9057 - val_accuracy: 0.3694
Epoch 18/100
34/34 [==============================] - 4s 125ms/step - loss: 1.8827 - accuracy: 0.3769 - val_loss: 1.9156 - val_accuracy: 0.3769
Epoch 19/100
34/34 [==============================] - 4s 125ms/step - loss: 1.7949 - accuracy: 0.3928 - val_loss: 1.8852 - val_accuracy: 0.3657
Epoch 20/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7781 - accuracy: 0.4092 - val_loss: 1.8273 - val_accuracy: 0.3694
Epoch 21/100
34/34 [==============================] - 4s 130ms/step - loss: 1.7144 - accuracy: 0.4232 - val_loss: 1.8104 - val_accuracy: 0.3918
Epoch 22/100
34/34 [==============================] - 4s 126ms/step - loss: 1.6692 - accuracy: 0.4325 - val_loss: 1.8384 - val_accuracy: 0.3806
Epoch 23/100
34/34 [==============================] - 4s 125ms/step - loss: 1.6120 - accuracy: 0.4568 - val_loss: 1.7642 - val_accuracy: 0.4104
Epoch 24/100
34/34 [==============================] - 4s 125ms/step - loss: 1.6421 - accuracy: 0.4493 - val_loss: 1.7497 - val_accuracy: 0.4067
Epoch 25/100
34/34 [==============================] - 4s 126ms/step - loss: 1.5820 - accuracy: 0.4479 - val_loss: 1.7183 - val_accuracy: 0.4142
Epoch 26/100
34/34 [==============================] - 4s 128ms/step - loss: 1.5484 - accuracy: 0.4745 - val_loss: 1.7261 - val_accuracy: 0.4403
Epoch 27/100
34/34 [==============================] - 4s 128ms/step - loss: 1.5087 - accuracy: 0.4830 - val_loss: 1.7083 - val_accuracy: 0.4440
Epoch 28/100
34/34 [==============================] - 4s 126ms/step - loss: 1.4911 - accuracy: 0.4773 - val_loss: 1.6851 - val_accuracy: 0.4216
Epoch 29/100
34/34 [==============================] - 4s 125ms/step - loss: 1.4949 - accuracy: 0.4937 - val_loss: 1.6921 - val_accuracy: 0.4552
Epoch 30/100
34/34 [==============================] - 4s 126ms/step - loss: 1.4303 - accuracy: 0.4932 - val_loss: 1.7076 - val_accuracy: 0.4328
Epoch 31/100
34/34 [==============================] - 4s 126ms/step - loss: 1.4288 - accuracy: 0.5068 - val_loss: 1.6712 - val_accuracy: 0.4291
Epoch 32/100
34/34 [==============================] - 4s 131ms/step - loss: 1.3799 - accuracy: 0.5245 - val_loss: 1.6375 - val_accuracy: 0.4403
Epoch 33/100
34/34 [==============================] - 4s 129ms/step - loss: 1.3717 - accuracy: 0.5334 - val_loss: 1.6472 - val_accuracy: 0.4590
Epoch 34/100
34/34 [==============================] - 4s 128ms/step - loss: 1.3667 - accuracy: 0.5423 - val_loss: 1.6273 - val_accuracy: 0.4627
Epoch 35/100
34/34 [==============================] - 4s 125ms/step - loss: 1.3414 - accuracy: 0.5488 - val_loss: 1.6324 - val_accuracy: 0.4590
Epoch 36/100
34/34 [==============================] - 4s 125ms/step - loss: 1.3298 - accuracy: 0.5367 - val_loss: 1.6070 - val_accuracy: 0.4403
Epoch 37/100
34/34 [==============================] - 4s 131ms/step - loss: 1.3138 - accuracy: 0.5455 - val_loss: 1.6675 - val_accuracy: 0.4291
Epoch 38/100
34/34 [==============================] - 4s 131ms/step - loss: 1.2989 - accuracy: 0.5390 - val_loss: 1.6554 - val_accuracy: 0.4142
Epoch 39/100
34/34 [==============================] - 4s 132ms/step - loss: 1.2358 - accuracy: 0.5838 - val_loss: 1.6414 - val_accuracy: 0.4291
Epoch 00039: early stopping
Fold 9 - Test set accuracy: 47%
Pipeline Completed
Epoch 1/100
34/34 [==============================] - 5s 158ms/step - loss: 3.2665 - accuracy: 0.0383 - val_loss: 3.2489 - val_accuracy: 0.0562
Epoch 2/100
34/34 [==============================] - 4s 129ms/step - loss: 3.2255 - accuracy: 0.0588 - val_loss: 3.1547 - val_accuracy: 0.0599
Epoch 3/100
34/34 [==============================] - 4s 126ms/step - loss: 3.1353 - accuracy: 0.0779 - val_loss: 3.0591 - val_accuracy: 0.0936
Epoch 4/100
34/34 [==============================] - 4s 120ms/step - loss: 3.0529 - accuracy: 0.0915 - val_loss: 2.9219 - val_accuracy: 0.1273
Epoch 5/100
34/34 [==============================] - 4s 126ms/step - loss: 2.9584 - accuracy: 0.1050 - val_loss: 2.8460 - val_accuracy: 0.1723
Epoch 6/100
34/34 [==============================] - 4s 131ms/step - loss: 2.8669 - accuracy: 0.1428 - val_loss: 2.7162 - val_accuracy: 0.1685
Epoch 7/100
34/34 [==============================] - 4s 129ms/step - loss: 2.7653 - accuracy: 0.1442 - val_loss: 2.6266 - val_accuracy: 0.2135
Epoch 8/100
34/34 [==============================] - 4s 129ms/step - loss: 2.6929 - accuracy: 0.1801 - val_loss: 2.5384 - val_accuracy: 0.2210
Epoch 9/100
34/34 [==============================] - 4s 125ms/step - loss: 2.5571 - accuracy: 0.2086 - val_loss: 2.4323 - val_accuracy: 0.2210
Epoch 10/100
34/34 [==============================] - 4s 125ms/step - loss: 2.4872 - accuracy: 0.2165 - val_loss: 2.3451 - val_accuracy: 0.2434
Epoch 11/100
34/34 [==============================] - 4s 124ms/step - loss: 2.3540 - accuracy: 0.2543 - val_loss: 2.2940 - val_accuracy: 0.2734
Epoch 12/100
34/34 [==============================] - 4s 125ms/step - loss: 2.2692 - accuracy: 0.2664 - val_loss: 2.2227 - val_accuracy: 0.2846
Epoch 13/100
34/34 [==============================] - 4s 127ms/step - loss: 2.2037 - accuracy: 0.2907 - val_loss: 2.1397 - val_accuracy: 0.2959
Epoch 14/100
34/34 [==============================] - 4s 131ms/step - loss: 2.1645 - accuracy: 0.3024 - val_loss: 2.1318 - val_accuracy: 0.3184
Epoch 15/100
34/34 [==============================] - 4s 127ms/step - loss: 2.1325 - accuracy: 0.3196 - val_loss: 2.0789 - val_accuracy: 0.3221
Epoch 16/100
34/34 [==============================] - 4s 124ms/step - loss: 2.0220 - accuracy: 0.3383 - val_loss: 2.0245 - val_accuracy: 0.3296
Epoch 17/100
34/34 [==============================] - 4s 125ms/step - loss: 2.0008 - accuracy: 0.3500 - val_loss: 1.9790 - val_accuracy: 0.3483
Epoch 18/100
34/34 [==============================] - 4s 125ms/step - loss: 1.9045 - accuracy: 0.3752 - val_loss: 1.9681 - val_accuracy: 0.3670
Epoch 19/100
34/34 [==============================] - 4s 125ms/step - loss: 1.8799 - accuracy: 0.3840 - val_loss: 1.8951 - val_accuracy: 0.3633
Epoch 20/100
34/34 [==============================] - 4s 131ms/step - loss: 1.8264 - accuracy: 0.3896 - val_loss: 1.8586 - val_accuracy: 0.3820
Epoch 21/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7842 - accuracy: 0.3980 - val_loss: 1.8148 - val_accuracy: 0.3670
Epoch 22/100
34/34 [==============================] - 4s 126ms/step - loss: 1.7525 - accuracy: 0.4036 - val_loss: 1.8494 - val_accuracy: 0.3596
Epoch 23/100
34/34 [==============================] - 4s 132ms/step - loss: 1.7135 - accuracy: 0.4288 - val_loss: 1.7969 - val_accuracy: 0.3970
Epoch 24/100
34/34 [==============================] - 4s 131ms/step - loss: 1.6972 - accuracy: 0.4279 - val_loss: 1.7607 - val_accuracy: 0.3933
Epoch 25/100
34/34 [==============================] - 5s 134ms/step - loss: 1.6148 - accuracy: 0.4545 - val_loss: 1.6973 - val_accuracy: 0.4382
Epoch 26/100
34/34 [==============================] - 4s 129ms/step - loss: 1.6226 - accuracy: 0.4680 - val_loss: 1.7577 - val_accuracy: 0.3895
Epoch 27/100
34/34 [==============================] - 4s 127ms/step - loss: 1.5894 - accuracy: 0.4671 - val_loss: 1.7238 - val_accuracy: 0.4419
Epoch 28/100
34/34 [==============================] - 4s 128ms/step - loss: 1.5590 - accuracy: 0.4685 - val_loss: 1.7438 - val_accuracy: 0.4232
Epoch 00028: early stopping
Fold 10 - Test set accuracy: 41%
[0.48, 0.43, 0.4, 0.43, 0.39, 0.43, 0.44, 0.45, 0.47, 0.41]
mean score: 0.43

print("Done")
print(acc_per_fold)
print('mean score:', round(np.mean(acc_per_fold), 2))

Done
[0.48, 0.43, 0.4, 0.43, 0.39, 0.43, 0.44, 0.45, 0.47, 0.41]
mean score: 0.43