keras搭建简单的神经网络

from keras import layers
from keras import Model
from keras.optimizers import Adam
import tensorflow as tf
import numpy

class mymodel:
    def build(self, num_classes=3, dim=4):
        x = layers.Input(shape=(dim,))
        dense1 = layers.Dense(16, input_shape=(dim,),
                              activation='sigmoid')(x)
        out = layers.Dense(num_classes, activation='softmax')(dense1)
        model = Model(x, out)
        return model


data = numpy.loadtxt('Iris')
X = data[:, :4]
y = numpy.array(data[:, 4], dtype=int)
labels = tf.one_hot(y, 3)
m = mymodel()
model = m.build(num_classes=3, dim=4)
model.compile(optimizer=Adam(0.005),
              loss='categorical_crossentropy',
              metrics=['accuracy'])
# model.summary() 模型描述
model.fit(X, labels, epochs=50, steps_per_epoch=1)

Epoch 1/50
1/1 [==============================] - 0s 72ms/step - loss: 0.9302 - accuracy: 0.3333
Epoch 2/50
1/1 [==============================] - 0s 998us/step - loss: 0.8987 - accuracy: 0.3333
Epoch 3/50
1/1 [==============================] - 0s 1ms/step - loss: 0.8681 - accuracy: 0.3333
Epoch 4/50
1/1 [==============================] - 0s 998us/step - loss: 0.8387 - accuracy: 0.3333
Epoch 5/50
1/1 [==============================] - 0s 997us/step - loss: 0.8106 - accuracy: 0.3333
Epoch 6/50
1/1 [==============================] - 0s 997us/step - loss: 0.7840 - accuracy: 0.3333
Epoch 7/50
1/1 [==============================] - 0s 2ms/step - loss: 0.7588 - accuracy: 0.3333
Epoch 8/50
1/1 [==============================] - 0s 998us/step - loss: 0.7352 - accuracy: 0.3333
Epoch 9/50
1/1 [==============================] - 0s 997us/step - loss: 0.7133 - accuracy: 0.3333
Epoch 10/50
1/1 [==============================] - 0s 2ms/step - loss: 0.6930 - accuracy: 0.3333
Epoch 11/50
1/1 [==============================] - 0s 998us/step - loss: 0.6745 - accuracy: 0.3333
Epoch 12/50
1/1 [==============================] - 0s 1ms/step - loss: 0.6578 - accuracy: 0.3333
Epoch 13/50
1/1 [==============================] - 0s 987us/step - loss: 0.6429 - accuracy: 0.3333
Epoch 14/50
1/1 [==============================] - 0s 1ms/step - loss: 0.6297 - accuracy: 0.3333
Epoch 15/50
1/1 [==============================] - 0s 997us/step - loss: 0.6182 - accuracy: 0.4000
Epoch 16/50
1/1 [==============================] - 0s 997us/step - loss: 0.6081 - accuracy: 0.5933
Epoch 17/50
1/1 [==============================] - 0s 2ms/step - loss: 0.5993 - accuracy: 0.6600
Epoch 18/50
1/1 [==============================] - 0s 997us/step - loss: 0.5916 - accuracy: 0.6400
Epoch 19/50
1/1 [==============================] - 0s 1ms/step - loss: 0.5846 - accuracy: 0.5067
Epoch 20/50
1/1 [==============================] - 0s 997us/step - loss: 0.5783 - accuracy: 0.4400
Epoch 21/50
1/1 [==============================] - 0s 977us/step - loss: 0.5723 - accuracy: 0.3933
Epoch 22/50
1/1 [==============================] - 0s 2ms/step - loss: 0.5666 - accuracy: 0.3600
Epoch 23/50
1/1 [==============================] - 0s 993us/step - loss: 0.5611 - accuracy: 0.3333
Epoch 24/50
1/1 [==============================] - 0s 1ms/step - loss: 0.5556 - accuracy: 0.3333
Epoch 25/50
1/1 [==============================] - 0s 999us/step - loss: 0.5503 - accuracy: 0.3333
Epoch 26/50
1/1 [==============================] - 0s 1ms/step - loss: 0.5449 - accuracy: 0.3333
Epoch 27/50
1/1 [==============================] - 0s 998us/step - loss: 0.5397 - accuracy: 0.3467
Epoch 28/50
1/1 [==============================] - 0s 991us/step - loss: 0.5345 - accuracy: 0.3600
Epoch 29/50
1/1 [==============================] - 0s 995us/step - loss: 0.5293 - accuracy: 0.3867
Epoch 30/50
1/1 [==============================] - 0s 2ms/step - loss: 0.5243 - accuracy: 0.4267
Epoch 31/50
1/1 [==============================] - 0s 2ms/step - loss: 0.5195 - accuracy: 0.4600
Epoch 32/50
1/1 [==============================] - 0s 995us/step - loss: 0.5147 - accuracy: 0.4867
Epoch 33/50
1/1 [==============================] - 0s 997us/step - loss: 0.5101 - accuracy: 0.5200
Epoch 34/50
1/1 [==============================] - 0s 979us/step - loss: 0.5057 - accuracy: 0.5667
Epoch 35/50
1/1 [==============================] - 0s 2ms/step - loss: 0.5014 - accuracy: 0.6000
Epoch 36/50
1/1 [==============================] - 0s 998us/step - loss: 0.4974 - accuracy: 0.6200
Epoch 37/50
1/1 [==============================] - 0s 996us/step - loss: 0.4935 - accuracy: 0.6333
Epoch 38/50
1/1 [==============================] - 0s 997us/step - loss: 0.4898 - accuracy: 0.6400
Epoch 39/50
1/1 [==============================] - 0s 998us/step - loss: 0.4862 - accuracy: 0.6400
Epoch 40/50
1/1 [==============================] - 0s 991us/step - loss: 0.4829 - accuracy: 0.6467
Epoch 41/50
1/1 [==============================] - 0s 998us/step - loss: 0.4797 - accuracy: 0.6467
Epoch 42/50
1/1 [==============================] - 0s 997us/step - loss: 0.4767 - accuracy: 0.6467
Epoch 43/50
1/1 [==============================] - 0s 997us/step - loss: 0.4739 - accuracy: 0.6467
Epoch 44/50
1/1 [==============================] - 0s 993us/step - loss: 0.4712 - accuracy: 0.6467
Epoch 45/50
1/1 [==============================] - 0s 997us/step - loss: 0.4687 - accuracy: 0.6467
Epoch 46/50
1/1 [==============================] - 0s 0us/step - loss: 0.4664 - accuracy: 0.6467
Epoch 47/50
1/1 [==============================] - 0s 996us/step - loss: 0.4642 - accuracy: 0.6467
Epoch 48/50
1/1 [==============================] - 0s 998us/step - loss: 0.4622 - accuracy: 0.6467
Epoch 49/50
1/1 [==============================] - 0s 997us/step - loss: 0.4602 - accuracy: 0.6467
Epoch 50/50
1/1 [==============================] - 0s 998us/step - loss: 0.4584 - accuracy: 0.6467

D:\myftp\8-人工智能挑战赛\github\my>python _main__.py
Using TensorFlow backend.
2020-03-24 20:26:40.182081: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
3 4
Epoch 1/50
1/1 [==============================] - 0s 47ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 2/50
1/1 [==============================] - 0s 999us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 3/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 4/50
1/1 [==============================] - 0s 981us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 5/50
1/1 [==============================] - 0s 2ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 6/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 7/50
1/1 [==============================] - 0s 998us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 8/50
1/1 [==============================] - 0s 998us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 9/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 10/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 11/50
1/1 [==============================] - 0s 972us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 12/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 13/50
1/1 [==============================] - 0s 0us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 14/50
1/1 [==============================] - 0s 998us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 15/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 16/50
1/1 [==============================] - 0s 2ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 17/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 18/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 19/50
1/1 [==============================] - 0s 968us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 20/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 21/50
1/1 [==============================] - 0s 2ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 22/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 23/50
1/1 [==============================] - 0s 809us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 24/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 25/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 26/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 27/50
1/1 [==============================] - 0s 977us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 28/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 29/50
1/1 [==============================] - 0s 989us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 30/50
1/1 [==============================] - 0s 998us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 31/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 32/50
1/1 [==============================] - 0s 968us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 33/50
1/1 [==============================] - 0s 2ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 34/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 35/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 36/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 37/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 38/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 39/50
1/1 [==============================] - 0s 960us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 40/50
1/1 [==============================] - 0s 999us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 41/50
1/1 [==============================] - 0s 997us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 42/50
1/1 [==============================] - 0s 2ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 43/50
1/1 [==============================] - 0s 999us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 44/50
1/1 [==============================] - 0s 994us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 45/50
1/1 [==============================] - 0s 996us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 46/50
1/1 [==============================] - 0s 998us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 47/50
1/1 [==============================] - 0s 1ms/step - loss: 0.1066 - accuracy: 0.6667
Epoch 48/50
1/1 [==============================] - 0s 968us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 49/50
1/1 [==============================] - 0s 986us/step - loss: 0.1066 - accuracy: 0.6667
Epoch 50/50
1/1 [==============================] - 0s 960us/step - loss: 0.1066 - accuracy: 0.6667