I am new to Tensorflow and the field of ML and I am having a weird experience with Tensorflow.

I am trying to train a Tensorflow simple Sequential Model but during the training phase rather than showing accuracy or some progress bar its printing the entire training dataset.

Here is my whole code

import tensorflow as tf
from data import get_data  
from sklearn import model_selection

data = get_data('2Y')

x_train, x_test, y_train, y_test = model_selection.train_test_split(data.get_values(['temperature','wind','humidity']), data.get_values('rain'), test_size=0.1, shuffle=False)
model = tf.keras.Sequential([
    tf.keras.layers.Dense(8),
    tf.keras.layers.Dense(8)
])

model.compile(
    optimizer="adam",
    loss="binary_crossentropy",
    metrics=["accuracy"]
)

model.fit(x_train, y_train, epochs=10, batch_size=64, validation_data=(x_test, y_test), verbose=2)

I read tensorflow docs but there is no mention of such thing like prinitng entire dataset during fitting of model. I don’t get where its getting wrong. and also after model.fit any code after gets discarded like i tried having print() statements but they never run.