Error in shape (dimention) and type of Keras model input

I am desperate to set the Input shape of this simple Keras model :( Both X and Y are numpy.narray but I don't know what's the wrong with it! I tried different X shape but the error is there! The info of the datasets (dimentions, number of samples, etc.) is available in the code. The .pkl file for X_train is got from hidden state of a pre-trained model.

import pandas as pd
from sklearn.preprocessing import LabelEncoder
from keras.utils import np_utils
from keras import Input, Model
from keras.layers import Dense
import numpy as np

############################## X_Train ############################

X_Train_3embed1 = pd.read_pickle("XX_Train_3embeding.pkl")


X_Train_3embed = np.array(X_Train_3embed1)

print("X-Train")
print(X_Train_3embed.shape)   # (230, 1, 128)
print(type(X_Train_3embed))  # <class 'numpy.ndarray'>
print(X_Train_3embed[0].shape) # (1, 128)
print(type(X_Train_3embed[0])) # <class 'numpy.ndarray'>


############################## Y_Train ############################

Y_Train_labels_list = pd.read_pickle("lis_Y_all_Train.pkl")

print(type(Y_Train_labels_list))  #<class 'numpy.ndarray'>
print(type(Y_Train_labels_list[0])) #<class 'str'>

encoder = LabelEncoder()
encoder.fit(Y_Train_labels_list)
encoded_Y = encoder.transform(Y_Train_labels_list)
Y_my_Train = np_utils.to_categorical(encoded_Y)


print("Y-Train")
print(Y_my_Train.shape) #(230, 83)
print(type(Y_my_Train)) # <class 'numpy.ndarray'>
print(Y_my_Train[0].shape) # (83,)
print(type(Y_my_Train[0])) # <class 'numpy.ndarray'>

##################################  Model  ##################################

first_input = Input(shape=(1, 128))

first_dense = Dense(128)(first_input)

output_layer = Dense(83, activation='softmax')(first_dense)

model = Model(inputs=first_input, outputs=output_layer)

model.summary()


model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['acc'])


history = model.fit((X_Train_3embed, Y_my_Train), epochs=2, batch_size=32)

Here is the result:

Model: "model_1"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_1 (InputLayer)         (None, 1, 128)            0         
_________________________________________________________________
dense_1 (Dense)              (None, 1, 128)            16512     
_________________________________________________________________
dense_2 (Dense)              (None, 1, 83)             10707     
=================================================================
Total params: 27,219
Trainable params: 27,219
Non-trainable params: 0
_________________________________________________________________
Traceback (most recent call last):
  File "/home/vahideh/PycharmProjects/3KArgen-master/MyTransferClassifier2.py", line 63, in <module>
    history = model.fit((X_Train_3embed, Y_my_Train), epochs=2, batch_size=32)
  File "/home/vahideh/PycharmProjects/MyVirtualEnvs/MyKargo/lib/python3.6/site-packages/keras/engine/training.py", line 1154, in fit
    batch_size=batch_size)
  File "/home/vahideh/PycharmProjects/MyVirtualEnvs/MyKargo/lib/python3.6/site-packages/keras/engine/training.py", line 579, in _standardize_user_data
    exception_prefix='input')
  File "/home/vahideh/PycharmProjects/MyVirtualEnvs/MyKargo/lib/python3.6/site-packages/keras/engine/training_utils.py", line 99, in standardize_input_data
    data = [standardize_single_array(x) for x in data]
  File "/home/vahideh/PycharmProjects/MyVirtualEnvs/MyKargo/lib/python3.6/site-packages/keras/engine/training_utils.py", line 99, in <listcomp>
    data = [standardize_single_array(x) for x in data]
  File "/home/vahideh/PycharmProjects/MyVirtualEnvs/MyKargo/lib/python3.6/site-packages/keras/engine/training_utils.py", line 34, in standardize_single_array
    elif x.ndim == 1:
AttributeError: 'tuple' object has no attribute 'ndim'

How can I feed these dataset to the model? or change the input shape of the model?

from Error in shape (dimention) and type of Keras model input