ظهور الخطأ ValueError: Shapes (32, 1) and (32, 2) are incompatible أثناء تدريب نموذج في Keras

اعمل على تصنيف الصور minst في keras على google colab ولكن قمت ببعض التعديلات على الداتا أي فقط صنفين 0 أو 1 ولكن يظهر لي الخطأ التالي
الكود:

import numpy as np
import pandas as pd
from keras.models import Sequential
from keras.layers import Dense , Activation, Dropout
from keras.models import Sequential
from keras.utils.np_utils import to_categorical
from keras.datasets import mnist
(x_train, y_train),(x_test, y_test) = mnist.load_data()
y_train[y_train<=5]=0
y_train[y_train>5]=1
y_train=y_train.astype('int64')
print(x_train.shape, y_train.shape)
image_size = x_train.shape[1]
input_size = image_size * image_size
x_train = np.reshape(x_train, [-1, input_size])
x_train = x_train.astype('float32') / 255
x_test = np.reshape(x_test, [-1, input_size])
x_test = x_test.astype('float32') / 255
batch_size = 32
hidden_units = 256
model = Sequential()
model.add(Dense(hidden_units, input_shape=(input_size,)))
model.add(Activation('relu'))
model.add(Dropout(0.45))
model.add(Dense(hidden_units))
model.add(Activation('relu'))
model.add(Dropout(0.45))
model.add(Dense(2))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=5, batch_size=batch_size)
الخطأ
(60000, 28, 28) (60000,)
Epoch 1/5

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-22-3c7ca6e80a5b> in <module>()
     32 model.add(Activation('softmax'))
     33 model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
---> 34 model.fit(x_train, y_train, epochs=5, batch_size=batch_size)

9 frames

/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, kwargs)
    984           except Exception as e:  # pylint:disable=broad-except
    985             if hasattr(e, "ag_error_metadata"):
--> 986               raise e.ag_error_metadata.to_exception(e)
    987             else:
    988               raise

ValueError: in user code:

    /usr/local/lib/python3.7/dist-packages/keras/engine/training.py:830 train_function  *
        return step_function(self, iterator)
    /usr/local/lib/python3.7/dist-packages/keras/engine/training.py:813 run_step  *
        outputs = model.train_step(data)
    /usr/local/lib/python3.7/dist-packages/keras/engine/training.py:771 train_step  *
        loss = self.compiled_loss(
    /usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py:201 __call__  *
        loss_value = loss_obj(y_t, y_p, sample_weight=sw)
    /usr/local/lib/python3.7/dist-packages/keras/losses.py:142 __call__  *
        losses = call_fn(y_true, y_pred)
    /usr/local/lib/python3.7/dist-packages/keras/losses.py:246 call  *
        return ag_fn(y_true, y_pred, **self._fn_kwargs)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206 wrapper  
        return target(*args, **kwargs)
    /usr/local/lib/python3.7/dist-packages/keras/losses.py:1631 categorical_crossentropy
        y_true, y_pred, from_logits=from_logits)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206 wrapper
        return target(*args, **kwargs)
    /usr/local/lib/python3.7/dist-packages/keras/backend.py:4827 categorical_crossentropy
        target.shape.assert_is_compatible_with(output.shape)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py:1161 assert_is_compatible_with
        raise ValueError("Shapes %s and %s are incompatible" % (self, other))

    ValueError: Shapes (32, 1) and (32, 2) are incompatible