I'm a student in datascience and I'm trying to work with deep learning. The model I have is as follows:
Model: "sequential_32"
Layer (type) Output Shape Param #
=================================================================
conv2d_26 (Conv2D) (None, 27, 27, 32) 288
_________________________________________________________________
max_pooling2d_12 (MaxPooling (None, 13, 13, 32) 0
_________________________________________________________________
dense_13 (Dense) (None, 13, 13, 128) 4224
_________________________________________________________________
dropout_6 (Dropout) (None, 13, 13, 128) 0
_________________________________________________________________
dense_14 (Dense) (None, 13, 13, 10) 1290
=================================================================
Total params: 5,802
Trainable params: 5,802
Non-trainable params: 0
_________________________________________________________________
Now I'm trying to fit some data into it with the following code:
print(x_train.shape)
print(x_test.shape)
result = model.fit(x_train, y_train,
batch_size=batch_size,
epochs=epochs,
verbose=1,
validation_data=(x_test, y_test))
Which outputs the following:
(60000, 28, 28, 1)
(10000, 28, 28, 1)
# some error codes followed by:
ValueError: Shapes (32, 10) and (32, 13, 13, 11) are incompatible
I feel like it really is an easy mistake to fix but I just can't see it. Any help and/ or explanation is welcome!
Yes, Thymen's response helped me. Thank you. The model now looks like this:
Model: "sequential_35"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_29 (Conv2D) (None, 27, 27, 32) 160
_________________________________________________________________
max_pooling2d_15 (MaxPooling (None, 13, 13, 32) 0
_________________________________________________________________
flatten (Flatten) (None, 5408) 0
_________________________________________________________________
dense_17 (Dense) (None, 128) 692352
_________________________________________________________________
dropout_8 (Dropout) (None, 128) 0
_________________________________________________________________
dense_18 (Dense) (None, 10) 1290
=================================================================
Total params: 693,802
Trainable params: 693,802
Non-trainable params: 0
_________________________________________________________________