Cannot train model

[ashoknar]

ValueError: You are passing a target array of shape (3, 1) while using as loss categorical_crossentropy. categorical_crossentropy expects targets to be binary matrices (1s and 0s) of shape (samples, classes). If your targets are integer classes, you can convert them to the expected format via:

from keras.utils import to_categorical
y_binary = to_categorical(y_int)

Alternatively, you can use the loss function sparse_categorical_crossentropy instead, which does expect integer targets.

[ashoknar]

I have tried to train the model using varying number of input files. The error is the same, only the array shape shown above changes.

[ashoknar]

The error occurred because there wasn't enough fields labeled as header in the training data. At least one header field must be specified in each training set.

[saipavanmeruga]

Please elaborate on this issue and how you solved this. I am using 5 input files to train my model and it has skills as the only header after annotation