Closed johann-petrak closed 5 years ago
There are probably two problems here:
1) we generate a rubbish network architecture: we generate a linear layer which gets as many inputs as there are numeric features . Especially if we only have one numeric feature this does not make sense as we get a Linear(1,1) Layer.
2) we should simply concatenate the numeric inputs with the concatenation of all the embeddings for the non-numeric features instead!
Overall this means we change the architecture AND the way how we forward the values.
Fixed as of 237ef31362a5416bb3ebbf90550e9e4ff296a98a
When the data from the LF includes a numerical feature when training a sequence-based chunking model we get the following error:
at line 74 in classificationmodule.py
Need to check if numeric features are also a problem with non-sequence classification.