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BERT Classification Learner

BERT extension for KNIME Workbench version 0.0.1.v202012081121 by Redfield AB

The node uses BERT model and adds a predefined neural network on top. There are 3 layers added:

  • GlobalAveragePooling1D layer
  • Dropout layer
  • Dense layer
The trained model can be applied for multi-class classification.



Sentence column
A column with a plain text (String), that contains text to be classified. No special pre-processing is needed.
Class column
A column that contains class labels.
Max sequence length
The maximum length of a sequence after tokenization, limit is 512.


Number of epochs
The number of epochs used for training the classifier.
Batch size
The size of a chunk of the input data used for model update.
Fine tune BERT
If checked than BERT model will be trained along with the additional classifier. It takes longer time to fine tune BERT, but the results are usually better.
Available optimizers and their configuration.

Input Ports

BERT Model
Data Table
Validation Table

Output Ports

BERT Classifier model

Best Friends (Incoming)

Best Friends (Outgoing)



To use this node in KNIME, install Redfield BERT Nodes from the following update site:


A zipped version of the software site can be downloaded here.

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