BERT Classification Learner

Trains a text classification model on top of the provided BERT model. The model is extended with 3 layers:

• GlobalAveragePooling1D layer
• Dropout layer
• Dense layer

Besides the typical classification task where every row is assigned a single class it is also possible to train a model for multi-label classification where a row can be assigned multiple labels.

If a validation table is provided, then the model performance is evaluated on that data after every epoch.

Input ports

1. Type: se.redfield.bert.nodes.port.BertModelPortObject
   BERT Model
   BERT Model
2. Type: Table
   Data Table
   Data Table
3. Type: Table
   Validation Table
   Optional Validation Table

Output ports

1. Type: se.redfield.bert.nodes.port.BertClassifierPortObject
   BERT Classifier
   BERT Classifier model
2. Type: Table
   Training statistics
   Statistics of the training process