  Neural network has been recognized with its accomplishments on tackling
various natural language understanding (NLU) tasks. Methods have been developed
to train a robust model to handle multiple tasks to gain a general
representation of text. In this paper, we implement the model-agnostic
meta-learning (MAML) and Online aware Meta-learning (OML) meta-objective under
the continual framework for NLU tasks. We validate our methods on selected
SuperGLUE and GLUE benchmark.
