Model Improvement
Explore effective methods to enhance Seq2Seq encoder-decoder models, including training strategies like adjusting batch size and learning rate. Understand domain-specific tweaks for tasks such as machine translation, text summarization, and dialog systems to optimize model performance and inference accuracy.
We'll cover the following...
We'll cover the following...
Chapter Goals:
Learn strategies for improving an encoder-decoder model
Run the encoder-decoder model in inference mode
A. Training strategies
Good encoder-decoder models tend to have a large number of weight parameters, since they consist of large LSTM/BiLSTM layers. Because of this, it usually takes a long time to train an encoder-decoder model to convergence.
To speed up ...