Encoder-only Neural Network

A Encoder-only Neural Network is a neural network model that exclusively uses an encoder architecture.

• Context:
  • It can (typically) employ a bidirectional approach to process and understand natural language.
  • It can be used in various natural language processing tasks, like language understanding and language representation.
  • It can (often) be pre-trained on large corpora to learn word and sentence representations and their semantic relations.
  • It can lack a decoder component, which restricts its ability in tasks like text generation and language generation.
  • It can be fine-tuned on smaller datasets for specific tasks, such as sentiment analysis or question answering.
• Example(s):
  • BERT (Bidirectional Encoder Representations from Transformers).
  • RoBERTa (A Robustly Optimized BERT Pretraining Approach).
  • ...
• Counter-Example(s):
  • Decoder-only Neural Network Model.
  • Encoder-Decoder Neural Network Model.
• See: Natural Language Processing, Bidirectional Training, Language Understanding, Pre-trained Models.

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