Sage-Tips

How is BERT different from LSTM?

Bidirectional LSTM is trained both from left-to-right to predict the next word, and right-to-left, to predict the previous word. But, in BERT, the model is made to learn from words in all positions, meaning the entire sentence.

Is BERT always better?

Recently however there is growing evidence that BERT may not always give the best performance. Using a number of different pre-trained BERT modules from the TensorFlow Hub that were then fine-tuned for the downstream purpose, both their experiments resulted in the LSTM models outperforming BERT with transfer learning.

What is the advantage of BERT?

Some of the profound benefits BERT brings to AI include: Much better model performance over legacy methods. An ability to process larger amounts of text and language. An easy route to using pre-trained models (transfer learning)

Is Transformer better than LSTM?

The Transformer model is based on a self-attention mechanism. The Transformer architecture has been evaluated to out preform the LSTM within these neural machine translation tasks. Thus, the transformer allows for significantly more parallelization and can reach a new state of the art in translation quality.

How is BERT different from Word2Vec?

Word2Vec will generate the same single vector for the word bank for both the sentences. Whereas, BERT will generate two different vectors for the word bank being used in two different contexts. One vector will be similar to words like money, cash etc. The other vector would be similar to vectors like beach, coast etc.

What is the best NLP model?

Let’s take a look at the top 5 pre-trained NLP models.

1. BERT (Bidirectional Encoder Representations from Transformers) BERT is a technique for NLP pre-training, developed by Google.
2. RoBERTa (Robustly Optimized BERT Pretraining Approach)
3. OpenAI’s GPT-3.
4. ALBERT.
5. XLNet.

Why is BERT better than models?

BERT is different because it is designed to read in both directions at once. This capability, enabled by the introduction of Transformers, is known as bidirectionality.

How is Bert different from transformer?

Introduction to BERT One of the difference is BERT use bidirectional transformer (both left-to-right and right-to-left direction) rather than dictional transformer (left-to-right direction). On the other hand, both ELMo use bidirectional language model to learn the text representations.