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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838987312
Length 284 pages
Edition 1st Edition
Languages
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Author (1):
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Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (10) Chapters Close

Preface 1. Chapter 1: Learning NLP Basics 2. Chapter 2: Playing with Grammar FREE CHAPTER 3. Chapter 3: Representing Text – Capturing Semantics 4. Chapter 4: Classifying Texts 5. Chapter 5: Getting Started with Information Extraction 6. Chapter 6: Topic Modeling 7. Chapter 7: Building Chatbots 8. Chapter 8: Visualizing Text Data 9. Other Books You May Enjoy

Using BERT for sentiment analysis

In this recipe, we will fine-tune a pretrained Bidirectional Encoder Representations from Transformers (BERT) model to classify the Twitter data from the previous recipe. We will load the model, encode the data, and then fine-tune the model with the data. We will then use it on unseen examples.

Getting ready

We will use the Hugging Face transformers library for this recipe. To install the package, run the following command:

pip install transformers

We will use the same Twitter dataset as in the previous recipe.

How to do it…

BERT models are a little more complicated than the models we were using in previous recipes, but the general idea is the same: encode the data and train the model. The one difference is that in this recipe, the model is already pretrained and we will be just fine-tuning it with our data. The steps for this recipe are as follows:

  1. Import the necessary functions and packages:
    import pandas as pd
    import...
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