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How to Fine Tune BERT for Sentiment Analysis with Hugging Face Transformers
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In this video, we take you through a step-by-step tutorial on how to fine-tune BERT for sentiment analysis using the Hugging Face Transformers library. Whether you're new to natural language processing (NLP) or an experienced practitioner, this guide will help you set up your environment, preprocess data, and train a powerful BERT model to analyze sentiments in text.
What You'll Learn:
1.Setting up the environment with Hugging Face Transformers, PyTorch, and 2.Datasets
3.Loading and tokenizing the IMDb movie review dataset
4.Splitting the dataset into training and validation sets
5.Creating DataLoaders for efficient data management
6.Fine-tuning the BERT model for sentiment analysis
7/Evaluating model performance with accuracy, precision, recall, and F1-score
8.Making predictions with your fine-tuned BERT model.
#SentimentAnalysis #NLP #BERT #HuggingFace #MachineLearning #DataScience #Python #PyTorch #AI #DeepLearning #Tutorial #IMDbDataset #TextAnalysis
What You'll Learn:
1.Setting up the environment with Hugging Face Transformers, PyTorch, and 2.Datasets
3.Loading and tokenizing the IMDb movie review dataset
4.Splitting the dataset into training and validation sets
5.Creating DataLoaders for efficient data management
6.Fine-tuning the BERT model for sentiment analysis
7/Evaluating model performance with accuracy, precision, recall, and F1-score
8.Making predictions with your fine-tuned BERT model.
#SentimentAnalysis #NLP #BERT #HuggingFace #MachineLearning #DataScience #Python #PyTorch #AI #DeepLearning #Tutorial #IMDbDataset #TextAnalysis
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