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1
Introduction
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Config File
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Model File
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Train Function
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Data Serve
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Item Function
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BERT
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Data Set
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Loss Function
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Evaluation Function
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Training Function
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Parameters
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Training Steps
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Optimizer
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Scheduler
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Save Model
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Train Model
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Train Engine
Description:
Learn to develop and deploy a high-accuracy sentiment analysis model using BERT and Flask in this comprehensive tutorial video. Explore the entire process, from creating data loaders and implementing a BERT model with the Transformers library to training the model and serving it via a Flask REST API. Achieve 93% accuracy on the IMDB 50K Movie Reviews dataset as you master techniques for sentiment analysis, deep learning, and model deployment. Gain hands-on experience with data preparation, model architecture, training procedures, and inference using Flask. Access provided resources, including the training dataset and BERT base uncased files, to follow along and implement your own sentiment analysis solution.

Training Sentiment Model Using BERT and Serving It With Flask API

Abhishek Thakur
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