Fine-tuning BERT for text classification of emotions.
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Updated
Dec 22, 2022 - Jupyter Notebook
Fine-tuning BERT for text classification of emotions.
In this implementation , I tried to identify spam and ham messages with Bert and I obtained %93 accuracy
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BERT QnA API to answer prompts based on Context. (Using CDN)
Fine-Tune BERT model for spam detection.
News Topic MultiClass Classification with BERT
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This repo provides a guide and code examples to preprocess text for BERT, build TensorFlow input pipelines for text data, and fine-tune BERT for text classification using TensorFlow 2 and TensorFlow Hub.
This repository implements sentiment classifier with Google Jax using Bert transformer as backbone. It also shows model checkpointing and loading for inference.
Implemented BERT from scratch in PyTorch framework using Stanford Sentiment Treebank (SST) & CFIMDB datasets. Inspired by the papers ”The Annotated Transformer” and ”Illustrated BERT”.
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Sentence Embeddings with BERT & XLNet
Layer Freezing in NLP Transfer Learning
Twitter Emotion MultiClass Classification with BERT
Predict which Tweets are about real disasters and which ones are not
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