https://github.com/cooldragon12/fine-tune-bert-for-text-classification-sentiment-analysis

Fine tuning BERT for sentiment analysis
https://github.com/cooldragon12/fine-tune-bert-for-text-classification-sentiment-analysis

bert-model fine-tuning machine-learning nlp

Last synced: 29 days ago
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Fine tuning BERT for sentiment analysis

• Host: GitHub
• URL: https://github.com/cooldragon12/fine-tune-bert-for-text-classification-sentiment-analysis
• Owner: cooldragon12
• Created: 2023-08-03T10:29:27.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-08-03T10:43:56.000Z (over 1 year ago)
• Last Synced: 2024-04-23T05:35:08.786Z (7 months ago)
• Topics: bert-model, fine-tuning, machine-learning, nlp
• Language: Jupyter Notebook
• Homepage:
• Size: 75.2 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Fine Tune BERT for Text Classification - Sentiment Analysis

### Project Requirement in Coursera  

This project is based on the guided project of the Coursera Course.

This directory includes a few sample datasets to get you started.

*   `california_housing_data*.csv` is California housing data from the 1990 US

    Census; more information is available at:

    https://developers.google.com/machine-learning/crash-course/california-housing-data-description

*   `mnist_*.csv` is a small sample of the

    [MNIST database](https://en.wikipedia.org/wiki/MNIST_database), which is

    described at: http://yann.lecun.com/exdb/mnist/

*   `anscombe.json` contains a copy of

    [Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet); it

    was originally described in

    Anscombe, F. J. (1973). 'Graphs in Statistical Analysis'. American

    Statistician. 27 (1): 17-21. JSTOR 2682899.

    and our copy was prepared by the

    [vega_datasets library](https://github.com/altair-viz/vega_datasets/blob/4f67bdaad10f45e3549984e17e1b3088c731503d/vega_datasets/_data/anscombe.json).