lightning-text-classification | Minimalist implementation of a BERT Sentence Classifier | Natural Language Processing library
kandi X-RAY | lightning-text-classification Summary
kandi X-RAY | lightning-text-classification Summary
lightning-text-classification is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Bert applications. lightning-text-classification has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
Minimalist implementation of a BERT Sentence Classifier with PyTorch Lightning, Transformers and PyTorch-NLP.
Minimalist implementation of a BERT Sentence Classifier with PyTorch Lightning, Transformers and PyTorch-NLP.
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lightning-text-classification has a low active ecosystem.
It has 192 star(s) with 37 fork(s). There are 4 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 2 have been closed. On average issues are closed in 46 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of lightning-text-classification is current.
Quality
lightning-text-classification has 0 bugs and 0 code smells.
Security
lightning-text-classification has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
lightning-text-classification code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
lightning-text-classification does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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lightning-text-classification releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
lightning-text-classification saves you 186 person hours of effort in developing the same functionality from scratch.
It has 460 lines of code, 32 functions and 5 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed lightning-text-classification and discovered the below as its top functions. This is intended to give you an instant insight into lightning-text-classification implemented functionality, and help decide if they suit your requirements.
- Adds model specific arguments to the given parser
- Evaluate the loss function
- Compute the classification loss
- Fill missing values
- Calculate the loss
- Perform training step
- Load a model from an experiment folder
- Predict on the given sample
- Prepare a sample
- Encodes sentences
- Stop the encoder
- Unfrees the encoder model
Get all kandi verified functions for this library.
lightning-text-classification Key Features
No Key Features are available at this moment for lightning-text-classification.
lightning-text-classification Examples and Code Snippets
No Code Snippets are available at this moment for lightning-text-classification.
Community Discussions
Trending Discussions on lightning-text-classification
QUESTION
Great accuracy on IMDB Sentiment Analysis. Is there any train data leakage I'm missing?
Asked 2020-Nov-07 at 21:43
I'm getting an unusual high accuracy on a sentiment analysis classifier I'm testing with python sklearn library. This is usually some sort of training data leakage but I can't figure out if that's the case.
My dataset has ~50k nonduplicated IMDB reviews.
...ANSWER
Answered 2020-Nov-07 at 21:43A good way to test if there is data leakage would be to check the performance on the validation set in the repository you linked, here.
I downloaded the dataset and tried to construct a Naive Bayes classifier with a pipeline like so:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install lightning-text-classification
You can download it from GitHub.
You can use lightning-text-classification like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use lightning-text-classification like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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