Sentiment analysis neural network trained by fine-tuning BERT, ALBERT, or DistilBERT on the Stanford Sentiment Treebank.
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Updated
Jun 12, 2023 - Python
Sentiment analysis neural network trained by fine-tuning BERT, ALBERT, or DistilBERT on the Stanford Sentiment Treebank.
😡😇 Stanford Sentiment Treebank loader in Python
word2vec implementation (for skip-gram and cbow) and simple application of word2vec in sentiment analysis
Neural sentiment classification of text using the Stanford Sentiment Treebank (SST-2) movie reviews dataset, logistic regression, naive bayes, continuous bag of words, and multiple CNN variants.
Refined dataset for Stanford Sentiment Treebank used in Yoon Kim (2014).
An LSTM model implemented by PyTorch to perform sentiment classification on the Stanford Sentiment Treebank (SST-5) dataset.
Bi-LSTM with Attention performs sentence-level sentiment classification on Stanford Sentiment Treebank dataset .
Sentiment Classification
Cleaned, Ready-to-use Sentence Level Labeled Stanford Sentiment Treebank Dataset
This is the implementation of paper "Convolutional Neural Networks for Sentence Classification" by Yoon Kim
Implementation of Recursive Neural Tensor Network as described in https://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf
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