# Sentiment Classification

This model is a fine-tuned version of distilbert-base-uncased on an emotions dataset, designed for text sentiment classification.

A lightweight text sentiment classification model based on DistilBERT, fine-tuned on the emotion dataset with an accuracy of 93.05%

A lightweight sentiment classification model distilled from the GoEmotions dataset, trained via a zero-shot classification pipeline, suitable for efficient sentiment analysis tasks.

A sentiment classification model fine-tuned on the go_emotions dataset based on bert-base-uncased

A sentiment classification model fine-tuned on the emotion dataset based on BERT-base-cased

A lightweight text sentiment classification model based on DistilBERT, fine-tuned on the emotion dataset

Lightweight sentiment analysis model based on ALBERT architecture, fine-tuned on Twitter sentiment dataset

This model is a text classification model fine-tuned on the emotion dataset based on DistilBERT, designed for sentiment analysis tasks.

A BERT-based sentiment classifier for classical poetry, specialized in analyzing emotional tendencies in ancient texts.

A lightweight text sentiment classification model based on DistilBERT, fine-tuned on the emotion dataset with an accuracy of 92.3%

A customer service survey text classification model fine-tuned based on bert-base-uncased for analyzing customer feedback

This model is a fine-tuned version of bert-base-chinese on an unknown dataset, primarily used for Chinese text processing tasks.