# Social media text

This model is an English sentiment analysis model based on the RoBERTa architecture, capable of classifying text into positive, neutral, and negative categories.

A food entity recognition model specifically designed for informal text on social media, fine-tuned based on the RoBERTa architecture

A sentiment analysis model based on DeepPavlov/rubert-base-cased-conversational architecture, trained on the RuSentiment dataset, capable of identifying neutral, positive, and negative emotions in Russian text.

A text classification model fine-tuned on distilbert-base-uncased, trained on the tweet_eval sentiment analysis dataset

A sentiment analysis model fine-tuned on approximately 600,000 Persian tweets for analyzing sentiment tendencies in Persian text.

A sentiment analysis model fine-tuned on distilbert-base-uncased, trained on the tweet_eval dataset for tweet sentiment classification

A text sentiment classification model fine-tuned on distilbert-base-uncased, trained on the tweet_eval dataset