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Sentiment analysis model that uses the Roberta sentiment tweet pre-trained model (from https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment), and fine-tuned on a dataset containing Trip Advisor reviews (from https://www.kaggle.com/datasets/arnabchaki/tripadvisor-reviews-2023).

Reviews with 1 or 2 stars are considered 'Negative', 3 stars are 'Neutral', and 4 or 5 stars are 'Positive'.

Should be loaded with the following code:

# Load pre-trained model and tokenizer
model_name = "gosorio/robertaSentimentFT_TripAdvisor"
tokenizer_name = "cardiffnlp/twitter-roberta-base-sentiment"
device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')

tokenizer = AutoTokenizer.from_pretrained(tokenizer_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name, num_labels=3).to(device)
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Dataset used to train gosorio/robertaSentimentFT_TripAdvisor