Edit model card

citizenlab/twitter-xlm-roberta-base-sentiment-finetunned

This is multilingual XLM-Roberta model sequence classifier fine tunned and based on Cardiff NLP Group sentiment classification model.

How to use it

from transformers import pipeline

model_path = "citizenlab/twitter-xlm-roberta-base-sentiment-finetunned"

sentiment_classifier = pipeline("text-classification", model=model_path, tokenizer=model_path)
sentiment_classifier("this is a lovely message")
> [{'label': 'Positive', 'score': 0.9918450713157654}]

sentiment_classifier("you are an idiot and you and your family should go back to your country")
> [{'label': 'Negative', 'score': 0.9849833846092224}]

Evaluation

              precision    recall  f1-score   support

    Negative       0.57      0.14      0.23        28
     Neutral       0.78      0.94      0.86       132
    Positive       0.89      0.80      0.85        51

    accuracy                           0.80       211
   macro avg       0.75      0.63      0.64       211
weighted avg       0.78      0.80      0.77       211
Downloads last month
81,138
Inference API

Model tree for citizenlab/twitter-xlm-roberta-base-sentiment-finetunned

Finetunes
15 models

Dataset used to train citizenlab/twitter-xlm-roberta-base-sentiment-finetunned

Spaces using citizenlab/twitter-xlm-roberta-base-sentiment-finetunned 15