cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual

This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base on the cardiffnlp/tweet_sentiment_multilingual (all) via tweetnlp. Training split is train and parameters have been tuned on the validation split validation.

Following metrics are achieved on the test split test (link).

• F1 (micro): 0.6931034482758621
• F1 (macro): 0.692628774202147
• Accuracy: 0.6931034482758621

Usage

Install tweetnlp via pip.

pip install tweetnlp

Load the model in python.

import tweetnlp
model = tweetnlp.Classifier("cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual", max_length=128)
model.predict('Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@} via {@bluenoterecords@} link below {{URL}}')

Reference

@inproceedings{camacho-collados-etal-2022-tweetnlp,
 title = "{T}weet{NLP}: Cutting-Edge Natural Language Processing for Social Media",
 author = "Camacho-collados, Jose and
 Rezaee, Kiamehr and
 Riahi, Talayeh and
 Ushio, Asahi and
 Loureiro, Daniel and
 Antypas, Dimosthenis and
 Boisson, Joanne and
 Espinosa Anke, Luis and
 Liu, Fangyu and
 Mart{\'\i}nez C{\'a}mara, Eugenio" and others,
 booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
 month = dec,
 year = "2022",
 address = "Abu Dhabi, UAE",
 publisher = "Association for Computational Linguistics",
 url = "https://aclanthology.org/2022.emnlp-demos.5",
 pages = "38--49"
}