cardiffnlp/twitter-roberta-base-2021-124m-topic-multi

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2021-124m on the cardiffnlp/tweet_topic_multi via tweetnlp. Training split is train_all and parameters have been tuned on the validation split validation_2021.

Following metrics are achieved on the test split test_2021 (link).

• F1 (micro): 0.7528230865746549
• F1 (macro): 0.5564228688431104
• Accuracy: 0.535437760571769

Usage

Install tweetnlp via pip.

pip install tweetnlp

Load the model in python.

import tweetnlp
model = tweetnlp.Classifier("cardiffnlp/twitter-roberta-base-2021-124m-topic-multi", 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}: {C}utting-{E}dge {N}atural {L}anguage {P}rocessing for {S}ocial {M}edia},
 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},
 author = "Ushio, Asahi and
 Camacho-Collados, Jose",
 booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
 month = nov,
 year = "2022",
 address = "Abu Dhabi, U.A.E.",
 publisher = "Association for Computational Linguistics",
}