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

这个模型是基于 cardiffnlp/twitter-roberta-base-2021-124m 在 cardiffnlp/tweet_topic_multi 经过 tweetnlp 微调的版本。训练数据集为 train_all，并且参数已经在验证数据集 validation_2021 上进行了调整。

在测试数据集 test_2021 ( link ) 上取得了以下指标：

• F1 (micro): 0.7528230865746549
• F1 (macro): 0.5564228688431104
• 准确率: 0.535437760571769

使用方法

通过pip安装tweetnlp。

pip install tweetnlp

在Python中加载模型。

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}}')

参考资料

@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",
}