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

此模型是通过 tweetnlp 对 cardiffnlp/twitter-roberta-base-2021-124m 在 cardiffnlp/tweet_topic_single 上进行微调的版本。训练集划分为 train_all，并且参数已经在验证集 validation_2021 上进行了调整。

在测试集 test_2021 （ link ）上达到了以下指标：

• F1（微平均）：0.9019492025989368
• F1（宏平均）：0.801375264407874
• 准确率：0.9019492025989368

用法

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-single", 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

@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",
}