cardiffnlp/roberta-base-sentiment

这个模型是在 tweet_eval (sentiment) 上经过 tweetnlp 的微调版本，使用了 train 的训练集进行训练，参数在验证集 validation 上进行了调优。

在测试集 test 上（ link ）获得了以下指标：

• F1（微平均）：0.7086453923803321
• F1（宏平均）：0.7097736527692039
• 准确率：0.7086453923803321

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/roberta-base-sentiment", 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",
}