Edit model card

cardiffnlp/twitter-roberta-base-dec2021-tweet-topic-single-all

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-dec2021 on the tweet_topic_single. This model is fine-tuned on train_all split and validated on test_2021 split of tweet_topic. Fine-tuning script can be found here. It achieves the following results on the test_2021 set:

  • F1 (micro): 0.8948611931482575
  • F1 (macro): 0.800952410284692
  • Accuracy: 0.8948611931482575

Usage

from transformers import pipeline

pipe = pipeline("text-classification", "cardiffnlp/twitter-roberta-base-dec2021-tweet-topic-single-all")  
topic = pipe("Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US.")
print(topic)

Reference


@inproceedings{dimosthenis-etal-2022-twitter,
    title = "{T}witter {T}opic {C}lassification",
    author = "Antypas, Dimosthenis  and
    Ushio, Asahi  and
    Camacho-Collados, Jose  and
    Neves, Leonardo  and
    Silva, Vitor  and
    Barbieri, Francesco",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics"
}
Downloads last month
54
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train cardiffnlp/twitter-roberta-base-dec2021-tweet-topic-single-all

Evaluation results