readme: # Twitter-roBERTa-base-jun2022_sem_eval_2018_task1
  
  This model was trained on ~7000 tweets in English annotated for 11 emotion categories in [SemEval-2018 Task 1: Affect in Tweets: SubTask 5: Emotion Classification](https://competitions.codalab.org/competitions/17751) (also available on the [Hugging Face Dataset Hub](https://huggingface.co/datasets/sem_eval_2018_task_1)).
  
  The underlying model is a RoBERTa-base model trained on 132.26M tweets until the end of June 2022. Fore more details check out the [model page](https://huggingface.co/cardiffnlp/twitter-roberta-base-jun2022).
  
  To quickly test it locally, use a pipeline:
  
  ```python
  from transformers import pipeline
  
  pipe = pipeline("text-classification",model="maxpe/twitter-roberta-base-jun2022_sem_eval_2018_task_1")
  
  pipe("I couldn't see any seafood for a year after I went to that restaurant that they send all the tourists to!",top_k=11)
  ```