Update README.md

README.md

@@ -1,7 +1,34 @@
+---
+license: mit
+datasets:
+- cardiffnlp/super_tweeteval
+language:
+- en
+pipeline_tag: text-classification
+---
 # cardiffnlp/twitter-roberta-base-latest-tweet-emotion
 
-This is a [RoBERTa-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-2022-154m) model fine-tuned on [tweet-emotion](https://huggingface.co/datasets/cardiffnlp/super_tweeteval).
+This is a RoBERTa-base model trained on 154M tweets until the end of December 2022 and finetuned for emotion classification (multilabel classification) on the _TweetEmotion_ dataset of [SuperTweetEval](https://huggingface.co/datasets/cardiffnlp/super_tweeteval).
+The original Twitter-based RoBERTa model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-2022-154m).
 
+## Labels
+<code>
+    "id2label": {
+    "0": "anger",
+    "1": "anticipation",
+    "2": "disgust",
+    "3": "fear",
+    "4": "joy",
+    "5": "love",
+    "6": "optimism",
+    "7": "pessimism",
+    "8": "sadness",
+    "9": "surprise",
+    "10": "trust"
+  }
+</code>
+
+## Example
 ```python
 from transformers import pipeline
 text= "@user it also helps that the majority of NFL coaching is inept. Some of Bill O'Brien's play calling was wow, ! #GOPATS"
@@ -14,4 +41,17 @@ predictions
  {'label': 'disgust', 'score': 0.7899409532546997},
  {'label': 'joy', 'score': 0.9664386510848999},
  {'label': 'optimism', 'score': 0.6123248934745789}]
+```
+
+## Citation Information
+
+Please cite the [reference paper](https://arxiv.org/abs/2310.14757) if you use this model.
+
+```bibtex
+@inproceedings{antypas2023supertweeteval,
+  title={SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research},
+  author={Dimosthenis Antypas and Asahi Ushio and Francesco Barbieri and Leonardo Neves and Kiamehr Rezaee and Luis Espinosa-Anke and Jiaxin Pei and Jose Camacho-Collados},
+  booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
+  year={2023}
+}
 ```