Update README.md

README.md

@@ -1,7 +1,25 @@
+---
+license: mit
+datasets:
+- cardiffnlp/super_tweeteval
+language:
+- en
+pipeline_tag: text-classification
+---
 # cardiffnlp/twitter-roberta-base-latest-tweet-nerd
 
-This is a [RoBERTa-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-2022-154m) model fine-tuned on [tweet-nerd](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 name entity Disambiguation (binary classification) on the _TweetNERD_ 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": "no",
+    "1": "yes"
+  }
+</code>
+
+## Example
 ```python
 from transformers import pipeline
 text = 'Banana+Nutella snack pack=someone is gonna see me crying in the break room'
@@ -12,4 +30,16 @@ text_input = f"{text} </s> {definition} </s> {target}"
 pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
 pipe(text_input)
 >> [{'label': 'yes', 'score': 0.9993378520011902}]
+```
+
+## 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}
+}
 ```