Create README.md

README.md

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+---
+language:
+- en
+library_name: transformers
+pipeline_tag: text-classification
+tags:
+- humor-detection
+- humor-classification
+- joke-detection
+- humor-vs-non-humor
+- binary-classification
+- text-classification
+- english
+- nlp
+- computational-humor
+- roberta
+---
+
+# English Humor Detection Model
+
+This model is part of the **Humor Research** collection of models for **English humor detection**, **humor classification**, and **joke detection**. It can be used for binary text classification tasks such as identifying whether an English text is humorous or non-humorous.
+
+## Model name
+
+The model name indicates the dataset from the paper on which the model was trained. The numbers in the model name correspond to the random seed used for model initialization.
+
+## Recommended model for humor detection
+
+If you need a single recommended model for English humor vs. non-humor classification, please refer to the best model from the project:
+
+[Humor-Research/humor-detection-comb-23](https://huggingface.co/Humor-Research/humor-detection-comb-23)
+
+## Paper
+
+This model was released as part of the study:
+
+[You Told Me That Joke Twice: A Systematic Investigation of Transferability and Robustness of Humor Detection Models](https://aclanthology.org/2023.emnlp-main.845/)
+
+## GitHub repository
+
+Code, data processing tools, and additional project information are available here:
+
+[Humor-Research/Humor-detection](https://github.com/Humor-Research/Humor-detection)
+
+## Citation
+
+If you use this model, please cite the following paper:
+
+```bibtex
+@inproceedings{baranov-etal-2023-told,
+    title = "You Told Me That Joke Twice: A Systematic Investigation of Transferability and Robustness of Humor Detection Models",
+    author = "Baranov, Alexander  and
+      Kniazhevsky, Vladimir  and
+      Braslavski, Pavel",
+    editor = "Bouamor, Houda  and
+      Pino, Juan  and
+      Bali, Kalika",
+    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
+    month = dec,
+    year = "2023",
+    address = "Singapore",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2023.emnlp-main.845",
+    doi = "10.18653/v1/2023.emnlp-main.845",
+    pages = "13701--13715",
+}
+```