Update README.md

README.md

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 ---
-license: apache-2.0
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- en
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+- 10K<n<100K
+- 1K<n<10K
+- n<1K
+source_datasets:
+- extended|other-tweet-datasets
+task_categories:
+- text-classification
+task_ids:
+- intent-classification
+- multi-class-classification
+- sentiment-classification
+paperswithcode_id: tweeteval
+pretty_name: TweetEval
+train-eval-index:
+- config: emotion
+  task: text-classification
+  task_id: multi_class_classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    text: text
+    label: target
+  metrics:
+    - type: accuracy
+      name: Accuracy
+    - type: f1
+      name: F1 macro
+      args:
+        average: macro
+    - type: f1
+      name: F1 micro
+      args:
+        average: micro
+    - type: f1
+      name: F1 weighted
+      args:
+        average: weighted
+    - type: precision
+      name: Precision macro
+      args:
+        average: macro
+    - type: precision
+      name: Precision micro
+      args:
+        average: micro
+    - type: precision
+      name: Precision weighted
+      args:
+        average: weighted
+    - type: recall
+      name: Recall macro
+      args:
+        average: macro
+    - type: recall
+      name: Recall micro
+      args:
+        average: micro
+    - type: recall
+      name: Recall weighted
+      args:
+        average: weighted
+- config: hate
+  task: text-classification
+  task_id: binary_classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    text: text
+    label: target
+  metrics:
+    - type: accuracy
+      name: Accuracy
+    - type: f1
+      name: F1 binary
+      args:
+        average: binary
+    - type: precision
+      name: Precision macro
+      args:
+        average: macro
+    - type: precision
+      name: Precision micro
+      args:
+        average: micro
+    - type: precision
+      name: Precision weighted
+      args:
+        average: weighted
+    - type: recall
+      name: Recall macro
+      args:
+        average: macro
+    - type: recall
+      name: Recall micro
+      args:
+        average: micro
+    - type: recall
+      name: Recall weighted
+      args:
+        average: weighted
+- config: irony
+  task: text-classification
+  task_id: binary_classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    text: text
+    label: target
+  metrics:
+    - type: accuracy
+      name: Accuracy
+    - type: f1
+      name: F1 binary
+      args:
+        average: binary
+    - type: precision
+      name: Precision macro
+      args:
+        average: macro
+    - type: precision
+      name: Precision micro
+      args:
+        average: micro
+    - type: precision
+      name: Precision weighted
+      args:
+        average: weighted
+    - type: recall
+      name: Recall macro
+      args:
+        average: macro
+    - type: recall
+      name: Recall micro
+      args:
+        average: micro
+    - type: recall
+      name: Recall weighted
+      args:
+        average: weighted
+- config: offensive
+  task: text-classification
+  task_id: binary_classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    text: text
+    label: target
+  metrics:
+    - type: accuracy
+      name: Accuracy
+    - type: f1
+      name: F1 binary
+      args:
+        average: binary
+    - type: precision
+      name: Precision macro
+      args:
+        average: macro
+    - type: precision
+      name: Precision micro
+      args:
+        average: micro
+    - type: precision
+      name: Precision weighted
+      args:
+        average: weighted
+    - type: recall
+      name: Recall macro
+      args:
+        average: macro
+    - type: recall
+      name: Recall micro
+      args:
+        average: micro
+    - type: recall
+      name: Recall weighted
+      args:
+        average: weighted
+- config: sentiment
+  task: text-classification
+  task_id: multi_class_classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    text: text
+    label: target
+  metrics:
+    - type: accuracy
+      name: Accuracy
+    - type: f1
+      name: F1 macro
+      args:
+        average: macro
+    - type: f1
+      name: F1 micro
+      args:
+        average: micro
+    - type: f1
+      name: F1 weighted
+      args:
+        average: weighted
+    - type: precision
+      name: Precision macro
+      args:
+        average: macro
+    - type: precision
+      name: Precision micro
+      args:
+        average: micro
+    - type: precision
+      name: Precision weighted
+      args:
+        average: weighted
+    - type: recall
+      name: Recall macro
+      args:
+        average: macro
+    - type: recall
+      name: Recall micro
+      args:
+        average: micro
+    - type: recall
+      name: Recall weighted
+      args:
+        average: weighted
+configs:
+- emoji
+- emotion
+- hate
+- irony
+- offensive
+- sentiment
+- stance_abortion
+- stance_atheism
+- stance_climate
+- stance_feminist
+- stance_hillary
 ---
+# Dataset Card for tweet_eval
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+## Dataset Description
+- **Homepage:** [Needs More Information]
+- **Repository:** [GitHub](https://github.com/cardiffnlp/tweeteval)
+- **Paper:** [EMNLP Paper](https://arxiv.org/pdf/2010.12421.pdf)
+- **Leaderboard:** [GitHub Leaderboard](https://github.com/cardiffnlp/tweeteval)
+- **Point of Contact:** [Needs More Information]
+### Dataset Summary
+TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. The tasks include - irony, hate, offensive, stance, emoji, emotion, and sentiment. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
+### Supported Tasks and Leaderboards
+- `text_classification`: The dataset can be trained using a SentenceClassification model from HuggingFace transformers.
+### Languages
+The text in the dataset is in English, as spoken by Twitter users.
+## Dataset Structure
+### Data Instances
+An instance from `emoji` config:
+```
+{'label': 12, 'text': 'Sunday afternoon walking through Venice in the sun with @user ️ ️ ️ @ Abbot Kinney, Venice'}
+```
+An instance from `emotion` config:
+```
+{'label': 2, 'text': "“Worry is a down payment on a problem you may never have'. \xa0Joyce Meyer.  #motivation #leadership #worry"}
+```
+An instance from `hate` config:
+```
+{'label': 0, 'text': '@user nice new signage. Are you not concerned by Beatlemania -style hysterical crowds crongregating on you…'}
+```
+An instance from `irony` config:
+```
+{'label': 1, 'text': 'seeing ppl walking w/ crutches makes me really excited for the next 3 weeks of my life'}
+```
+An instance from `offensive` config:
+```
+{'label': 0, 'text': '@user Bono... who cares. Soon people will understand that they gain nothing from following a phony celebrity. Become a Leader of your people instead or help and support your fellow countrymen.'}
+```
+An instance from `sentiment` config:
+```
+{'label': 2, 'text': '"QT @user In the original draft of the 7th book, Remus Lupin survived the Battle of Hogwarts. #HappyBirthdayRemusLupin"'}
+```
+An instance from `stance_abortion` config:
+```
+{'label': 1, 'text': 'we remind ourselves that love means to be willing to give until it hurts - Mother Teresa'}
+```
+An instance from `stance_atheism` config:
+```
+{'label': 1, 'text': '@user Bless Almighty God, Almighty Holy Spirit and the Messiah. #SemST'}
+```
+An instance from `stance_climate` config:
+```
+{'label': 0, 'text': 'Why Is The Pope Upset?  via @user #UnzippedTruth #PopeFrancis #SemST'}
+```
+An instance from `stance_feminist` config:
+```
+{'label': 1, 'text': "@user @user is the UK's answer to @user and @user  #GamerGate #SemST"}
+```
+An instance from `stance_hillary` config:
+```
+{'label': 1, 'text': "If a man demanded staff to get him an ice tea he'd be called a sexists elitist pig.. Oink oink #Hillary #SemST"}
+```
+### Data Fields
+For `emoji` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: ❤
+    `1`: 😍
+    `2`: 😂
+    `3`: 💕
+    `4`: 🔥
+    `5`: 😊
+    `6`: 😎
+    `7`: ✨
+    `8`: 💙
+    `9`: 😘
+    `10`: 📷
+    `11`: 🇺🇸
+    `12`: ☀
+    `13`: 💜
+    `14`: 😉
+    `15`: 💯
+    `16`: 😁
+    `17`: 🎄
+    `18`: 📸
+    `19`: 😜
+For `emotion` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: anger
+    `1`: joy
+    `2`: optimism
+    `3`: sadness
+For `hate` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: non-hate
+    `1`: hate
+For `irony` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: non_irony
+    `1`: irony
+For `offensive` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: non-offensive
+    `1`: offensive
+For `sentiment` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: negative
+    `1`: neutral
+    `2`: positive
+For `stance_abortion` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: none
+    `1`: against
+    `2`: favor
+For `stance_atheism` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: none
+    `1`: against
+    `2`: favor
+For `stance_climate` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: none
+    `1`: against
+    `2`: favor
+For `stance_feminist` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: none
+    `1`: against
+    `2`: favor
+For `stance_hillary` config:
+- `text`: a `string` feature containing the tweet.
+- `label`: an `int` classification label with the following mapping:
+    `0`: none
+    `1`: against
+    `2`: favor
+### Data Splits
+| name            | train | validation | test  |
+| --------------- | ----- | ---------- | ----- |
+| emoji           | 45000 | 5000       | 50000 |
+| emotion         | 3257  | 374        | 1421  |
+| hate            | 9000  | 1000       | 2970  |
+| irony           | 2862  | 955        | 784   |
+| offensive       | 11916 | 1324       | 860   |
+| sentiment       | 45615 | 2000       | 12284 |
+| stance_abortion | 587   | 66         | 280   |
+| stance_atheism  | 461   | 52         | 220   |
+| stance_climate  | 355   | 40         | 169   |
+| stance_feminist | 597   | 67         | 285   |
+| stance_hillary  | 620   | 69         | 295   |
+## Dataset Creation
+### Curation Rationale
+[Needs More Information]
+### Source Data
+#### Initial Data Collection and Normalization
+[Needs More Information]
+#### Who are the source language producers?
+[Needs More Information]
+### Annotations
+#### Annotation process
+[Needs More Information]
+#### Who are the annotators?
+[Needs More Information]
+### Personal and Sensitive Information
+[Needs More Information]
+## Considerations for Using the Data
+### Social Impact of Dataset
+[Needs More Information]
+### Discussion of Biases
+[Needs More Information]
+### Other Known Limitations
+[Needs More Information]
+## Additional Information
+### Dataset Curators
+Francesco Barbieri, Jose Camacho-Collados, Luis Espiinosa-Anke and Leonardo Neves through Cardiff NLP.
+### Licensing Information
+This is not a single dataset, therefore each subset has its own license (the collection itself does not have additional restrictions).
+All of the datasets require complying with Twitter [Terms Of Service](https://twitter.com/tos) and Twitter API [Terms Of Service](https://developer.twitter.com/en/developer-terms/agreement-and-policy)
+Additionally the license are:
+- emoji: Undefined
+- emotion(EmoInt): Undefined
+- hate (HateEval): Need permission [here](http://hatespeech.di.unito.it/hateval.html)
+- irony: Undefined
+- Offensive: Undefined
+- Sentiment: [Creative Commons Attribution 3.0 Unported License](https://groups.google.com/g/semevaltweet/c/k5DDcvVb_Vo/m/zEOdECFyBQAJ)
+- Stance: Undefined
+### Citation Information
+```
+@inproceedings{barbieri2020tweeteval,
+title={{TweetEval:Unified Benchmark and Comparative Evaluation for Tweet Classification}},
+author={Barbieri, Francesco and Camacho-Collados, Jose and Espinosa-Anke, Luis and Neves, Leonardo},
+booktitle={Proceedings of Findings of EMNLP},
+year={2020}
+}
+```
+If you use any of the TweetEval datasets, please cite their original publications:
+#### Emotion Recognition:
+```
+@inproceedings{mohammad2018semeval,
+  title={Semeval-2018 task 1: Affect in tweets},
+  author={Mohammad, Saif and Bravo-Marquez, Felipe and Salameh, Mohammad and Kiritchenko, Svetlana},
+  booktitle={Proceedings of the 12th international workshop on semantic evaluation},
+  pages={1--17},
+  year={2018}
+}
+```
+#### Emoji Prediction:
+```
+@inproceedings{barbieri2018semeval,
+  title={Semeval 2018 task 2: Multilingual emoji prediction},
+  author={Barbieri, Francesco and Camacho-Collados, Jose and Ronzano, Francesco and Espinosa-Anke, Luis and
+    Ballesteros, Miguel and Basile, Valerio and Patti, Viviana and Saggion, Horacio},
+  booktitle={Proceedings of The 12th International Workshop on Semantic Evaluation},
+  pages={24--33},
+  year={2018}
+}
+```
+#### Irony Detection:
+```
+@inproceedings{van2018semeval,
+  title={Semeval-2018 task 3: Irony detection in english tweets},
+  author={Van Hee, Cynthia and Lefever, Els and Hoste, V{\'e}ronique},
+  booktitle={Proceedings of The 12th International Workshop on Semantic Evaluation},
+  pages={39--50},
+  year={2018}
+}
+```
+#### Hate Speech Detection:
+```
+@inproceedings{basile-etal-2019-semeval,
+    title = "{S}em{E}val-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in {T}witter",
+    author = "Basile, Valerio  and Bosco, Cristina  and Fersini, Elisabetta  and Nozza, Debora and Patti, Viviana and
+      Rangel Pardo, Francisco Manuel  and Rosso, Paolo  and Sanguinetti, Manuela",
+    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
+    year = "2019",
+    address = "Minneapolis, Minnesota, USA",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/S19-2007",
+    doi = "10.18653/v1/S19-2007",
+    pages = "54--63"
+}
+```
+#### Offensive Language Identification:
+```
+@inproceedings{zampieri2019semeval,
+  title={SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)},
+  author={Zampieri, Marcos and Malmasi, Shervin and Nakov, Preslav and Rosenthal, Sara and Farra, Noura and Kumar, Ritesh},
+  booktitle={Proceedings of the 13th International Workshop on Semantic Evaluation},
+  pages={75--86},
+  year={2019}
+}
+```
+#### Sentiment Analysis:
+```
+@inproceedings{rosenthal2017semeval,
+  title={SemEval-2017 task 4: Sentiment analysis in Twitter},
+  author={Rosenthal, Sara and Farra, Noura and Nakov, Preslav},
+  booktitle={Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017)},
+  pages={502--518},
+  year={2017}
+}
+```
+#### Stance Detection:
+```
+@inproceedings{mohammad2016semeval,
+  title={Semeval-2016 task 6: Detecting stance in tweets},
+  author={Mohammad, Saif and Kiritchenko, Svetlana and Sobhani, Parinaz and Zhu, Xiaodan and Cherry, Colin},
+  booktitle={Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)},
+  pages={31--41},
+  year={2016}
+}
+```