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Datasets:
cardiffnlp
/
super_tweeteval

Tasks:
Text Classification
Token Classification
Question Answering
Modalities:
Tabular
Text
Formats:
json
Sub-tasks:
topic-classification
named-entity-recognition
abstractive-qa
Languages:
English
Size:
100K - 1M
ArXiv:
Tags:
super_tweet_eval
tweet_eval
natural language understanding
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
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@@ -140,18 +140,18 @@ In the following we present the information contained in each of the datasets.
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  | **dataset** | **evaluation metric** | **gold label** | **model card** |
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  |-------------------|-------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------|
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- | TweetTopic | ```macro-F1``` | _arts\_&\_culture, business\_&\_entrepreneurs, celebrity\_&\_pop\_culture, <br />diaries\_&\_daily\_life, family, fashion\_&\_style, <br />film\_tv\_&\_video, fitness\_&\_health, food\_&\_dining, <br />gaming, learning\_&\_educational, music, <br />news\_&\_social\_concern, other\_hobbies, relationships, <br />science\_&\_technology, sports, travel\_&\_adventure, <br />youth\_&\_student\_life_ | |
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- | TweetNER7 | ```macro-F1``` | _B-corporation, B-creative_work, B-event, <br />B-group, B-location, B-person, <br />B-product, I-corporation, I-creative_work, <br />I-event, I-group, I-location, <br />I-person, I-product, O_ | |
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- | TweettQA | ```answer-F1``` | - | |
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- | TweetQG | ```METEOR``` | - | |
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- | TweetIntimacy | ```spearman correlation``` | _[1 - 5]_ | |
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- | TweetSIM | ```spearman correlation``` | _[0 - 5]_ | |
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- | TempoWIC | ```accuracy``` | _no, yes_ | |
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- | TweetHate | ```combined-F1```<br /> ```(micro-F1 for hate/not-hate &```<br /> ``` macro-F1 for hate speech subclasses)``` | _hate_gender, hate_race, hate_sexuality, hate_religion, hate_origin, <br />hate_disability, hate_age, not_hate_ | |
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- | TweetEmoji100 | ```accuracy at top 5``` | _Full emoji list: ./data/tweet_emoji/map.txt_ | |
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- | TweetSentiment | ```1 - MAE^M``` <br /> ```(MAE^M : Macro Averaged Mean Absolute Error)``` | _'strongly negative' , 'negative', 'negative or neutral', <br /> 'positive', 'strongly positive'_ | |
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- | TweetNERD | ```accuracy``` | _no, yes_ | |
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- | TweetEmotion | ```macro-F1``` | _anger, anticipation, disgust, fear, joy, love, optimism, <br />pessimism, sadness, surprise, trust_ | |
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  | **dataset** | **evaluation metric** | **gold label** | **model card** |
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  |-------------------|-------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------|
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+ | TweetTopic | ```macro-F1``` | _arts\_&\_culture, business\_&\_entrepreneurs, celebrity\_&\_pop\_culture, <br />diaries\_&\_daily\_life, family, fashion\_&\_style, <br />film\_tv\_&\_video, fitness\_&\_health, food\_&\_dining, <br />gaming, learning\_&\_educational, music, <br />news\_&\_social\_concern, other\_hobbies, relationships, <br />science\_&\_technology, sports, travel\_&\_adventure, <br />youth\_&\_student\_life_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-topic) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-topic) |
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+ | TweetNER7 | ```macro-F1``` | _B-corporation, B-creative_work, B-event, <br />B-group, B-location, B-person, <br />B-product, I-corporation, I-creative_work, <br />I-event, I-group, I-location, <br />I-person, I-product, O_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-ner7) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-ner7) |
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+ | TweettQA | ```answer-F1``` | - | [flan-t5-small](https://huggingface.co/cardiffnlp/flan-t5-small-tweet-qa) <br> [flan-t5-base](https://huggingface.co/cardiffnlp/flan-t5-base-tweet-qa) |
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+ | TweetQG | ```METEOR``` | - | [flan-t5-small](https://huggingface.co/cardiffnlp/flan-t5-small-tweet-qg) <br> [flan-t5-base](https://huggingface.co/cardiffnlp/flan-t5-base-tweet-qg) |
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+ | TweetIntimacy | ```spearman correlation``` | _[1 - 5]_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-intimacy) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-intimacy) |
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+ | TweetSIM | ```spearman correlation``` | _[0 - 5]_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-similarity) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-similarity) |
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+ | TempoWIC | ```accuracy``` | _no, yes_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tempo-wic) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tempo-wic) |
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+ | TweetHate | ```combined-F1```<br /> ```(micro-F1 for hate/not-hate &```<br /> ``` macro-F1 for hate speech subclasses)``` | _hate_gender, hate_race, hate_sexuality, hate_religion, hate_origin, <br />hate_disability, hate_age, not_hate_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-hate) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-hate) |
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+ | TweetEmoji100 | ```accuracy at top 5``` | _Full emoji list: ./data/tweet_emoji/map.txt_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-emoji) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-emoji) |
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+ | TweetSentiment | ```1 - MAE^M``` <br /> ```(MAE^M : Macro Averaged Mean Absolute Error)``` | _'strongly negative' , 'negative', 'negative or neutral', <br /> 'positive', 'strongly positive'_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-sentiment) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-sentiment) |
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+ | TweetNERD | ```accuracy``` | _no, yes_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-nerd) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-nerd) |
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+ | TweetEmotion | ```macro-F1``` | _anger, anticipation, disgust, fear, joy, love, optimism, <br />pessimism, sadness, surprise, trust_ | [twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base-latest-tweet-emotion) <br> [twitter-roberta-large](https://huggingface.co/cardiffnlp/twitter-roberta-large-latest-tweet-emotion) |
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