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import pandas as pd |
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from datasets import load_dataset |
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table = [] |
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task_description = { |
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'tweet_intimacy': "regression on a single text", |
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'tweet_ner7': "sequence labeling", |
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'tweet_qa': "generation", |
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'tweet_similarity': "regression on two texts", |
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'tweet_topic': "multi-label classification" |
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} |
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for task in ['tweet_intimacy', 'tweet_ner7', 'tweet_qa', 'tweet_similarity', 'tweet_topic']: |
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data = load_dataset("cardiffnlp/super_tweet_eval", task) |
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tmp_table = {"task": task, "description": task_description[task]} |
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tmp_table['number of instances'] = " / ".join([str(len(data[s])) for s in ['train', 'validation', 'test']]) |
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table.append(tmp_table) |
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df = pd.DataFrame(table) |
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print(df.to_markdown(index=False)) |
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