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license: mit |
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task_categories: |
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- text-classification |
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- token-classification |
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size_categories: |
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- 1M<n<10M |
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datasets: |
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- tomekkorbak/pile-toxicity-balanced2 |
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- datasets/thai_toxicity_tweet |
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--- |
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About 11 months ago, I downloaded and preprocessed 2.7M rows of text data, but completely forgot the original source of these datasets... |
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All I know is that I looked everywhere: HuggingFace, research papers, GitHub, Kaggle, and Google search. I even fetched 20K+ tweets using the Twitter API. |
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Today (6/28/2023) I came across three newer HuggingFace datasets, so I added them to this dataset. |
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The deduplicated training data alone consists of 2,880,230 rows of comments and messages. Among these rows, 416,457 are classified as toxic, while the remaining 2,463,773 are considered neutral. Below is a table to illustrate the data composition: |
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| | Toxic | Neutral | Total | |
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|-------|----------|----------|----------| |
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| [multilingual-train-deduplicated.csv](./multilingual-train-deduplicated.csv) | 416,457 | 2,463,773 | 2,880,230 | |
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| [multilingual-validation.csv](./multilingual-validation.csv) | 1,230 | 6,770 | 8,000 | |
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| [multilingual-test.csv](./multilingual-test.csv) | 14,410 | 49,402 | 63,812 | |
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Each CSV file has two columns: `text` and `is_toxic`. |
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Have fun modelling! |
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