Datasets:
Maurice Weber
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update README.md
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README.md
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@@ -83,54 +83,50 @@ RedPajama-V2 is an open dataset for training large laguage models and includes o
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#### Quality Annotations
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| Annotation Tag
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| ccnet_bucket
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| ccnet_language_score
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| ccnet_length
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| ccnet_nlines
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| ccnet_original_length
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| ccnet_original_nlines
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| ccnet_perplexity
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| rps_doc_frac_chars_top_4gram | The fraction of characters in the top word 4gram. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_ldnoobw_words | The number of sequences of words that are contained in the List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words blocklist. The blocklist is obtained from [GitHub](https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words). | toxicity | C4 |
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| rps_doc_ut1_blacklist | A categorical id corresponding to the list of categories of the domain of the document. Categories are obtained from the UT1 blacklist. The list is obtained from [UT-Capitole](https://dsi.ut-capitole.fr/blacklists/). | toxicictiy | RefinedWeb |
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#### Document Counts for the Annotated part of the dataset
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#### Quality Annotations
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| Annotation Tag | Description | Category | Reference |
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|------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|------------------------------------|
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| ccnet_bucket | head, middle or tail bucket of the perplexity score | ccnet | ccnet |
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| ccnet_language_score | score of the language identification model | ccnet | ccnet |
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| ccnet_length | number of characters | ccnet | ccnet |
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| ccnet_nlines | number of lines | ccnet | ccnet |
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| ccnet_original_length | number of characters before in-document line deduplication | ccnet | ccnet |
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| ccnet_original_nlines | number of lines before in-document line deduplication | ccnet | ccnet |
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| ccnet_perplexity | perplexity of an LM trained on Wikipedia | ccnet | ccnet |
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| rps_doc_books_importance | Given a bag of {1,2}-wordgram model trained on Books p, and a model trained on the source domain q, This is the logarithm of the ratio p(doc)/q(doc). | ML Heuristics | Importance Resampling (Xie et al.) |
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| rps_doc_openwebtext_importance | Given a bag of {1,2}-wordgram model trained on OpenWebText p, and a model trained on the source domain q, this is the logarithm of the ratio p(doc)/q(doc). | ML Heuristics | Importance Resampling (Xie et al.) |
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| rps_doc_wikipedia_importance | Given a bag of {1,2}-wordgram model trained on Wikipedia articles p, and a model trained on the source domain q, this is the logarithm of the ratio p(doc)/q(doc). | ML Heuristics | Importance Resampling (Xie et al.) |
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| rps_doc_ml_wikiref_score | Fasttext classifier prediction for the document being a Wikipedia reference. This is the same fasttext model used in the RedPajama-1T dataset. Only applies to English data.. | ML Heuristics | LLaMA, RedPajama-1T |
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| rps_doc_ml_palm_score | Fasttext classifier prediction for the document being a Wikipedia article, OpenWebText sample or a RedPajama-V1 book. Only for English data. | ML Heuristics | PaLM, GLaM |
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| rps_doc_ml_wikipedia_score | Fasttext classifier prediction for the document being a Wikipedia article. This is used for non-English data | ML Heuristics | - |
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| rps_doc_curly_bracket | The ratio between the number of occurrences of '{' or '}' and the number of characters in the raw text. | Natural Language | C4 |
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| rps_doc_frac_all_caps_words | The fraction of words in the content that only consist of uppercase letters. This is based on the raw content. | Natural Language | Pretrainer’s Guide |
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| rps_doc_frac_lines_end_with_ellipsis | The fraction of lines that end with an ellipsis, where an ellipsis is defined as either "..." or "…". | Natural Language | RefinedWeb, Gopher |
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| rps_doc_frac_no_alph_words | The fraction of words that contain no alphabetical character. | Natural Language | RefinedWeb, Gopher |
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| rps_doc_lorem_ipsum | The ratio between the number of occurrences of 'lorem ipsum' and the number of characters in the content after normalisation. | Natural Language | C4 |
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| rps_doc_mean_word_length | The mean length of words in the content after normalisation. | Natural Language | RefinedWeb, Gopher |
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| rps_doc_stop_word_fraction | The ratio between the number of stop words and the number of words in the document. Stop words are obtained from https://github.com/6/stopwords-json. | Natural Language | RefinedWeb, Gopher |
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| rps_doc_symbol_to_word_ratio | The ratio of symbols to words in the content.. Symbols are defined "#", "...", and "…". | Natural Language | RefinedWeb, Gopher |
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| rps_doc_frac_unique_words | The fraction of unique words in the content. This is also known as the degeneracy of a text sample. Calculated based on the normalised content. | Natural Language | Pretrainer’s Guide |
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| rps_doc_unigram_entropy | The entropy of the unigram distribution of the content. This measures the diversity of the content and is computed using sum(-x / total * log(x / total)) where the sum is taken over counts of unique words in the normalised content. | Natural Language | - |
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| rps_doc_word_count | The number of words in the content after normalisation. | Natural Language | RefinedWeb, Gopher |
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| rps_lines_ending_with_terminal_punctution_mark | Indicates whether a line ends with a terminal punctuation mark. A terminal punctation mark is defined as one of: ".", "!", "?", "”". | Natural Language | C4 |
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| rps_lines_javascript_counts | The number of occurrences of the word "javascript" in each line. | Natural Language | C4 |
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| rps_lines_num_words | The number of words in each line. This is computed based on the normalised text. | Natural Language | C4, RefinedWeb |
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| rps_lines_numerical_chars_fraction | The ratio between the number of numerical characters and total number of characters in each line. This is based on the normalised content. | Natural Language | RefinedWeb |
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| rps_lines_start_with_bulletpoint | Whether the lines that start with a bullet point symbol. The following set of unicodes are considered a bullet point: \u2022 (bullet point), \u2023 (triangular bullet point), \u25B6 (black right pointing triangle), \u25C0 (black left pointing triangle), \u25E6 (white bullet point), \u25A0 (black square), \u25A1 (white square), \u25AA (black small square), \u25AB (white small square), \u2013 (en dash). | Natural Language | RefinedWeb, Gopher |
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| rps_lines_uppercase_letter_fraction | The ratio between the number of uppercase letters and total number of characters in each line. This is based on the raw text. | Natural Language | RefinedWeb |
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| rps_doc_num_sentences | The number of sentences in the content. This is calculated using the regular expression `r'\b[^.!?]+[.!?]*'`. | Natural Language | C4 |
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| rps_doc_frac_chars_dupe_10grams | The fraction of characters in duplicate word 10grams. This operates on the lower-cased, punctuation removed content. It is also ensured that characters in overlapping ngrams are only counted once. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_dupe_5grams | The fraction of characters in duplicate word 5grams. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_dupe_6grams | The fraction of characters in duplicate word 6grams. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_dupe_7grams | The fraction of characters in duplicate word 7grams. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_dupe_8grams | The fraction of characters in duplicate word 8grams. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_dupe_9grams | The fraction of characters in duplicate word 9grams. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_top_2gram | The fraction of characters in the top word 2gram. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_top_3gram | The fraction of characters in the top word 3gram. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_frac_chars_top_4gram | The fraction of characters in the top word 4gram. | Repetitiveness | RefinedWeb, Gopher |
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| rps_doc_ldnoobw_words | The number of sequences of words that are contained in the List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words blocklist. The blocklist is obtained from [GitHub](https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words). | toxicity | C4 |
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| rps_doc_ut1_blacklist | A categorical id corresponding to the list of categories of the domain of the document. Categories are obtained from the UT1 blacklist. The list is obtained from [UT-Capitole](https://dsi.ut-capitole.fr/blacklists/). | toxicictiy | RefinedWeb |
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#### Document Counts for the Annotated part of the dataset
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