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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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task_categories:
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- text-generation
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language:
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- en
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tags:
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- data-juicer
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- pretraining
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size_categories:
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- 100M<n<1B
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---
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# RedPajama -- C4 (refined by Data-Juicer)
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A refined version of C4 dataset in RedPajama by [Data-Juicer](https://github.com/alibaba/data-juicer). Removing some "bad" samples from the original dataset to make it higher-quality.
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This dataset is usually used to pretrain a Large Language Model.
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**Notice**: Here is a small subset for previewing. The whole dataset is available [here](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/LLM_data/our_refined_datasets/pretraining/redpajama-c4-refine-result.jsonl) (About 832GB).
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## Dataset Information
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- Number of samples: 344,491,171 (Keep ~94.42% from the original dataset)
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## Refining Recipe
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```yaml
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# global parameters
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project_name: 'Data-Juicer-recipes-c4'
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dataset_path: '/path/to/your/dataset' # path to your dataset directory or file
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export_path: '/path/to/your/dataset.jsonl' # path to your dataset result file
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np: 50 # number of subprocess to process your dataset
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open_tracer: True
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# process schedule
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# a list of several process operators with their arguments
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process:
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- clean_email_mapper:
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- clean_links_mapper:
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- fix_unicode_mapper:
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- punctuation_normalization_mapper:
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- whitespace_normalization_mapper:
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- alphanumeric_filter:
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tokenization: false
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min_ratio: 0.65 # <3sigma (0.740)
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max_ratio: 0.9 # >3sigma (0.867)
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- average_line_length_filter: # for code
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max_len: 3000 # >3sigma (1277)
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- character_repetition_filter:
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rep_len: 10
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max_ratio: 0.3 # >3sigma (0.168)
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- language_id_score_filter:
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min_score: 0.6
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- maximum_line_length_filter: # for code
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max_len: 4000 # >3sigma (2017)
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- perplexity_filter:
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lang: en
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max_ppl: 6000 #(>3sigma 4543)
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- special_characters_filter:
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max_ratio: 0.4 # > 3sigma (0.303)
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- words_num_filter:
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tokenization: true
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min_num: 20
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max_num: 10000
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- word_repetition_filter:
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lang: en
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tokenization: true
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rep_len: 10
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max_ratio: 0.231 # 3sigma
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- document_simhash_deduplicator:
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tokenization: space
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window_size: 6
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lowercase: true
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ignore_pattern: '\p{P}'
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num_blocks: 6
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hamming_distance: 4
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```
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