README.md

---
license: apache-2.0
tags:
- data-juicer
- pretraining
task_categories:
- text-generation
language:
- en
size_categories:
- 10K<n<100K
---
# The Pile -- PhilPaper (refined by Data-Juicer)

A refined version of PhilPaper dataset in The Pile by [Data-Juicer](https://github.com/alibaba/data-juicer). Removing some "bad" samples from the original dataset to make it higher-quality.

This dataset is usually used to pretrain a Large Language Model.

**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/the-pile-philpaper-refine-result.jsonl) (About 1.7GB).

## Dataset Information

- Number of samples: 29,117 (Keep ~88.82% from the original dataset)

## Refining Recipe
```yaml
# global parameters
project_name: 'our-recipes-Philpaper'
dataset_path: '/path/to/the/original/dataset/'  # path to your dataset directory or file
export_path: 'Philpaper-refine-result.jsonl' # path to your dataset result file

np: 50  # number of subprocess to process your dataset
ds_cache_dir: /cache # path to your dataset cache file
open_tracer: true

# process schedule
# a list of several process operators with their arguments
process:
  - clean_email_mapper:
  - clean_links_mapper:
  - fix_unicode_mapper:
  - punctuation_normalization_mapper:
  - whitespace_normalization_mapper:

  - alphanumeric_filter:
      tokenization: false
      min_ratio: 0.7  # <3sigma (0.72)
  - average_line_length_filter:
      max_len: 5e5  # >3sigma (406006)
  - character_repetition_filter:
      rep_len: 10
      max_ratio: 0.2  # >3sigma (0.145)
  - flagged_words_filter:
      lang: en
      tokenization: true
      max_ratio: 0.0007  # 3sigma
  - language_id_score_filter:  
      min_score: 0.6
  - maximum_line_length_filter:
      max_len: 1e6  # 3sigma
  - perplexity_filter:
      lang: en
      max_ppl: 5000 
  - special_characters_filter:
      max_ratio: 0.4  # > 3sigma (0.302)
  - words_num_filter:
      lang: en
      tokenization: true
      min_num: 1000  
      max_num: 2e5  # 3sigma
  - word_repetition_filter:
      lang: en
      tokenization: true
      rep_len: 10
      max_ratio: 0.3  # > 3sigma (0.249)

  - document_simhash_deduplicator:
      tokenization: space
      window_size: 6
      lowercase: true
      ignore_pattern: '\p{P}'
      num_blocks: 6
      hamming_distance: 4
```