File size: 2,332 Bytes
c1eb3e4 5e77c4c 9e91011 c1eb3e4 5e77c4c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
---
license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- data-juicer
- pretraining
size_categories:
- 100K<n<1M
---
# The Pile -- HackerNews (refined by Data-Juicer)
A refined version of HackerNews 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-hackernews-refine-result.jsonl) (About 1.8G).
## Dataset Information
- Number of samples: 371,331 (Keep ~99.55% from the original dataset)
## Refining Recipe
```yaml
# global parameters
project_name: 'Data-Juicer-recipes-HackerNews'
dataset_path: '/path/to/your/dataset' # path to your dataset directory or file
export_path: '/path/to/your/dataset.jsonl'
np: 48 # number of subprocess to process your dataset
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: 0.2 #<3sigma
- average_line_length_filter:
min_len: 15 # >3sigma
- character_repetition_filter:
rep_len: 10
max_ratio: 0.3 # >3sigma
- flagged_words_filter:
lang: en
tokenization: true
max_ratio: 0.05 # >3sigma
- language_id_score_filter:
min_score: 0.2 # <3sigma
- maximum_line_length_filter:
min_len: 20 # >3sigma
- perplexity_filter:
lang: en
max_ppl: 10000 # >3sigma
- special_characters_filter:
max_ratio: 0.7 # >3sigma
- text_length_filter:
min_len: 100 # > 3sigma
- words_num_filter:
lang: en
tokenization: true
min_num: 30 # > 3sigma
- word_repetition_filter:
lang: en
tokenization: true
rep_len: 10
max_ratio: 0.8 # > 3sigma
- document_simhash_deduplicator:
tokenization: space
window_size: 6
lowercase: true
ignore_pattern: '\p{P}'
num_blocks: 6
hamming_distance: 4
``` |