update readme
Browse files
README.md
CHANGED
@@ -1,3 +1,82 @@
|
|
1 |
---
|
2 |
license: apache-2.0
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
license: apache-2.0
|
3 |
+
task_categories:
|
4 |
+
- text-generation
|
5 |
+
language:
|
6 |
+
- en
|
7 |
+
tags:
|
8 |
+
- data-juicer
|
9 |
---
|
10 |
+
|
11 |
+
# The Pile -- HackerNews (refined by Data-Juicer)
|
12 |
+
|
13 |
+
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.
|
14 |
+
|
15 |
+
This dataset is usually used to pretrain a Large Language Model.
|
16 |
+
|
17 |
+
**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).
|
18 |
+
|
19 |
+
## Dataset Information
|
20 |
+
|
21 |
+
- Number of samples: 371,331 (Keep ~99.55% from the original dataset)
|
22 |
+
|
23 |
+
## Refining Recipe
|
24 |
+
```yaml
|
25 |
+
# global parameters
|
26 |
+
project_name: 'Data-Juicer-recipes-HackerNews'
|
27 |
+
dataset_path: '/path/to/your/dataset' # path to your dataset directory or file
|
28 |
+
export_path: '/path/to/your/dataset.jsonl'
|
29 |
+
|
30 |
+
np: 48 # number of subprocess to process your dataset
|
31 |
+
open_tracer: true
|
32 |
+
|
33 |
+
# process schedule
|
34 |
+
# a list of several process operators with their arguments
|
35 |
+
process:
|
36 |
+
- clean_email_mapper:
|
37 |
+
#- clean_links_mapper:
|
38 |
+
- fix_unicode_mapper:
|
39 |
+
- punctuation_normalization_mapper:
|
40 |
+
- whitespace_normalization_mapper:
|
41 |
+
|
42 |
+
- alphanumeric_filter:
|
43 |
+
tokenization: false
|
44 |
+
min_ratio: 0.2 #<3sigma
|
45 |
+
- average_line_length_filter:
|
46 |
+
min_len: 15 # >3sigma
|
47 |
+
- character_repetition_filter:
|
48 |
+
rep_len: 10
|
49 |
+
max_ratio: 0.3 # >3sigma
|
50 |
+
- flagged_words_filter:
|
51 |
+
lang: en
|
52 |
+
tokenization: true
|
53 |
+
max_ratio: 0.05 # >3sigma
|
54 |
+
- language_id_score_filter:
|
55 |
+
min_score: 0.2 # <3sigma
|
56 |
+
- maximum_line_length_filter:
|
57 |
+
min_len: 20 # >3sigma
|
58 |
+
- perplexity_filter:
|
59 |
+
lang: en
|
60 |
+
max_ppl: 10000 # >3sigma
|
61 |
+
- special_characters_filter:
|
62 |
+
max_ratio: 0.7 # >3sigma
|
63 |
+
- text_length_filter:
|
64 |
+
min_len: 100 # > 3sigma
|
65 |
+
- words_num_filter:
|
66 |
+
lang: en
|
67 |
+
tokenization: true
|
68 |
+
min_num: 30 # > 3sigma
|
69 |
+
- word_repetition_filter:
|
70 |
+
lang: en
|
71 |
+
tokenization: true
|
72 |
+
rep_len: 10
|
73 |
+
max_ratio: 0.8 # > 3sigma
|
74 |
+
|
75 |
+
- document_simhash_deduplicator:
|
76 |
+
tokenization: space
|
77 |
+
window_size: 6
|
78 |
+
lowercase: true
|
79 |
+
ignore_pattern: '\p{P}'
|
80 |
+
num_blocks: 6
|
81 |
+
hamming_distance: 4
|
82 |
+
```
|