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README.md CHANGED
@@ -1,11 +1,5 @@
1
  ---
2
  license: odc-by
3
- task_categories:
4
- - text-generation
5
- language:
6
- - en
7
- size_categories:
8
- - n>1T
9
  ---
10
  # TxT360: A Top-Quality LLM Pre-training Dataset Requires the Perfect Blend
11
  <center><img src="llm360_logo(1).png" alt="k2 eval table" /></center>
@@ -16,7 +10,7 @@ size_categories:
16
  | Data Source | TxT360 | FineWeb | RefinedWeb | PedPajamaV2 | C4 | Dolma | RedPajamaV1 | The Pile |
17
  |---------------------------|--------|---------|------------|-------------|----|-------|-------------|--------------------|
18
  | CommonCrawl Snapshots | 99 | 96 | 90 | 84 | 1 | 24 | 5 | 0.6% of 74 |
19
- | Papers | 5 Sources | - | - | - | - | 1 Source | 1 Source | 4 Sources |
20
  | Wikipedia | 310+ Languages | - | - | - | - | Included | Included | English Only |
21
  | FreeLaw | Included | - | - | - | - | - | - | Included |
22
  | DM Math | Included | - | - | - | - | - | - | Included |
@@ -25,11 +19,12 @@ size_categories:
25
  | HackerNews | Included | - | - | - | - | - | - | Included |
26
  | Ubuntu IRC | Included | - | - | - | - | - | - | Included |
27
  | EuroParl | Included | - | - | - | - | - | - | Included |
28
- | StackExchange | Included | - | - | - | - | - | - | Included |
29
  | Code | * | - | - | - | - | Included | Included | Included |
30
 
31
  * TxT360 does not include code. This decision was made due to the perceived low duplication code with other sources.
32
 
 
33
 
34
  Complete details on the dataset can be found in our blog post [here](https://huggingface.co/spaces/LLM360/TxT360).
35
 
@@ -56,10 +51,10 @@ We further highlight the importance of mixing the datasets together with the rig
56
  | DM Math | 22 GB | 5.23B | - |
57
  | USPTO | 45 GB | 4.95B | Q3 2024 |
58
  | PG-19 | 11 GB | 2.63B | - |
59
- | HackerNews | 4.2 GB | 1.05B | Q4 2023 |
60
- | Ubuntu IRC | 6 GB | 1.89B | Q3 2024 |
61
  | Europarl | 6.1 GB | 1.96B | - |
62
- | StackExchange | 81 GB | 27.76B | Q4 2023 |
63
 
64
  The [TxT360](https://huggingface.co/spaces/LLM360/TxT360) blog post provides all the details behind how we approached and implemented the following features:
65
 
@@ -72,161 +67,6 @@ Each data source was filtered individually with respect to the underlying data.
72
  ## Global Deduplication
73
  After the web and curated sources were filtered, all sources globally deduplicated to create TxT360. The tips and tricks behind the deduplication process are included.
74
 
75
- ## Dataset Structure
76
- The dataset is organized under the ```data``` directory, with each subdirectory representing a data subset.
77
- Below is an overview of the structure and organization of these subsets:
78
- ```
79
- ├── data
80
- ├── common-crawl # data subset
81
- ├── CC-MAIN-2013-20 # common-crawl dumps
82
- ├── 1-1 # number of duplicates
83
- ├── chunk_000_0000.jsonl.gz
84
- ├── ...
85
- ├── 2-5
86
- ├── chunk_000_0000.jsonl.gz
87
- ├── ...
88
- ├── ...
89
- ├── CC-MAIN-2013-48
90
- ├── 1-1
91
- ├── chunk_000_0000.jsonl.gz
92
- ├── ...
93
- ├── ...
94
- ├── ...
95
- ├── dm_math
96
- ├── full_data_1
97
- ├── 0_11255.jsonl
98
- ├── ...
99
- ├── full_data_2
100
- ├── 10000_11255.jsonl
101
- ├── ...
102
- ├── arxiv
103
- ├── 1-1 # number of duplicates
104
- ├── 0_171.jsonl
105
- ├── ...
106
- ├── 2-5
107
- ├── 0_2.jsonl
108
- ├── ...
109
- ├── ...
110
- ├── europarl
111
- ├── 1-1 # number of duplicates
112
- ├── 0_6.jsonl
113
- ├── ...
114
- ├── 2-5
115
- ├── 0_0.jsonl
116
- ├── ...
117
- ├── ...
118
- ├── ...
119
- ```
120
-
121
- ### Common Crawl (common-crawl)
122
- Each subdirectory under ```common-crawl``` corresponds to a specific dump of the dataset.
123
- Inside each dump folder, the data is further segmented into buckets based on the number of duplicates identified during deduplication:
124
-
125
- - ```1-1```: Contains documents with no duplicates across the dataset.
126
- - ```2-5```, ```6-10```, ```11-100```, ```101-1000```, ```1001-30000000```: Each contains documents that fall within the respective range of duplicates.
127
-
128
- Example path: ```data/common-crawl/CC-MAIN-2013-20/1-1/chunk_000_0000.jsonl.gz```
129
-
130
- ### DM Math (dm_math)
131
- The ```dm_math``` subset is divided into two subfolders to comply with the limit of 10,000 files per folder in a HuggingFace Repository:
132
-
133
- Example path: ```data/dm_math/full_data_1/0_11255.jsonl```
134
-
135
- ### Others
136
- Similar to common-crawl, other curated data subsets, such as arxiv, europal, etc., are organized by the number of duplicates:
137
- - ```1-1```, ```2-5```, ```6-10```, ```11-100```, ```101-1000```, ```1001-inf```
138
-
139
- Kindly note that some data subsets might not include the folder ```1001-inf``` (```1001-30000000``` in ```common-crawl```) or might contain only a few documents in such a folder due to the rarity of documents duplicated more than 1000 times.
140
-
141
- ## Data Schema
142
-
143
- ### Common Crawl (common-crawl)
144
- The documents in common-crawl follow the schema:
145
- ```python
146
- {'text': '...', # texts in the document
147
- 'meta':
148
- {
149
- 'lang': 'en', # top 1 language detected by fastText model
150
- 'lang_score': 0.912118136882782, # language score for the detected language
151
- 'url': 'http://www.shopgirljen.com/2017/10/lg-celebrates-5-years-of-lg-oled-tv.html', # the url that raw webpage is scraped from
152
- 'timestamp': '2024-07-24T00:56:12Z', # timestamp from Common Crawl raw data
153
- 'cc-path': 'crawl-data/CC-MAIN-2024-30/segments/1720763518130.6/warc/CC-MAIN-20240723224601-20240724014601-00300.warc.gz', # the path of the document in the raw Common Crawl
154
- 'quality_signals':
155
- {
156
- 'url_score': 0.0,
157
- 'fraction_of_duplicate_lines': 0.0,
158
- 'fraction_of_characters_in_duplicate_lines': 0.0,
159
- 'fraction_of_duplicate_paragraphs': 0.0,
160
- 'fraction_of_characters_in_duplicate_paragraphs': 0.0,
161
- 'fraction_of_characters_in_most_common_ngram': [[2, 0.03626373626373627],
162
- [3, 0.03296703296703297],
163
- [4, 0.01868131868131868]],
164
- 'fraction_of_characters_in_duplicate_ngrams': [[5, 0.01868131868131868],
165
- [6, 0.01868131868131868],
166
- [7, 0.01868131868131868],
167
- [8, 0.0],
168
- [9, 0.0],
169
- [10, 0.0]],
170
- 'fraction_of_words_corrected_in_lines': 0.0,
171
- 'fraction_of_lines_ending_with_ellipsis': 0.0,
172
- 'fraction_of_lines_starting_with_bullet_point': 0.0,
173
- 'fraction_of_lines_with_toxic_words': 0.0,
174
- 'num_of_lines_with_toxic_words': 0,
175
- 'num_of_toxic_words': 0,
176
- 'word_count': 358,
177
- 'mean_word_length': 5.083798882681564,
178
- 'num_of_sentences': 19,
179
- 'symbol_to_word_ratio': 0.0,
180
- 'fraction_of_words_with_alpha_character': 1.0,
181
- 'num_of_stop_words': 82,
182
- 'num_of_paragraphs': 0,
183
- 'has_curly_bracket': False,
184
- 'has_lorem_ipsum': False,
185
- 'orig_text_has_dup_lines': False
186
- },
187
- 'dup_signals':
188
- {
189
- 'dup_doc_count': 166, # the number of duplicated documents
190
- 'dup_dump_count': 57, # the number of dumps that the duplicated documents are from
191
- 'dup_details': # the dump distribution of the duplicated documents
192
- {
193
- '2024-30': 2,
194
- '2024-26': 1,
195
- '2024-22': 1,
196
- ...
197
- }
198
- }
199
- },
200
- 'subset': 'commoncrawl'}
201
- ```
202
-
203
- Please note that documents without duplicates, located in folders `*/1-1/`, have an empty `dup_signals` field.
204
- Additionally, some documents with duplicates might include an `unknown` entry within the `dup_details`.
205
- One example could be:
206
- ```python
207
- {'text': '...', # texts in the document
208
- 'meta':
209
- {
210
- ...
211
- 'dup_signals':
212
- {
213
- 'dup_doc_count': 7,
214
- 'dup_dump_count': 3,
215
- 'dup_details':
216
- {
217
- 'unknown': 4,
218
- '2024-30': 1,
219
- '2024-26': 1,
220
- '2024-22': 1,
221
- }
222
- }
223
- },
224
- 'subset': 'commoncrawl'}
225
- ```
226
- This occurs because the distribution of duplicates across dumps was not recorded in the early stages of our deduplication process, and only the total count of duplicate documents (`dup_doc_count`) was maintained.
227
- Due to the high cost of rerunning the deduplication, we have opted to label these distributions as `unknown` when integrating them with other documents for which duplicate distribution data is available.
228
- In these cases, the `dup_dump_count` is calculated excluding the `unknown`.
229
-
230
  # Citation
231
 
232
  **BibTeX:**
@@ -234,7 +74,7 @@ In these cases, the `dup_dump_count` is calculated excluding the `unknown`.
234
  ```bibtex
235
  @misc{txt360data2024,
236
  title={TxT360: A Top-Quality LLM Pre-training Dataset Requires the Perfect Blend},
237
- author={Liping Tang, Nikhil Ranjan, Omkar Pangarkar, Xuezhi Liang, Zhen Wang, Li An, Bhaskar Rao, Linghao Jin, Huijuan Wang, Zhoujun Cheng, Suqi Sun, Cun Mu, Victor Miller, Xuezhe Ma, Yue Peng, Zhengzhong Liu, Eric P. Xing},
238
  year={2024}
239
  }
240
- ```
 
1
  ---
2
  license: odc-by
 
 
 
 
 
 
3
  ---
4
  # TxT360: A Top-Quality LLM Pre-training Dataset Requires the Perfect Blend
5
  <center><img src="llm360_logo(1).png" alt="k2 eval table" /></center>
 
10
  | Data Source | TxT360 | FineWeb | RefinedWeb | PedPajamaV2 | C4 | Dolma | RedPajamaV1 | The Pile |
11
  |---------------------------|--------|---------|------------|-------------|----|-------|-------------|--------------------|
12
  | CommonCrawl Snapshots | 99 | 96 | 90 | 84 | 1 | 24 | 5 | 0.6% of 74 |
13
+ | Papers** | 5 Sources | - | - | - | - | 1 Source | 1 Source | 4 Sources |
14
  | Wikipedia | 310+ Languages | - | - | - | - | Included | Included | English Only |
15
  | FreeLaw | Included | - | - | - | - | - | - | Included |
16
  | DM Math | Included | - | - | - | - | - | - | Included |
 
19
  | HackerNews | Included | - | - | - | - | - | - | Included |
20
  | Ubuntu IRC | Included | - | - | - | - | - | - | Included |
21
  | EuroParl | Included | - | - | - | - | - | - | Included |
22
+ | StackExchange** | Included | - | - | - | - | - | - | Included |
23
  | Code | * | - | - | - | - | Included | Included | Included |
24
 
25
  * TxT360 does not include code. This decision was made due to the perceived low duplication code with other sources.
26
 
27
+ * StackExchange and PubMed Central datasets will be uploaded shortly. All other datasets are present and complete.
28
 
29
  Complete details on the dataset can be found in our blog post [here](https://huggingface.co/spaces/LLM360/TxT360).
30
 
 
51
  | DM Math | 22 GB | 5.23B | - |
52
  | USPTO | 45 GB | 4.95B | Q3 2024 |
53
  | PG-19 | 11 GB | 2.63B | - |
54
+ | HackerNews | 4.1 GB | 1.08B | Q4 2023 |
55
+ | Ubuntu IRC | 4.7 GB | 1.54B | Q3 2024 |
56
  | Europarl | 6.1 GB | 1.96B | - |
57
+ | StackExchange | 79 GB | 27.0B | Q4 2023 |
58
 
59
  The [TxT360](https://huggingface.co/spaces/LLM360/TxT360) blog post provides all the details behind how we approached and implemented the following features:
60
 
 
67
  ## Global Deduplication
68
  After the web and curated sources were filtered, all sources globally deduplicated to create TxT360. The tips and tricks behind the deduplication process are included.
69
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
70
  # Citation
71
 
72
  **BibTeX:**
 
74
  ```bibtex
75
  @misc{txt360data2024,
76
  title={TxT360: A Top-Quality LLM Pre-training Dataset Requires the Perfect Blend},
77
+ author={Liping Tang, Nikhil Ranjan, Omkar Pangarkar, Xuezhi Liang, Zhen Wang, Li An, Bhaskar Rao, Zhoujun Cheng, Suqi Sun, Cun Mu, Victor Miller, Yue Peng, Eric P. Xing, Zhengzhong Liu},
78
  year={2024}
79
  }
80
+ ```
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