File size: 1,151 Bytes
96c2f0e
6f9a032
 
96c2f0e
 
6f9a032
 
 
96c2f0e
 
 
 
 
 
6f9a032
 
 
 
03bf2e0
 
6f9a032
 
03bf2e0
 
 
 
6f9a032
 
 
 
 
96c2f0e
35dca29
 
 
 
16dc7b2
35dca29
16dc7b2
35dca29
 
 
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
---
language_creators:
- found
language:
- en
license: odc-by
source_datasets:
- c4
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
dataset_info:
  features:
  - name: text
    dtype: string
  - name: score
    dtype: float64
  splits:
  - name: train
    num_bytes: 406518157.4620394
    num_examples: 302379
  download_size: 245358543
  dataset_size: 406518157.4620394
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
The estimated top 10% of highest n-token (mean 3,4,5) overlaps for each of the 
selected benchmark datasets (arc, truthful_qa, hellaswag, mmlu, humaneval) based 
on 1k samples, within the first 3M samples of C4. The top scoring sample 
datasets for each benchmark are then filtered again for top 30% scores and 
combined and exact-match de-duplicated. ~~Then the top 3% scores are removed
because they likely have exact large n-token matches by chance such as exact 
dates or times that aren't actually relevant to the data.~~ (todo)

This is meant to fascilitate a high-quality short continuation of pretraining 
for language models.