goldfish-models commited on
Commit
007a154
1 Parent(s): 285b1cc

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +63 -0
README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ ---
3
+ license: apache-2.0
4
+ language:
5
+ - din
6
+ datasets:
7
+ - allenai/nllb
8
+ - allenai/MADLAD-400
9
+ library_name: transformers
10
+ pipeline_tag: text-generation
11
+ tags:
12
+ - goldfish
13
+
14
+ ---
15
+
16
+ # din_latn_10mb
17
+
18
+ Goldfish is a suite of monolingual language models trained for 350 languages.
19
+ This model is the <b>Dinka</b> (Latin script) model trained on 10MB of data, after accounting for an estimated byte premium of 1.24; content-matched text in Dinka takes on average 1.24x as many UTF-8 bytes to encode as English.
20
+ The Goldfish models are trained primarily for comparability across languages and for low-resource languages; Goldfish performance for high-resource languages is not designed to be comparable with modern large language models (LLMs).
21
+
22
+ Note: din_latn is a [macrolanguage](https://iso639-3.sil.org/code_tables/639/data) code. Individual language code dik_latn (Southwestern Dinka) is included in Goldfish, although with less data.
23
+
24
+ All training and hyperparameter details are in our paper, [Goldfish: Monolingual Language Models for 350 Languages (Chang et al., 2024)](https://github.com/tylerachang/goldfish/blob/main/goldfish_paper_20240815.pdf).
25
+
26
+ Training code and sample usage: https://github.com/tylerachang/goldfish
27
+
28
+ Sample usage also in this Google Colab: [link](https://colab.research.google.com/drive/1rHFpnQsyXJ32ONwCosWZ7frjOYjbGCXG?usp=sharing)
29
+
30
+ ## Model details:
31
+
32
+ To access all Goldfish model details programmatically, see https://github.com/tylerachang/goldfish/model_details.json.
33
+ All models are trained with a [CLS] (same as [BOS]) token prepended, and a [SEP] (same as [EOS]) token separating sequences.
34
+ Details for this model specifically:
35
+
36
+ * Architecture: gpt2
37
+ * Parameters: 39087104
38
+ * Maximum sequence length: 512 tokens
39
+ * Training text data (raw): 12.42MB
40
+ * Training text data (byte premium scaled): 10.005MB
41
+ * Training tokens: 3547136 (x10 epochs)
42
+ * Vocabulary size: 50000
43
+ * Compute cost: 2683882281369600.0 FLOPs or ~0.3 NVIDIA A6000 GPU hours
44
+
45
+ Training datasets (percentages prior to deduplication):
46
+ * 73.62398%: [NLLB (CommonCrawl and ParaCrawl)](https://huggingface.co/datasets/allenai/nllb)
47
+ * 17.66747%: [MADLAD-400 (CommonCrawl)](https://huggingface.co/datasets/allenai/MADLAD-400)
48
+ * 6.00269%: [eBible](https://ebible.org/find/)
49
+ * 2.70586%: [Wikipedia 2023/08](https://dumps.wikimedia.org/)
50
+
51
+
52
+ ## Citation
53
+
54
+ If you use this model, please cite:
55
+
56
+ ```
57
+ @article{chang-etal-2024-goldfish,
58
+ title={Goldfish: Monolingual Language Models for 350 Languages},
59
+ author={Chang, Tyler A. and Arnett, Catherine and Tu, Zhuowen and Bergen, Benjamin K.},
60
+ journal={Preprint},
61
+ year={2024},
62
+ }
63
+ ```