goldfish-models commited on
Commit
3dab06b
1 Parent(s): 164d22f

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +60 -0
README.md ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ ---
3
+ license: apache-2.0
4
+ language:
5
+ - per
6
+ - fas
7
+ datasets:
8
+ - cis-lmu/Glot500
9
+ library_name: transformers
10
+ pipeline_tag: text-generation
11
+ tags:
12
+ - goldfish
13
+
14
+ ---
15
+
16
+ # fas_arab_100mb
17
+
18
+ Goldfish is a suite of monolingual language models trained for 350 languages.
19
+ This model is the <b>Persian</b> (Arabic script) model trained on 100MB of data, after accounting for an estimated byte premium of 1.59; content-matched text in Persian takes on average 1.59x 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: fas_arab is a [macrolanguage](https://iso639-3.sil.org/code_tables/639/data) code. Individual language codes pes_arab (Iranian Persian) and prs_arab (Dari) are 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: 124770816
38
+ * Maximum sequence length: 512 tokens
39
+ * Training text data (raw): 159.08MB
40
+ * Training text data (byte premium scaled): 100.005MB
41
+ * Training tokens: 24438272 (x10 epochs)
42
+ * Vocabulary size: 50000
43
+ * Compute cost: 1.2475910651904e+17 FLOPs or ~11.8 NVIDIA A6000 GPU hours
44
+
45
+ Training datasets (percentages prior to deduplication):
46
+ * 100.00000%: [Glot500](https://huggingface.co/datasets/cis-lmu/Glot500), including [CCNet](https://github.com/facebookresearch/cc_net), [TICO](https://tico-19.github.io/), [W2C](https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0022-6133-9), [WikiMatrix](https://github.com/facebookresearch/LASER/tree/main/tasks/WikiMatrix)
47
+
48
+
49
+ ## Citation
50
+
51
+ If you use this model, please cite:
52
+
53
+ ```
54
+ @article{chang-etal-2024-goldfish,
55
+ title={Goldfish: Monolingual Language Models for 350 Languages},
56
+ author={Chang, Tyler A. and Arnett, Catherine and Tu, Zhuowen and Bergen, Benjamin K.},
57
+ journal={Preprint},
58
+ year={2024},
59
+ }
60
+ ```