johannhartmann commited on
Commit
abfb2dc
1 Parent(s): cf2c9df

Create README.md

Browse files
Files changed (1) hide show
  1. README.md +135 -0
README.md ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ language:
4
+ - en
5
+ - fr
6
+ pipeline_tag: text-generation
7
+ ---
8
+
9
+ ![image/png](https://huggingface.co/datasets/malteos/images/resolve/main/occiglot.medium.png)
10
+
11
+ # Occiglot-7B-FR-EN
12
+
13
+ > A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
14
+ >
15
+
16
+ **Occiglot-7B-FR-EN** is a generative language model with 7B parameters for French and English and trained by the [Occiglot Research Collective](https://occiglot.github.io/occiglot/).
17
+ It is based on [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) and trained on 113B tokens of additional multilingual and code data with a block size of 8,192 tokens per sample.
18
+ Note that the model is a general-purpose base model and was not instruction-fine-tuned nor optimized for chat or other applications. We make an instruction tuned variant available as [occiglot-7b-fr-en-instruct](https://huggingface.co/occiglot/occiglot-7b-fr-en-instruct)
19
+
20
+ This is the first release of an ongoing open research project for multilingual language models.
21
+ If you want to train a model for your own language or are working on evaluations, please contact us or join our [Discord server](https://discord.gg/wUpvYs4XvM). **We are open for collaborations!**
22
+
23
+
24
+ ### Model details
25
+
26
+ - **Continued-pretraining from:** [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
27
+ - **Model type:** Causal decoder-only transformer language model
28
+ - **Languages:** English, French, and code.
29
+ - **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
30
+ - **Compute resources:** [HessianAI's 42](https://hessian.ai/)
31
+ - **Contributors:** Manuel Brack, Patrick Schramowski, Pedro Ortiz, Malte Ostendorff, Fabio Barth, Georg Rehm, Kristian Kersting
32
+ - **Research labs:** [Occiglot](https://occiglot.github.io/occiglot/) with support from [SAINT](https://www.dfki.de/en/web/research/research-departments/foundations-of-systems-ai) and [SLT](https://www.dfki.de/en/web/research/research-departments/speech-and-language-technology)
33
+ - **Contact:** [Discord](https://discord.gg/wUpvYs4XvM)
34
+
35
+ ### How to use
36
+
37
+ You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we
38
+ set a seed for reproducibility:
39
+
40
+ ```python
41
+ >>> from transformers import pipeline, set_seed
42
+ >>> generator = pipeline('text-generation', model='occiglot/occiglot-7b-fr-en')
43
+ >>> set_seed(42)
44
+ >>> generator("Bonjour, Je suis un modèle linguistique,", max_length=40, num_return_sequences=1)
45
+ [{'generated_text': 'Bonjour, Je suis un modèle linguistique qui peut t'aider à traduire des textes entre le français et l'anglais. Si tu me donnes un texte en français'}]
46
+ ```
47
+
48
+ ## Dataset
49
+
50
+ The training data is the respective subset of the data used for [occiglot-7b-eu5](https://huggingface.co/occiglot/occiglot-7b-eu5), i.e. French plus English and Code.
51
+
52
+ The data distribution by language (estimated) is as follows:
53
+ - English: ~34%
54
+ - Code: ~13%
55
+ - French: ~52%
56
+
57
+ The training data was prepared using [lm-datasets](https://github.com/malteos/lm-datasets).
58
+ The exact data configuration is [here](https://huggingface.co/occiglot/occiglot-7b-eu5/blob/main/lm-datasets-config.yml).
59
+
60
+ ## Training settings
61
+
62
+ - Continual pre-training on 128 x A100-80GB on [HessianAI's 42](https://hessian.ai/).
63
+ - Framework: [Determined](https://www.determined.ai/)
64
+ - Precision: bf16
65
+ - Optimizer: AdamW (lr: 0.00001, warmup_steps: 420)
66
+ - Global batch size: 512 (with 8192 blocksize) split over 128 GPUs
67
+ - Cosine Annealing with Warmup
68
+
69
+
70
+ ## Tokenizer
71
+
72
+ Tokenizer is unchanged from [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
73
+
74
+ ## Evaluation
75
+
76
+ Preliminary evaluation results can be found below.
77
+ Please note that the non-English results are based on partially machine-translated datasets and English prompts ([Belebele](https://huggingface.co/datasets/facebook/belebele) and [Okapi framework](https://github.com/nlp-uoregon/Okapi)) and thus should be interpreted with caution, e.g., biased towards English model performance.
78
+ Currently, we are working on more suitable benchmarks for Spanish, French, German, and Italian.
79
+
80
+ <details>
81
+ <summary>Evaluation results</summary>
82
+
83
+ ### All 5 Languages
84
+
85
+ | | avg | arc_challenge | belebele | hellaswag | mmlu | truthfulqa |
86
+ |:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
87
+ | Occiglot-7b-eu5 | 0.516895 | 0.508109 | 0.675556 | 0.718963 | 0.402064 | 0.279782 |
88
+ | Occiglot-7b-eu5-instruct | 0.537799 | 0.53632 | 0.691111 | 0.731918 | 0.405198 | 0.32445 |
89
+ | Occiglot-7b-fr-en | 0.509209 | 0.496806 | 0.691333 | 0.667475 | 0.409129 | 0.281303 |
90
+ | Occiglot-7b-fr-en-instruct | 0.52884 | 0.515613 | 0.723333 | 0.67371 | 0.413024 | 0.318521 |
91
+ | Claire-mistral-7b-0.1 | 0.514226 | 0.502773 | 0.705111 | 0.666871 | 0.412128 | 0.284245 |
92
+ | Mistral-7b-v0.1 | 0.547111 | 0.528937 | 0.768444 | 0.682516 | 0.448253 | 0.307403 |
93
+ | Mistral-7b-instruct-v0.2 | 0.56713 | 0.547228 | 0.741111 | 0.69455 | 0.422501 | 0.430262 |
94
+
95
+
96
+ ### English
97
+
98
+ | | avg | arc_challenge | belebele | hellaswag | mmlu | truthfulqa |
99
+ |:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
100
+ | Occiglot-7b-eu5 | 0.59657 | 0.530717 | 0.726667 | 0.789882 | 0.531904 | 0.403678 |
101
+ | Occiglot-7b-eu5-instruct | 0.617905 | 0.558874 | 0.746667 | 0.799841 | 0.535109 | 0.449 |
102
+ | Occiglot-7b-fr-en | 0.621947 | 0.568259 | 0.771111 | 0.804919 | 0.570716 | 0.394726 |
103
+ | Occiglot-7b-fr-en-instruct | 0.646571 | 0.586177 | 0.794444 | 0.808305 | 0.569862 | 0.474064 |
104
+ | Claire-mistral-7b-0.1 | 0.651798 | 0.59727 | 0.817778 | 0.827126 | 0.600912 | 0.415906 |
105
+ | Mistral-7b-v0.1 | 0.668385 | 0.612628 | 0.844444 | 0.834097 | 0.624555 | 0.426201 |
106
+ | Mistral-7b-instruct-v0.2 | 0.713657 | 0.637372 | 0.824444 | 0.846345 | 0.59201 | 0.668116 |
107
+
108
+ ### French
109
+
110
+ | | avg | arc_challenge_fr | belebele_fr | hellaswag_fr | mmlu_fr | truthfulqa_fr |
111
+ |:---------------------------|---------:|-------------------:|--------------:|---------------:|----------:|----------------:|
112
+ | Occiglot-7b-eu5 | 0.525017 | 0.506416 | 0.675556 | 0.712358 | 0.495684 | 0.23507 |
113
+ | Occiglot-7b-eu5-instruct | 0.554216 | 0.541488 | 0.7 | 0.724245 | 0.499122 | 0.306226 |
114
+ | Occiglot-7b-fr-en | 0.542903 | 0.532934 | 0.706667 | 0.718891 | 0.51333 | 0.242694 |
115
+ | Occiglot-7b-fr-en-instruct | 0.567079 | 0.542344 | 0.752222 | 0.72553 | 0.52051 | 0.29479 |
116
+ | Claire-mistral-7b-0.1 | 0.515127 | 0.486741 | 0.694444 | 0.642964 | 0.479566 | 0.271919 |
117
+ | Mistral-7b-v0.1 | 0.558129 | 0.525235 | 0.776667 | 0.66481 | 0.543121 | 0.280813 |
118
+ | Mistral-7b-instruct-v0.2 | 0.575821 | 0.551754 | 0.758889 | 0.67916 | 0.506837 | 0.382465 |
119
+
120
+ </details>
121
+
122
+ ## Acknowledgements
123
+
124
+ The model training was supported by a compute grant at the [42 supercomputer](https://hessian.ai/) which is a central component in the development of [hessian AI](https://hessian.ai/), the [AI Innovation Lab](https://hessian.ai/infrastructure/ai-innovationlab/) (funded by the [Hessian Ministry of Higher Education, Research and the Art (HMWK)](https://wissenschaft.hessen.de) & the [Hessian Ministry of the Interior, for Security and Homeland Security (HMinD)](https://innen.hessen.de)) and the [AI Service Centers](https://hessian.ai/infrastructure/ai-service-centre/) (funded by the [German Federal Ministry for Economic Affairs and Climate Action (BMWK)](https://www.bmwk.de/Navigation/EN/Home/home.html)).
125
+ The curation of the training data is partially funded by the [German Federal Ministry for Economic Affairs and Climate Action (BMWK)](https://www.bmwk.de/Navigation/EN/Home/home.html)
126
+ through the project [OpenGPT-X](https://opengpt-x.de/en/) (project no. 68GX21007D).
127
+
128
+
129
+ ## License
130
+
131
+ [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
132
+
133
+ ## See also
134
+
135
+ - https://huggingface.co/collections/occiglot/occiglot-eu5-7b-v01-65dbed502a6348b052695e01