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Model: occiglot/occiglot-7b-fr-en
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+- fr
+pipeline_tag: text-generation
+---
+
+![image/png](https://huggingface.co/datasets/malteos/images/resolve/main/occiglot.medium.png)
+
+# Occiglot-7B-FR-EN
+
+> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
+> 
+
+**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/).
+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.
+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)
+
+This is the first release of an ongoing open research project for multilingual language models. 
+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!**
+
+
+### Model details
+
+- **Continued-pretraining from:** [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+- **Model type:** Causal decoder-only transformer language model
+- **Languages:** English, French, and code.
+- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
+- **Compute resources:** [HessianAI's 42](https://hessian.ai/)
+- **Contributors:** Manuel Brack, Patrick Schramowski, Pedro Ortiz, Malte Ostendorff, Fabio Barth, Georg Rehm, Kristian Kersting
+- **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)
+- **Contact:** [Discord](https://discord.gg/wUpvYs4XvM)
+
+### How to use
+
+You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we
+set a seed for reproducibility:
+
+```python
+>>> from transformers import pipeline, set_seed
+>>> generator = pipeline('text-generation', model='occiglot/occiglot-7b-fr-en')
+>>> set_seed(42)
+>>> generator("Bonjour, Je suis un modèle linguistique,", max_length=40, num_return_sequences=1)
+[{'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'}]
+```
+
+## Dataset
+
+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.
+
+The data distribution by language (estimated) is as follows:
+- English: ~34%
+- Code: ~13%
+- French: ~52%
+
+The training data was prepared using [lm-datasets](https://github.com/malteos/lm-datasets). 
+The exact data configuration is [here](https://huggingface.co/occiglot/occiglot-7b-eu5/blob/main/lm-datasets-config.yml).
+
+## Training settings
+
+- Continual pre-training on 128 x A100-80GB on [HessianAI's 42](https://hessian.ai/). 
+- Framework: [Determined](https://www.determined.ai/)
+- Precision: bf16
+- Optimizer: AdamW (lr: 0.00001, warmup_steps: 420)
+- Global batch size: 512 (with 8192 blocksize) split over 128 GPUs
+- Cosine Annealing with Warmup
+
+
+## Tokenizer
+
+Tokenizer is unchanged from [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
+
+## Evaluation
+
+Preliminary evaluation results can be found below. 
+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.
+Currently, we are working on more suitable benchmarks for Spanish, French, German, and Italian.
+
+<details>
+<summary>Evaluation results</summary>
+
+### All 5 Languages
+
+|                            |      avg |   arc_challenge |   belebele |   hellaswag |     mmlu |   truthfulqa |
+|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
+| Occiglot-7b-eu5            | 0.516895 |        0.508109 |   0.675556 |    0.718963 | 0.402064 |     0.279782 |
+| Occiglot-7b-eu5-instruct   | 0.537799 |        0.53632  |   0.691111 |    0.731918 | 0.405198 |     0.32445  |
+| Occiglot-7b-fr-en          | 0.509209 |        0.496806 |   0.691333 |    0.667475 | 0.409129 |     0.281303 |
+| Occiglot-7b-fr-en-instruct | 0.52884  |        0.515613 |   0.723333 |    0.67371  | 0.413024 |     0.318521 |
+| Claire-mistral-7b-0.1      | 0.514226 |        0.502773 |   0.705111 |    0.666871 | 0.412128 |     0.284245 |
+| Mistral-7b-v0.1            | 0.547111 |        0.528937 |   0.768444 |    0.682516 | 0.448253 |     0.307403 |
+| Mistral-7b-instruct-v0.2   | 0.56713  |        0.547228 |   0.741111 |    0.69455  | 0.422501 |     0.430262 |
+
+
+### English
+
+|                            |      avg |   arc_challenge |   belebele |   hellaswag |     mmlu |   truthfulqa |
+|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
+| Occiglot-7b-eu5            | 0.59657  |        0.530717 |   0.726667 |    0.789882 | 0.531904 |     0.403678 |
+| Occiglot-7b-eu5-instruct   | 0.617905 |        0.558874 |   0.746667 |    0.799841 | 0.535109 |     0.449    |
+| Occiglot-7b-fr-en          | 0.621947 |        0.568259 |   0.771111 |    0.804919 | 0.570716 |     0.394726 |
+| Occiglot-7b-fr-en-instruct | 0.646571 |        0.586177 |   0.794444 |    0.808305 | 0.569862 |     0.474064 |
+| Claire-mistral-7b-0.1      | 0.651798 |        0.59727  |   0.817778 |    0.827126 | 0.600912 |     0.415906 |
+| Mistral-7b-v0.1            | 0.668385 |        0.612628 |   0.844444 |    0.834097 | 0.624555 |     0.426201 |
+| Mistral-7b-instruct-v0.2   | 0.713657 |        0.637372 |   0.824444 |    0.846345 | 0.59201  |     0.668116 |
+
+### French
+
+|                            |      avg |   arc_challenge_fr |   belebele_fr |   hellaswag_fr |   mmlu_fr |   truthfulqa_fr |
+|:---------------------------|---------:|-------------------:|--------------:|---------------:|----------:|----------------:|
+| Occiglot-7b-eu5            | 0.525017 |           0.506416 |      0.675556 |       0.712358 |  0.495684 |        0.23507  |
+| Occiglot-7b-eu5-instruct   | 0.554216 |           0.541488 |      0.7      |       0.724245 |  0.499122 |        0.306226 |
+| Occiglot-7b-fr-en          | 0.542903 |           0.532934 |      0.706667 |       0.718891 |  0.51333  |        0.242694 |
+| Occiglot-7b-fr-en-instruct | 0.567079 |           0.542344 |      0.752222 |       0.72553  |  0.52051  |        0.29479  |
+| Claire-mistral-7b-0.1      | 0.515127 |           0.486741 |      0.694444 |       0.642964 |  0.479566 |        0.271919 |
+| Mistral-7b-v0.1            | 0.558129 |           0.525235 |      0.776667 |       0.66481  |  0.543121 |        0.280813 |
+| Mistral-7b-instruct-v0.2   | 0.575821 |           0.551754 |      0.758889 |       0.67916  |  0.506837 |        0.382465 |
+
+</details>
+
+## Acknowledgements
+
+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)).
+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)
+through the project [OpenGPT-X](https://opengpt-x.de/en/) (project no. 68GX21007D).
+
+
+## License
+
+[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
+
+## See also
+
+- https://huggingface.co/collections/occiglot/occiglot-eu5-7b-v01-65dbed502a6348b052695e01

config.json

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+{
+  "_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
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+  "initializer_range": 0.02,
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+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
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+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.37.0.dev0"
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}