Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- en
+- it
+pipeline_tag: text-generation
+---
+
+![image/png](https://huggingface.co/datasets/malteos/images/resolve/main/occiglot.medium.png)
+
+# Occiglot-7B-IT-EN
+
+> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
+> 
+
+**Occiglot-7B-IT-EN** is a generative language model with 7B parameters for Italian 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-it-en-instruct](https://huggingface.co/occiglot/occiglot-7b-it-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, Italian, 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-it-en')
+>>> set_seed(42)
+>>> generator("Salve, sono una modella linguistica,", max_length=40, num_return_sequences=1)
+[{'generated_text': 'Salve, sono una modella linguistica che può aiutarvi a tradurre testi tra l'italiano e l'inglese. Se mi inviate un testo in italiano'}]
+```
+
+## 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. Italian plus English and Code.
+
+The data distribution by language (estimated) is as follows:
+- English: ~34%
+- Code: ~13%
+- Italian: ~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-it-en          | 0.513221 |        0.500564 |   0.694444 |    0.668099 | 0.413528 |     0.289469 |
+| Occiglot-7b-it-en-instruct | 0.53721  |        0.523128 |   0.726667 |    0.683414 | 0.414918 |     0.337927 |
+| Cerbero-7b                 | 0.532385 |        0.513714 |   0.743111 |    0.654061 | 0.427566 |     0.323475 |
+| 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-it-en          | 0.630127 |        0.580205 |   0.774444 |    0.804222 | 0.578977 |     0.412786 |
+| Occiglot-7b-it-en-instruct | 0.659383 |        0.609215 |   0.82     |    0.809301 | 0.578835 |     0.479562 |
+| Cerbero-7b                 | 0.66661  |        0.613481 |   0.827778 |    0.810396 | 0.600484 |     0.480911 |
+| 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 |
+
+### Italian
+
+|                            |      avg |   arc_challenge_it |   belebele_it |   hellaswag_it |   mmlu_it |   truthfulqa_it |
+|:---------------------------|---------:|-------------------:|--------------:|---------------:|----------:|----------------:|
+| Occiglot-7b-eu5            | 0.421382 |           0.501283 |      0.652222 |       0.700533 |         0 |        0.252874 |
+| Occiglot-7b-eu5-instruct   | 0.437214 |           0.516681 |      0.661111 |       0.71326  |         0 |        0.295019 |
+| Occiglot-7b-it-en          | 0.432667 |           0.536356 |      0.684444 |       0.694768 |         0 |        0.247765 |
+| Occiglot-7b-it-en-instruct | 0.456261 |           0.545766 |      0.717778 |       0.713804 |         0 |        0.303959 |
+| Cerbero-7b                 | 0.434939 |           0.522669 |      0.717778 |       0.631567 |         0 |        0.302682 |
+| Mistral-7b-v0.1            | 0.426264 |           0.502139 |      0.734444 |       0.630371 |         0 |        0.264368 |
+| Mistral-7b-instruct-v0.2   | 0.442383 |           0.519247 |      0.703333 |       0.6394   |         0 |        0.349936 |
+
+
+</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