Add pipeline tag, library name and link to paper
#2
by
nielsr
HF staff
- opened
README.md
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---
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license: apache-2.0
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language:
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- en
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- fi
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base_model:
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- LumiOpen/Poro-34B
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datasets:
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- sablo/oasst2_curated
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- LumiOpen/instruction-collection-fin
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---
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This is an SFT-tuned model of [Poro-34B](https://huggingface.co/LumiOpen/Poro-34B) with English and Finnish data. We trained this model as part of our experiments on the impact of multilingual instruction-tuning on Poro-34B. For a better chat experience, we recommend using [Poro-34B-chat](https://huggingface.co/LumiOpen/Poro-34B-chat) instead.
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## Datasets
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### SFT
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warmup_ratio: 0.1
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```
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## Evaluation
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We use [IFEval](https://huggingface.co/datasets/google/IFEval) to evaluate the performance of the model in English. For Finnish, we translated the IFEval prompts to [Finnish](https://huggingface.co/datasets/LumiOpen/ifeval_mt) with DeepL. We report the instruction-level strict accuracy:
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---
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base_model:
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- LumiOpen/Poro-34B
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datasets:
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- sablo/oasst2_curated
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- LumiOpen/instruction-collection-fin
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language:
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- en
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- fi
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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---
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This is an SFT-tuned model of [Poro-34B](https://huggingface.co/LumiOpen/Poro-34B) with English and Finnish data. We trained this model as part of our experiments on the impact of multilingual instruction-tuning on Poro-34B. For a better chat experience, we recommend using [Poro-34B-chat](https://huggingface.co/LumiOpen/Poro-34B-chat) instead.
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The model was presented in the paper [Poro 34B and the Blessing of Multilinguality](https://huggingface.co/papers/2404.01856).
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## Datasets
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### SFT
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warmup_ratio: 0.1
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```
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## Evaluation
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We use [IFEval](https://huggingface.co/datasets/google/IFEval) to evaluate the performance of the model in English. For Finnish, we translated the IFEval prompts to [Finnish](https://huggingface.co/datasets/LumiOpen/ifeval_mt) with DeepL. We report the instruction-level strict accuracy:
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