Rijgersberg
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README.md
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base_model: mistralai/Mistral-7B-v0.1
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tags:
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- generated_from_trainer
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model-index:
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- name: Mistral-7B-v0.1-chat-nl
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B-v0.1-chat-nl
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the
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It achieves the following results on the evaluation set:
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- Loss: 1.0263
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## Model description
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More
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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- Transformers 4.36.0.dev0
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- Pytorch 2.1.1+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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base_model: mistralai/Mistral-7B-v0.1
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tags:
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- generated_from_trainer
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- GEITje
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model-index:
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- name: Mistral-7B-v0.1-chat-nl
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results: []
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datasets:
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- Rijgersberg/no_robots_nl
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- Rijgersberg/ultrachat_10k_nl
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language:
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- nl
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pipeline_tag: conversational
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B-v0.1-chat-nl
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the Rijgersberg/no_robots_nl and Rijgersberg/ultrachat_10k_nl datasets.
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It achieves the following results on the evaluation set:
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- Loss: 1.0263
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## Model description
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In order to investigate the effect of pretraining [Rijgersberg/GEITje-7B](https://huggingface.co/Rijgersberg/GEITje-7B-chat) on the finetuning of [Rijgersberg/GEITje-7B-chat](https://huggingface.co/Rijgersberg/GEITje-7B-chat),
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I also subjected the base model Mistral 7B v0.1 to the exact same training.
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This model is called Mistral-7B-v0.1-chat-nl.
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## More info
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Read more about GEITje and GEITje-chat in the [📄 README](https://github.com/Rijgersberg/GEITje/blob/main/README-en.md) on GitHub.
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## Training procedure
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- Transformers 4.36.0.dev0
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- Pytorch 2.1.1+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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