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@@ -77,7 +77,7 @@ r = pipe(
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  ### Training Data
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- The model has been on a proprietary dataset of ~1.35M examples consisting of
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  * High quality swedish instruct data
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  * Single turn
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  * Multi-turn
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  For training we used hugginface Accelerate and TRL.
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- #### Preprocessing [optional]
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  For efficiency, we packed all the examples into 8K context windows, reducing the number examples to ~12% of their original count.
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  #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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  [More Information Needed]
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  The model has been evaluated on [Scandeval](https://scandeval.com/swedish-nlg/) swedish subset.
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  ![metrics](assets/metrics.png)
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  ![mean-score](assets/mean_score.png)
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  ### Training Data
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+ The model has been trained on a proprietary dataset of ~1.35M examples consisting of
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  * High quality swedish instruct data
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  * Single turn
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  * Multi-turn
 
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  For training we used hugginface Accelerate and TRL.
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+ #### Preprocessing
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  For efficiency, we packed all the examples into 8K context windows, reducing the number examples to ~12% of their original count.
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  #### Training Hyperparameters
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+ - **Training regime:**
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  [More Information Needed]
 
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  The model has been evaluated on [Scandeval](https://scandeval.com/swedish-nlg/) swedish subset.
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+ The result of the individual metrics compared to other top scoring models
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  ![metrics](assets/metrics.png)
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+ The mean score of all metrics compared to other models in the Swedish NLG category.
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  ![mean-score](assets/mean_score.png)
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