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@@ -86,10 +86,6 @@ The model was trained on a diverse set of Turkish & English language sources, en
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  The training data underwent standard NLP preprocessing steps, including tokenization, normalization, and possibly data augmentation to enhance the model's robustness.
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- #### Training Hyperparameters
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- - Learning Rate: 2e-5
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  ## Environmental Impact
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  The training of Cymist2-v0.1-SFT was conducted with a focus on minimizing carbon emissions. Detailed carbon emission statistics will be provided based on the Machine Learning Impact calculator, considering hardware type, usage hours, cloud provider, compute region, and total emissions.
 
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  The training data underwent standard NLP preprocessing steps, including tokenization, normalization, and possibly data augmentation to enhance the model's robustness.
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  ## Environmental Impact
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  The training of Cymist2-v0.1-SFT was conducted with a focus on minimizing carbon emissions. Detailed carbon emission statistics will be provided based on the Machine Learning Impact calculator, considering hardware type, usage hours, cloud provider, compute region, and total emissions.