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@@ -93,7 +93,7 @@ After cleaning the dataset and normalizing the `ñ` character to `ny`, we have u
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  ### Training procedure
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  This model was trained starting from a pre-trained Spanish [stt-es-citrinet-512](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_es_citrinet_512) model. The initial learning rate was set to 0.005 and the minimum lr for weight decay was set to 1e-7.
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- The model was trained for 90 steps and then continued training for another 90 steps starting from a learning rate of 0.0001.
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  ## Evaluation
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  After evaluation on the test split of Common Voice 11.0 we have obtained a WER of 6.684.
 
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  ### Training procedure
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  This model was trained starting from a pre-trained Spanish [stt-es-citrinet-512](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_es_citrinet_512) model. The initial learning rate was set to 0.005 and the minimum lr for weight decay was set to 1e-7.
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+ The model was trained for 90 steps and then continued training for another 90 steps starting from a learning rate of 1e-4.
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  ## Evaluation
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  After evaluation on the test split of Common Voice 11.0 we have obtained a WER of 6.684.