I have created a workflow which uses train extractor ml Activity and Out of the box invoice model. I am trying to retrain the model using the data generated by the validation station in Action Center for more accuracy.
I have not used any data manager feature since I don’t want to customize anything.
The Invoice Trainer activity is automatically uploading it from Studio to a DataSet.(inside of a fine-tune folder)
But I am not able to train ml model using that fine-tune folder dataset as it doesn’t contain split.csv all those files. Can anyone help what I am doing wrong.
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Hence, we may not be able to avoid the Data Labelling for Auto Retraining the ML Model.
Perhaps, you could try importing some documents (15-20) into the Data Manager, Use Pre-Labelling option by providing the necessary endpoints and API (No need for correction as you do not want to customize) and then Perform the Export /Schedule the Export.
For Combining the datasets into the Export Folder, it seems Data Manager’s Export feature is required for now. Maybe in later releases they may introduce it separately or Perhaps because the Model needs a minimum number of Trained documents they keep the functionality this way.
Let us know if you were able to figure out a solution or provide us with some feedback if you were able to try the above approaches.