1st, thanks for the information you have provided and it was very helpful to understand the concept. Now I have few issues and many question.
Download the schema for the invoices using Data Manager as you said 1st and trained the ML model in pipeline and it was successful. When I ran the process using the trained model, I can see the confidence level has been increase to 99% from 75% for 3 certain fields. For the 4 field items, (product name which I have purchased) from the invoice even after I have trained the model using Data Manager it is not predicting the items purchased when I ran it through UiPath.
So using ML extractor trainer data I have extracted the data which have 3 folder:
- documents - have all the input invoices in pdf format
- metadata - have all the json files for the input files
- predictions - No data
I have compressed this and upload the folder in Data manager and it shows the items highlighted correctly. Now I have downloaded the file from Data manager and used this file (The input folder needs to contain these 4 things: 2 folders called images and latest, and 2 files called split.csv and schema.json.) to retrain the previously trained model.
So in Pipelines: created a new pipeline and choose the ML model, major version as 5 (Invoices India ML model) & minor version as 1 (Previously it was 0) and started the training for which I’m getting an error. I have attached the logs below.e12fd44a-3c19-4513-bffb-e3a9163cd8fd.txt (54.7 KB)
- How can I train my ML model again using the data from ML extractor trainer data?
- How to use evaluate and full pipeline run for this scenario to get the confidence level?
Kindly help me in solving these hurdles.