Document Understanding
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Document Understanding User Guide for Modern Experience
Last updated Feb 22, 2024

3. AI Center: Scheduled Auto-retraining Pipeline

When scheduling a Training or Full Pipeline in AI Center, there are a few aspects that need to be taken into consideration.

First, we strongly recommend you create an Evaluation dataset and that you only schedule Full pipelines. Full pipelines run Training and Evaluation together, and the Evaluation pipeline uses the Evaluation dataset to produce a score. This score will be critical for deciding whether the new version is better than the previous version, and it can be deployed for being consumed by Robots.

Second, for the Full Pipeline you need to specify two datasets: an Input Dataset and an Evaluation Dataset.

There is no change to the Evaluation dataset in the context of the Auto-Fine-tuning Loop feature. You still need to select a dataset as usual, containing the two folders: images and latest, and the two files: schema.json and split.csv.

However, the Input dataset is no longer a dataset, but you need to select the export folder in the AI Center dataset which is connected to the Data Labelling session. This way, the Training runs on the latest export from your Data Labelling session while the Evaluation runs on the same Evaluation dataset you specify.

Important: If you do not select the export folder, the auto-retraining does not work.

Third, you need to set the auto-retraining environment variable to True.

Finally, you need to select Recurring and set a day and time to leave enough time for the export from Document Manager to finish. For example, if the Document Manager export runs at 1 AM on Saturday, then the Pipeline might run at 2 or 3 AM on Saturday. If the export is not finished when the pipeline runs, it uses the previous export, and it might retrain on the same data it trained on the previous week.

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