Transkribus Model Creation and Training Guide

This page will outline the process of creating and training a new model using the Transkribus Lite interface.

General Overview of the Procedure
The entire process of creating and training a new model is quite extensive. This flowchart given below broadly details the various steps involved in the whole workflow right from getting the required model training data to making the model available on your Wikisource. NOTE: ''Certain advanced processes like customizing shapes of polygons or editing baseline data are not mentioned in the flowchart for sake of simplicity. They will be detailed in their respective sections.''

Prerequisites
The following are the prerequisites to creating and training a new model


 * Have a functional account on Transkribus with enough credits to perform OCR operations
 * Keep at least 5,000 and 15,000 words (around 25-75 pages) of transcribed material in your desired language ready to be uploaded
 * If you are working with printed text and not handwritten text, a lower amount of training data will be needed (around 50 pages)
 * Please note that the number of pages of a particular type for which the model is being created is crucial to the performance of the model
 * When creating a model for a particular style of handwritten text, ensure that all the manuscripts available are of that particular style only
 * And a lot of patience, for this is going to take some time!

The Transkribus Work Area
Once you click on any of the documents under the Work Desk section on your Transkribus Lite interface, you will be redirected to a screen as shown below. This is where all the work related to your manuscript will take place. This interface includes the following options (numbered accordingly):


 * 1) Cursor tool for moving the manuscript around
 * 2) Pen tool to indicate baselines for your manuscript
 * 3) Region selector tool to define the various regions in your manuscript
 * 4) A tool to add tables to the manuscript regions
 * 5) A button to provide more information and keyboard shortcuts
 * 6) A layout editor that allows you to see your lines and regions in one place
 * 7) Zoom controllers
 * 8) Center your document with respect to the viewing area
 * 9) Fit the document to the viewing area
 * 10) Rotate your document
 * 11) Change the view to full screen
 * 12) Start transcription with an existing model
 * 13) Option to download the existing document
 * 14) A dropdown to change the status of the page to one of the following
 * 15) In Progress
 * 16) Ground Truth
 * 17) Done
 * 18) Final
 * 19) Save progress on your current document

Apart from these, there are also buttons to undo/redo changes, a virtual keyboard, and options to share your work.

Adding ground truth
Before training a model, you will need to prepare your training data, this means preparing enough images and their corresponding correct transcriptions to train the model. This process known as the addition of ground truth, ensures that the model can be trained on existing validated data.

While preparing your manuscripts as ground truth data, you can utilise any of the public models available on Transkribus to transcribe your text and make corrections. In case there are no models for your kind of text, you will have to transcribe manually. When you are done with the transcription, save each page as ground truth. This indicates that the pages can be used to train your model. Once the pages have been marked appropriately, you can begin the training process.

Training a base model
The process of training the model is further split into two: creating and training the baseline model and then creating the hand recognition model on top of it.

Baseline Model
The process of training the baseline model begins with a section as shown below.


 * Go to the Training section and choose a collection as prompted. Select the Baselines model option, as shown in Fig 2.
 * In the dialog box that appears, proceed to fill required details like model name (numbered 3 in the figure above) and description (numbered 4 in the figure above). The field named epochs (numbered 5 the figure above) determines how long the model will iterate over the provided dataset.
 * The next step involves selecting the training data containing the corrected baselines that were prepared in the previous step. Select all relevant documents or collections that you want the model to learn from. Similarly, select the dataset to be used for validation as well.
 * NOTE: Ideally, 90% of the entire data available should be used for training while 10% should be used for validation.
 * Trigger the model training process

The training process takes a few minutes to complete. You can check the progress of the training process in the Jobs tab. Once complete, this job readies the baseline model that can further be used to create the main model!