Status or feedback when running TrainImagesClassifier

Context

Hello, I am trying to train a classifier using the TrainImagesClassifier to be able to classify trees in an orthophoto. But when I run the training algorithm I don’t get any feedback. It would be nice to know the number of learning cycles it has done and its current performance. With this information I would know that something is happening and I am not wasting a few days running a script that is stuck on something.

My question: Is there a way to get the feedback I need - current and goal classifier performance and learning cycle?
Maybe by running the algorithm using Python API, and not from the QGIS GUI?

Configuration setup

My system: Windows10
Version of the OTB: 9.1.0
I installed the OTB with: QGIS

Description of my issue

I am running the algorithm TrainImagesClassifier through QGIS GUI with these params:

{
    "io.il": [
        "D:/path/to/project/ai_orthophoto_tree_localization/cropped_orthophoto.tif"
    ],
    "io.vd": [
        "D:/path/to/project/ai_orthophoto_tree_localization/classification_training.shp"
    ],
    "io.valid": [
        "D:/path/to/project/ai_orthophoto_tree_localization/validation_shape.shp"
    ],
    "io.imstat": "D:\\path\\to\\project\\ai_orthophoto_tree_localization\\ai\\statistics.xml",
    "io.out": "D:/path/to/project/ai_orthophoto_tree_localization/ai/output/model.model",
    "io.confmatout": "D:/path/to/project/ai_orthophoto_tree_localization/ai/output/conf_mat.csv",
    "cleanup": True,
    "sample.mt": 1000,
    "sample.mv": 1000,
    "sample.bm": 1,
    "sample.vtr": 0.5,
    "sample.vfn": "id",
    "elev.dem": "",
    "elev.geoid": "",
    "elev.default": 0,
    "classifier": "libsvm",
    "classifier.libsvm.k": "linear",
    "classifier.libsvm.m": "csvc",
    "classifier.libsvm.c": 1,
    "classifier.libsvm.gamma": 1,
    "classifier.libsvm.coef0": 0,
    "classifier.libsvm.degree": 3,
    "classifier.libsvm.nu": 0.5,
    "classifier.libsvm.opt": False,
    "classifier.libsvm.prob": False,
    "rand": 0,
}

I have let the training run for two days without it finishing. The CPU usage was just 30%, and RAM around 350 MB the whole time - except for the beginning when I am guessing it was preparing the inputs.

I know the the TrainImagesClassifier is working when I gave it a black and white image, and made it classify white as 0, and black as 1 (I used the same params as shown above), it finished faster and it gave me the model.

Thank you for your time and help!