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Solved Projects; Customer Reviews; Experts New; class_names = datasets_images['train_data'].classes (ride-hailing) i.e. Multi-class and multi-label time series classification notebook: you can also check our new tutorial notebook: Self-supervised learning: Learn how to leverage your unlabeled datasets New visualization: Weve also added a new PredictionDynamics callback that will display the predictions during training. Weight for class 0: 0.50 Weight for class 1: 289.44 Train a model with class weights. We already have training and test datasets. This is example walks through using a Triton Server and Python client using MONAI on the MedNIST classification problem. Hence, we have a multi-class, classification problem.. Train/validation/test split. The classifier makes the assumption that each new complaint is assigned to one and only one category. This post is an outcome of my effort to solve a Multi-label Text classification problem using Transformers, hope it helps a few readers! 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