You are given a text dataset and asked to build a model that predicts whether a piece of content is harmful (binary classification).
Task
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Propose an end-to-end approach to train and evaluate a classifier (you may assume you can fine-tune a pretrained Transformer).
What to cover
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Data understanding, labeling quality, and preprocessing
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Model choice and training procedure
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Evaluation metrics and thresholding
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Handling class imbalance and ambiguous labels
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Deployment considerations: latency, monitoring, safety/abuse, and model updates