NLP Text Classification Model

I’m working on an Artificial Intelligence project focused on Natural Language Processing and need an expert who can build a reliable text-classification pipeline from scratch to production-ready code.

Here’s what I need from you:
• Analyse the problem statement I provide and suggest the most suitable model architecture (traditional ML or a transformer-based approach if warranted).
• Prepare and clean the text data, engineer any helpful features, and handle class imbalance where necessary.
• Train, validate, and fine-tune the classifier, then document the metrics so I can clearly see accuracy, precision, recall, and F1 on a held-out test set.
• Package the final model with inference code (Python preferred; PyTorch, TensorFlow, scikit-learn or similar are all acceptable) plus a short README so I can reproduce the results on my machine.

Acceptance criteria
1. Reproducible training script that runs end-to-end with one command.
2. Minimum F1 score target agreed at project start.
3. Clean, well-commented code pushed to a private Git repo and handed over on completion.

If this scope aligns with your skills in NLP and text classification, let’s discuss the dataset, timeline, and performance goals so we can get started right away.