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Library/ NLP & Transformers/ Module 3 · Project 1: Banking Customer Query Classifier (fine-tuning BERT)/ 3.3 Prepare the data

subtopic

Splits, label IDs and tokenisation

10 min applied15 min research2 curated resources

Keep the official test set for the final score; split train into 90% train / 10% validation (stratified by intent). Create label2id / id2label maps. Tokenise all messages with the model's tokenizer (max_length 64 covers almost all messages) using dataset.map in batches.

Builds on: M03 · Build: Model-Ready Data & Baselines, 2.3 Tokenisation

Notes, key code, what to skip and 2 curated resources are inside the platform.Join the waitlist and we'll build you a roadmap that includes this topic only if your goal needs it.

Splits, label IDs and tokenisation · 1x1labs.ai