Custom Transformer Training — Pre-Train on Your Domain Corpus

I will pre-train or domain-adapt a transformer model on your specialised text corpus — using masked language modelling (BERT-style) or causal language modelling (GPT-style) to adapt a general pre-trained model to your domain's vocabulary and language patterns before task-specific fine-tuning. Domain-adaptive pre-training on your corpus (continuing training of a general model on your domain text before task fine-tuning) consistently improves downstream task performance in highly specialised domains — legal, medical, financial, and scientific text each have vocabulary distributions and syntactic patterns sufficiently different from general web text that domain adaptation provides measurable gains.

The training covers corpus preprocessing and tokenisation, continued pre-training with masked or causal LM objective, perplexity evaluation on a domain held-out set, model checkpoint selection, and export for downstream fine-tuning.