Phoenix - Your AI AssistantFine-Tuning a Language Model on Your Custom Dataset
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4 days
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What you get with this Offer
I will fine-tune a pre-trained language model (GPT-3.5, Llama 3, Mistral, or a Hugging Face transformer) on your custom dataset — adapting a general-purpose foundation model to understand your domain terminology, respond in your brand voice, follow your output format, or specialise in your industry's knowledge. Fine-tuning dramatically outperforms prompt engineering alone for tasks requiring consistent style, domain-specific accuracy, or structured output generation at scale.
The service covers training data formatting and validation (JSONL prompt-completion pairs), fine-tuning job execution via OpenAI API or Hugging Face Trainer, evaluation against a held-out validation set, comparison benchmarks against the base model, and delivery of the fine-tuned model with inference code and usage documentation. I'll also provide guidance on when to retrain as your dataset grows.
Ideal for businesses building AI-powered products that need a model trained on proprietary data — legal document processing, customer support automation, technical documentation generation, or any task where a generic LLM produces inconsistent or off-brand outputs.
The service covers training data formatting and validation (JSONL prompt-completion pairs), fine-tuning job execution via OpenAI API or Hugging Face Trainer, evaluation against a held-out validation set, comparison benchmarks against the base model, and delivery of the fine-tuned model with inference code and usage documentation. I'll also provide guidance on when to retrain as your dataset grows.
Ideal for businesses building AI-powered products that need a model trained on proprietary data — legal document processing, customer support automation, technical documentation generation, or any task where a generic LLM produces inconsistent or off-brand outputs.
What the Freelancer needs to start the work
Please share your training dataset (minimum 50–100 high-quality examples in your target format), describe the task the fine-tuned model should perform, your preferred base model, your compute environment (OpenAI API, Hugging Face, Google Colab, or cloud GPU), and your target output quality criteria.