Phoenix - Your AI AssistantOpenAI GPT Fine-Tuning — Model Trained & Delivered on Your Data
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4 days
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What you get with this Offer
I will fine-tune a GPT-3.5 Turbo or GPT-4o mini model on your prepared dataset using the OpenAI fine-tuning API — managing the full training run from data upload and hyperparameter configuration through training job monitoring, evaluation against a validation set, and delivery of your fine-tuned model ID with inference code ready to drop into your application. Fine-tuning via the OpenAI API is one of the most accessible routes to a custom language model, but achieving a model that genuinely outperforms the base requires correct hyperparameter selection, sufficient training data, and rigorous evaluation — not just submitting a dataset and hoping for the best.
The service covers dataset upload and validation via the OpenAI API, training job configuration (epochs, learning rate multiplier, batch size), training loss monitoring, validation set evaluation with example-level output comparison against the base model, and a post-training report documenting model ID, training metrics, and performance observations. Inference code in Python is included so you can start using the model immediately.
This service excludes the OpenAI training cost, which is billed directly to your account. I manage the technical execution; you retain full ownership of the fine-tuned model.
The service covers dataset upload and validation via the OpenAI API, training job configuration (epochs, learning rate multiplier, batch size), training loss monitoring, validation set evaluation with example-level output comparison against the base model, and a post-training report documenting model ID, training metrics, and performance observations. Inference code in Python is included so you can start using the model immediately.
This service excludes the OpenAI training cost, which is billed directly to your account. I manage the technical execution; you retain full ownership of the fine-tuned model.
What the Freelancer needs to start the work
Please provide your prepared JSONL training dataset (minimum 50 examples, ideally 200+), your OpenAI API key with fine-tuning permissions, your target model (GPT-3.5 Turbo or GPT-4o mini), and a description of the evaluation criteria you'll use to judge whether the fine-tuned model meets your quality bar.
Please provide your prepared JSONL training dataset (minimum 50 examples, ideally 200+), your OpenAI API key with fine-tuning permissions, your target model (GPT-3.5 Turbo or GPT-4o mini), and a description of the evaluation criteria you'll use to judge whether the fine-tuned model meets your quality bar.