SUPERVISED FINE-TUNING

Tailor Existing Models with Supervised
Fine-Tuning

Turn your proprietary data into powerful models with Sama’s supervised fine-tuning solutions that combine the efficiency of automation with human-in-the-loop accuracy.

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40% of FAANG companies trust Sama to deliver industry-leading data that powers AI

SOLUTIONS

Supervised Fine-Tuning Solutions

Our dedicated Gen AI team will help you fine tune an existing LLM or generative model based on your unique objectives.

Domain Specificity

Fine-tuning a model for a specific domain (retail, finance, HR, etc.) requires a targeted approach. We help curate a high-quality dataset tailored to your domain, encompassing various aspects like tone, format and justifications. Our team can also evaluate and rewrite model responses for context and domain specificity to fine-tune your model to its environment.

Retrieval-Augmented Generation (RAG)

Our team will enhance RAG by fine-tuning question-answer pairs, pulling from proprietary documentation and other knowledge retrieval systems. We’ll also evaluate model outputs and rewrite any incorrect responses to create additional training data to better fine-tune your model.

Task Optimization

We can fine-tune models for specific tasks such as summarization or sentiment analysis. Our team starts by crafting clear and concise prompts along with corresponding answers. We’ll also evaluate and rewrite model responses based on your goals to help fine-tune an existing model to your exact needs.

Multimodal

Sama’s team of experts can fine-tune models across multiple types of data, from text to images, video and more. We can create tailored data sets, paired with expert-written captions describing the content, to fine-tune the model to generate accurate, relevant responses for new visual inputs.

Model Evaluation

Our team uses a systematic approach to assess the performance and effectiveness of your Gen AI models. In addition to improving your model’s performance, we can help you understand model metrics and improve user experience, both during the fine-tuning process and evaluation.

Prompt Engineering

For prompt-based models, our team can create new prompts to help boost model performance, train on specific tasks, incorporate domain-specific language, improve on tone, handle multimodal tasks, and more.

APPROACH

Our Proprietary Approach to Supervised Fine-Tuning

Sama’s supervised fine-tuning projects start with tailored consultations to understand requirements for model behavior. This collaborative effort involves identifying key characteristics like tone, terminology, writing styles, relevant factual knowledge and more. We’ll align on how you want your model to behave and set targets across a variety of dimensions.

Our AI specialists leverage their expertise to write high quality prompts along with corresponding answers across varying formats and dimensions. We’ll curate a highly specialized set of data to help streamline the generative model or LLM development process.

After an initial set of data has been created we’ll work with your team to review the prompts and responses created to ensure the data aligns with the intended purpose of the generative model or LLM. If needed, our teams will collaborate closely to recalibrate.

As errors in model outputs are identified, our team will begin creating an additional training data set that can be used to fine-tune model performance based on your objective: domain specificity, task optimization, etc. This new data consists of rewritten prompts and corresponding responses that address the specific mistakes made by the model.

When the project is complete, we follow a structured delivery process to ensure smooth integration with your LLM or generative model training pipeline. We offer flexible and customizable delivery formats, APIs, and the option for custom API integrations to support rapid development of models.

OTHER SOLUTIONS

Generative AI and LLM Capabilities

With over 15 years of industry experience, Sama’s data annotation and validation solutions help you build more accurate GenAI models and LLMs—faster.

Model Validation & Fact Checking

Our data experts will review your model’s responses for accuracy, identify and highlight any errors, and rewrite responses to improve model performance, combining workflow automation with our human-in-the-loop approach to ensure speed and quality.

Instruction Following

Our team can assess how well your Gen AI model understands, interprets, and executes instructions. We’ll help you identify where your model doesn’t comply, including why a response was selected. Any issues are highlighted and flagged, making it easier and more efficient to fine-tune.

laptop with text prompts

Preference Ranking

Sama’s highly trained team of experts can help you improve the quality and alignment of model outputs through feedback loops, RLHF, and more. With domain expertise across multiple industries and functions, we can analyze and rank model responses, indicate the rationale behind each choice, and highlight any issues within the outputs.

Image & Video Captioning

Sama can help you scale captioning for a variety of modalities. Our team of experts will describe the content of visual inputs, verify if the captions match, and rewrite captions as needed to retrain the model to reduce errors and hallucinations. Sama’s proprietary platform makes sampling easy and our collaborative workflows help reduce subjectivity and ambiguity from project kickoff.

text document open on a laptop

Creative Writing

With domain expertise across a variety of industries and functions, Sama’s dedicated team can create new prompts and responses based on your model goals. We can also rewrite responses, tailored to model capabilities and limitations, to augment existing training data. Our team can also employ chain of thought to provide clear rationale for chosen outputs.

text document open on a laptop

Synthetic Data Creation

When real training data is too difficult or not cost effective to obtain, our team can create synthetic data sets to help train your model, using a human-in-the-loop approach to ensure the highest level of quality. Our team will define objectives for your data, including a specific domain or other required parameters, and test outputs for quality and accuracy by comparing them against outputs from authentic data. 

text document open on a laptop
PLATFORM

What Our Platform Offers

Multimodal Support

Our team is trained to provide comprehensive support across various modalities including text, image, and voice search applications. We help improve model accuracy and performance through a variety of solutions. 

Proactive Quality at-Scale

Our proactive approach minimizes delays while maintaining quality to help teams and models hit their milestones. All of our solutions are backed by SamaAssure™, the industry’s highest quality guarantee for Generative AI. 

Proactive Insights

SamaIQ™ combines the expertise of the industry’s best specialists with deep industry knowledge and proprietary algorithms to deliver faster insights and reduce the likelihood of unwanted biases and other privacy or compliance vulnerabilities.

Collaborative Project Space

SamaHub™, our collaborative project space, is designed for enhanced communication. GenAI and LLM clients have access to collaboration workflows, self-service sampling and complete reporting to track their project’s progress.

Easy Integrations

We offer a variety of integration options, including APIs, CLIs, and webhooks that allow you to seamlessly connect our platform to your existing workflows. The Sama API is a powerful tool that allows you to programmatically query the status of projects, post new tasks to be done, receive results automatically, and more.

99%

First batch client acceptance rate across 10B points per month

3X

Get models to market 3x faster by eliminating delays, missed deadlines and excessive rework

65K+

Lives impacted to date thanks to our purpose-driven business model

92%

2024 Customer Satisfaction (CSAT) score and an NPS of 64

RESOURCES

Popular Resources

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Frequently Asked Questions

What is supervised fine-tuning?

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Why is high-quality training data important for supervised fine tuning?

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What is prompt engineering for supervised fine tuning?

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Why is contextual optimization important for supervised fine tuning?

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