Fine-Tuning

Fine-tuning with Web-UI

Customers can kick off fine-tuning jobs by completing the data preparation and validation steps through the Cohere dashboard. This is useful for customers who don’t need or don’t want to create a fine-tuning job programmatically via the Fine-tuning API or via the Cohere Python SDK, instead preferring the ease and simplicity of a web interface.

Datasets

Before a fine-tuning job can be started, users must upload a dataset with training and (optionally) evaluation data. The contents and structure of the dataset will vary depending on the type of fine-tuning. Read more about preparing the training data for Chat, Classify, and Rerank fine-tuning.

Your Datasets can be managed in the Datasets dashboard.

Starting a Fine-tuning job

After uploading the dataset and going through the validation and review data phases in the UI, the fine-tuning job can begin. Read more about starting the fine-tuning jobs for Chat, Classify, and Rerank.

Fine-tuning results

You will receive an email notification when the fine-tuned model is ready. You can explore the evaluation metrics using the Dashboard and try out your model using one of our APIs on the interactive Playground.

Fine-tuning job statuses

As your fine-tuning job progresses, it will progress through various stages. The following table describes the meaning of the various status messages you might encounter:

StatusMeaning
QueuedThe fine-tuning job is queued and will start training soon.
TrainingThe fine-tuning job is currently training.
DeployingThe fine-tuning job has finished training and is deploying the model endpoint.
ReadyThe fine-tuning job has finished and is ready to be called.
FailedThe fine-tuning job has failed. Please contact customer support if you need more help in understanding why the job has failed.