> ## Documentation Index
> Fetch the complete documentation index at: https://wb-21fd5541-docs-sandboxes-integrations-placement.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

> Fine-tune Cohere models with W&B experiment tracking to log training metrics and monitor model performance.

# Cohere fine-tuning

With W\&B you can log your Cohere model's fine-tuning metrics and configuration to analyze and understand the performance of your models and share the results with your colleagues.

This [guide from Cohere](https://docs.cohere.com/page/convfinqa-finetuning-wandb) has a full example of how to kick off a fine-tuning run and you can find the [Cohere API docs here](https://docs.cohere.com/reference/createfinetunedmodel#request.body.settings.wandb)

## Log your Cohere fine-tuning results

To add Cohere fine-tuning logging to your W\&B workspace:

1. Create a `WandbConfig` with your W\&B API key, W\&B `entity` and `project` name. Create an API key at [https://wandb.ai/settings](https://wandb.ai/settings)

2. Pass this config to the `FinetunedModel` object along with your model name, dataset and hyperparameters to kick off your fine-tuning run.

   ```python theme={null}
   from cohere.finetuning import WandbConfig, FinetunedModel

   # create a config with your W&B details
   wandb_ft_config = WandbConfig(
       api_key="<wandb_api_key>",
       entity="my-entity", # must be a valid enitity associated with the provided API key
       project="cohere-ft",
   )

   ...  # set up your datasets and hyperparameters

   # start a fine-tuning run on cohere
   cmd_r_finetune = co.finetuning.create_finetuned_model(
     request=FinetunedModel(
       name="command-r-ft",
       settings=Settings(
         base_model=...
         dataset_id=...
         hyperparameters=...
         wandb=wandb_ft_config  # pass your W&B config here
       ),
     ),
   )
   ```

3. View your model's fine-tuning training and validation metrics and hyperparameters in the W\&B project that you created.

   <Frame>
     <img src="https://mintcdn.com/wb-21fd5541-docs-sandboxes-integrations-placement/F9fRIboixVPY5pzA/images/integrations/cohere_ft.png?fit=max&auto=format&n=F9fRIboixVPY5pzA&q=85&s=54d4a65d19bfde1131c9426735ce939b" alt="Cohere fine-tuning dashboard" width="2180" height="586" data-path="images/integrations/cohere_ft.png" />
   </Frame>

## Organize runs

Your W\&B runs are automatically organized and can be filtered/sorted based on any configuration parameter such as job type, base model, learning rate and any other hyper-parameter.

In addition, you can rename your runs, add notes or create tags to group them.

## Resources

* [Cohere Fine-tuning Example](https://github.com/cohere-ai/notebooks/blob/kkt_ft_cookbooks/notebooks/finetuning/convfinqa_finetuning_wandb.ipynb)