Logging metrics

The observability dashboard captures the most important plots and metadata you’d care about during training. However, when you need access to everything logged by the underlying framework, you can use our Weights & Biases integration.

First, you’ll need to create a Modal Secret with your API key:

modal secret create wandb-secret WANDB_API_KEY=<your-api-key>

Then, just pass it in your training recipe:

from modal_training_gym import Qwen3_5_4B, Qwen3_5_4B_Recipe, TrainConfig, WandbConfig

config = TrainConfig(
    model=Qwen3_5_4B(),
    dataset=my_dataset,
    recipe=Qwen3_5_4B_Recipe(
        # ...
        metrics=WandbConfig(
            project="my-rl-project",
            group="lr-sweep",  # optional: organize related runs
        ),
    ),
)

run = config.launch()

See the reference page for the full list of parameters.

When launching a hyperparameter sweep, the group parameter is especially useful to overlay multiple runs’ reward curves.

Trackio

Trackio is a lightweight, W&B-compatible tracker from Hugging Face. Training Gym installs it in the training image and routes the framework’s existing metric calls to it whenever a recipe uses TrackioConfig.

There are two ways to visualize your metrics if you are using Trackio: 1) deploy on Modal, and 2) deploy on a Hugging Face Space.

Deploy on Modal

You can host a Trackio server on Modal:

from modal_training_gym import TrackioConfig

metrics = TrackioConfig.deploy_to_modal(project="my-rl-project")

The first call creates a Modal app, a Volume for Trackio’s data, and a Secret holding a write token; later calls reuse them. Pass metrics to your recipe exactly like WandbConfig.

Reads to Trackio are open unless you’ve set a dashboard password with training-gym set-password:

training-gym set-password

Training containers keep logging either way, since they authenticate with the write token instead. The password is read at container startup, so rerun deploy_to_modal() after changing it.

Deploy on a Hugging Face Space

Point TrackioConfig at a Hugging Face Space with space_id="my-org/training-metrics", or at your own server with server_url plus a Modal Secret holding TRACKIO_WRITE_TOKEN. See the reference page for all parameters.