Experiment tracking with Weights & Biases#
Weights & Biases for tracking experiments and visualizing results. Great for comparing different model fits during manual parameter and automatic architecture tuning (see example).
Setup Weights & Biases#
Create account at https://wandb.ai
Install the wandb python package and log in:
conda install wandb -c conda-forge
wandb login
See wandb docs for details.
Log your DAS runs:#
CLI:
das train OTHER_CLI_ARGS --wandb-token MY_SUPER_SECRET_TOKEN --wandb-entity django_reinhardt --wandb-project test_run
Python:
das.train.train(..., wandb-token="MY_SUPER_SECRET_TOKEN", wandb-entity="django_reinhardt", wandb_project="test_run")
Args:
wandb_api_token
: API token from wandb. See the wandb docs on how to generate the token.wandb_project
: Project to log to - useful for grouping runs.wandb_entity
: User or team name to log to.