This repository contains the project files for ML@B's ClimateHack 2023 contest submissions.
Specify the model name in config.model.name with the model name in build.py. We use a yaml file for each model, for easy access.
python main.py -n run_name -c config_filepath
Specify run_name to for wandb logging. Run without flags to use defaults. Run name and configs must be specified.
The model weights and a json copy of the config file used will be saved in ckpts/{run_name}/.
Local eval:
python main.py -n run_name -c config_filepath -t eval
(default behaviour is that main.py will train, not eval)
DOXA local eval:
python doxa_local.py ckpts/run_name
This automatically copies the model weights and config from the folder ckpts/{run_name}/ to the submissions folder, then runs the eval on the model. We recommend running this before submission to make sure everything works as intended!
bash submit.sh ckpts/run_name
Logs into DOXA and submits model.