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As we run multiple iterations of training for each binary classifier, we will want to compare the different runs while maintaining organization between them. I think we should associate each run with a group that shares a common DNN architecture, hyperparameters and training set using e.g. wandb.init(group="experiment_1", job_type="eval") (https://docs.wandb.ai/guides/track/advanced/grouping).
The text was updated successfully, but these errors were encountered:
As we run multiple iterations of training for each binary classifier, we will want to compare the different runs while maintaining organization between them. I think we should associate each run with a group that shares a common DNN architecture, hyperparameters and training set using e.g.
wandb.init(group="experiment_1", job_type="eval")
(https://docs.wandb.ai/guides/track/advanced/grouping).The text was updated successfully, but these errors were encountered: