diff --git a/burn-book/src/basic-workflow/training.md b/burn-book/src/basic-workflow/training.md index 6c78f339d..31f245ae4 100644 --- a/burn-book/src/basic-workflow/training.md +++ b/burn-book/src/basic-workflow/training.md @@ -135,7 +135,7 @@ pub fn train(artifact_dir: &str, config: TrainingConfig, dev It is a good practice to use the `Config` derive to create the experiment configuration. In the `train` function, the first thing we are doing is making sure the `artifact_dir` exists, using the standard rust library for file manipulation. All checkpoints, logging and metrics will be stored -under the this directory. We then initialize our dataloaders using our previously created batcher. +under this directory. We then initialize our dataloaders using our previously created batcher. Since no automatic differentiation is needed during the validation phase, the backend used for the corresponding batcher is `B::InnerBackend` (see [Backend](./backend.md)). The autodiff capabilities are available through a type system, making it nearly impossible to forget to deactivate gradient