added a Legend of the definitions showed in the logger (#395)

* added a Legend of the definitions showed in the logger

docs/src/architectures/soap-bpnn.rst

@@ -9,7 +9,7 @@ SOAP-BPNN
 
 This is a Behler-Parrinello neural network :footcite:p:`behler_generalized_2007` with
 using features based on the Smooth overlab of atomic positions (SOAP)
-:footcite:p:`bartok_representing_2013`. The SOAP features are calculated wit `rascaline
+:footcite:p:`bartok_representing_2013`. The SOAP features are calculated with `rascaline
 <https://luthaf.fr/rascaline/latest/index.html>`_.
 
 Installation

src/metatrain/experimental/pet/trainer.py

@@ -117,7 +117,7 @@ def train(
             checkpoint_path = None
 
         ########################################
-        # STARTNG THE PURE PET TRAINING SCRIPT #
+        # STARTING THE PURE PET TRAINING SCRIPT #
         ########################################
 
         logging.info("Initializing PET training...")
@@ -165,6 +165,20 @@ def train(
             f"CUDA is deterministic: {FITTING_SCHEME.CUDA_DETERMINISTIC}"
         )
 
+        st = """
+Legend: LR          -> Learning Rate
+        MAE         -> Mean Square Error
+        RMSE        -> Root Mean Square Error
+        V-E-MAE/at  -> MAE of the Energy per atom on the Validation set
+        V-E-RMSE/at -> RMSE of the Energy per atom on the Validation set
+        V-F-MAE     -> MAE of the Forces on the Validation set
+        V-F-RMSE    -> RMSE of the Forces on the Validation set
+        T-E-MAE/at  -> MAE of the Energy per atom on the Training set
+        T-E-RMSE/at -> RMSE of the Energy per atom on the Training set
+        T-F-MAE     -> MAE of the Forces on the Training set
+        T-F-RMSE    -> RMSE of the Forces on the Training set
+Units of the Energy and Forces are the same units given in input"""
+        training_configuration_log += st
         logging.info(training_configuration_log)
 
         set_reproducibility(