GH-440 add new evaluation metrics

add mean squared error as default for regression

flair/trainers/trainer_regression.py

@@ -15,6 +15,46 @@
 
 class RegressorTrainer(flair.trainers.ModelTrainer):
 
+    def train(self,
+              base_path: Union[Path, str],
+              evaluation_metric: EvaluationMetric = EvaluationMetric.MEAN_SQUARED_ERROR,
+              learning_rate: float = 0.1,
+              mini_batch_size: int = 32,
+              eval_mini_batch_size: int = None,
+              max_epochs: int = 100,
+              anneal_factor: float = 0.5,
+              patience: int = 3,
+              anneal_against_train_loss: bool = True,
+              train_with_dev: bool = False,
+              monitor_train: bool = False,
+              embeddings_in_memory: bool = True,
+              checkpoint: bool = False,
+              save_final_model: bool = True,
+              anneal_with_restarts: bool = False,
+              test_mode: bool = False,
+              param_selection_mode: bool = False,
+              **kwargs
+              ) -> dict:
+
+        return super(RegressorTrainer, self).train(
+              base_path=base_path, 
+              evaluation_metric=evaluation_metric, 
+              learning_rate=learning_rate,
+              mini_batch_size=mini_batch_size,
+              eval_mini_batch_size=eval_mini_batch_size,
+              max_epochs=max_epochs,
+              anneal_factor=anneal_factor,
+              patience=patience,
+              anneal_against_train_loss=anneal_against_train_loss,
+              train_with_dev=train_with_dev,
+              monitor_train=monitor_train,
+              embeddings_in_memory=embeddings_in_memory,
+              checkpoint=checkpoint,
+              save_final_model=save_final_model,
+              anneal_with_restarts=anneal_with_restarts,
+              test_mode=test_mode,
+              param_selection_mode=param_selection_mode)
+
     @staticmethod
     def _evaluate_text_regressor(model: flair.nn.Model,
                                   sentences: List[Sentence],

flair/training_utils.py

@@ -140,6 +140,7 @@ class EvaluationMetric(Enum):
     MICRO_F1_SCORE = 'micro-average f1-score'
     MACRO_ACCURACY = 'macro-average accuracy'
     MACRO_F1_SCORE = 'macro-average f1-score'
+    MEAN_SQUARED_ERROR = 'mean squared error'
 
 
 class WeightExtractor(object):