Set can_return_loss=True globally, instead of via the data collator

sentence_transformers/data_collator.py

@@ -19,7 +19,7 @@ def __call__(self, features: List[Dict[str, Any]]) -> Dict[str, torch.Tensor]:
         columns = list(features[0].keys())
 
         # We should always be able to return a loss, label or not:
-        batch = {"return_loss": True}
+        batch = {}
 
         if "dataset_name" in columns:
             columns.remove("dataset_name")

sentence_transformers/trainer.py

@@ -197,7 +197,13 @@ def __init__(
             optimizers=optimizers,
             preprocess_logits_for_metrics=preprocess_logits_for_metrics,
         )
+        # Every Sentence Transformer model can always return a loss, so we set this to True
+        # to avoid having to specify it in the data collator or model's forward
+        self.can_return_loss = True
+
         self.model: SentenceTransformer
+        self.args: SentenceTransformerTrainingArguments
+        self.data_collator: SentenceTransformerDataCollator
         # Set the W&B project via environment variables if it's not already set
         if any([isinstance(callback, WandbCallback) for callback in self.callback_handler.callbacks]):
             os.environ.setdefault("WANDB_PROJECT", "sentence-transformers")