add docstring example for compute_loss_func (#35020)

src/transformers/trainer.py

@@ -360,8 +360,7 @@ class Trainer:
             inner layers, dropout probabilities etc).
         compute_loss_func (`Callable`, *optional*):
             A function that accepts the raw model outputs, labels, and the number of items in the entire accumulated
-            batch (batch_size * gradient_accumulation_steps) and returns the loss. For example, here is one using
-            the loss function from `transformers`
+            batch (batch_size * gradient_accumulation_steps) and returns the loss. For example, see the default [loss function](https://github.com/huggingface/transformers/blob/052e652d6d53c2b26ffde87e039b723949a53493/src/transformers/trainer.py#L3618) used by [`Trainer`].
         compute_metrics (`Callable[[EvalPrediction], Dict]`, *optional*):
             The function that will be used to compute metrics at evaluation. Must take a [`EvalPrediction`] and return
             a dictionary string to metric values. *Note* When passing TrainingArgs with `batch_eval_metrics` set to