Add missing doc strings in SFTrainer (#4003)

Co-authored-by: Quentin Gallouédec <[email protected]>
Co-authored-by: Quentin Gallouédec <[email protected]>

Author: pramodith

trl/trainer/sft_trainer.py

@@ -523,6 +523,16 @@ class SFTTrainer(Trainer):
             Processing class used to process the data. If `None`, the processing class is loaded from the model's name
             with [`~transformers.AutoProcessor.from_pretrained`]. A padding token, `tokenizer.pad_token`, must be set.
             If the processing class has not set a padding token, `tokenizer.eos_token` will be used as the default.
+        compute_loss_func (`Callable` or `None`, *optional*, defaults to `None`):
+            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, 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]` or `None`, *optional*, defaults to `None`):
+            The function that will be used to compute metrics at evaluation. Must take a
+            [`~transformers.EvalPrediction`] and return a dictionary string to metric values. When passing
+            [`SFTConfig`] with `batch_eval_metrics` set to `True`, your `compute_metrics` function must take a boolean
+            `compute_result` argument. This will be triggered after the last eval batch to signal that the function
+            needs to calculate and return the global summary statistics rather than accumulating the batch-level
+            statistics.
         callbacks (list of [`~transformers.TrainerCallback`], *optional*, defaults to `None`):
             List of callbacks to customize the training loop. Will add those to the list of default callbacks detailed
             in [here](https://huggingface.co/docs/transformers/main_classes/callback).