Update max_length explanation for VLM in online trainers (#4220)

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

Author: sergiopaniego

docs/source/grpo_trainer.md

@@ -563,8 +563,14 @@ accelerate launch \
 
 ### Configuration Tips
 
-> [!WARNING]
-> VLM training may fail if image tokens are truncated. We highly recommend disabling truncation by setting `max_prompt_length` to `None`.
+> [!TIP]
+> For VLMs, truncating may remove image tokens, leading to errors during training. To avoid this, set `max_prompt_length=None` in the [`GRPOConfig`]. This allows the model to process the full sequence length without truncating image tokens.
+>
+> ```python
+> GRPOConfig(max_prompt_length=None, ...)
+> ```
+>
+> Only use `max_prompt_length` when you've verified that truncation won't remove image tokens for the entire dataset.
 
 - Use LoRA on vision-language projection layers
 - Enable 4-bit quantization to reduce memory usage

docs/source/rloo_trainer.md

@@ -545,8 +545,14 @@ accelerate launch \
 
 ### Configuration Tips
 
-> [!WARNING]
-> VLM training may fail if image tokens are truncated. We highly recommend disabling truncation by setting `max_prompt_length` to `None`.
+> [!TIP]
+> For VLMs, truncating may remove image tokens, leading to errors during training. To avoid this, set `max_prompt_length=None` in the [`RLOOConfig`]. This allows the model to process the full sequence length without truncating image tokens.
+>
+> ```python
+> RLOOConfig(max_prompt_length=None, ...)
+> ```
+>
+> Only use `max_prompt_length` when you've verified that truncation won't remove image tokens for the entire dataset.
 
 - Use LoRA on vision-language projection layers
 - Enable 4-bit quantization to reduce memory usage