Merge pull request #1 from evalstate/feature/trl-fixes

trl/references/training_methods.md

@@ -24,11 +24,14 @@ trainer = SFTTrainer(
         output_dir="my-model",
         push_to_hub=True,
         hub_model_id="username/my-model",
+        eval_strategy="no",  # Disable eval for simple example
     )
 )
 trainer.train()
 ```
 
+**Note:** For production training with evaluation monitoring, see `scripts/train_sft_example.py`
+
 **Documentation:** `hf_doc_fetch("https://huggingface.co/docs/trl/sft_trainer")`
 
 ## Direct Preference Optimization (DPO)
@@ -52,11 +55,14 @@ trainer = DPOTrainer(
     args=DPOConfig(
         output_dir="dpo-model",
         beta=0.1,  # KL penalty coefficient
+        eval_strategy="no",  # Disable eval for simple example
     )
 )
 trainer.train()
 ```
 
+**Note:** For production training with evaluation monitoring, see `scripts/train_dpo_example.py`
+
 **Documentation:** `hf_doc_fetch("https://huggingface.co/docs/trl/dpo_trainer")`
 
 ## Group Relative Policy Optimization (GRPO)