feat: removing hard limits on learning rate

unsloth/models/rl.py

@@ -1076,10 +1076,17 @@ def _patch_trl_rl_trainers(trainer_file = "grpo_trainer"):
     # Warn on too large or too small learning rate
     if "learning_rate" in call_args:
         learning_rate_check = (
-            "if learning_rate < 1e-7: print(f'Unsloth: Your learning rate of `{learning_rate}` is too small and less than 1e-7! "
-            "Consider increasing it, otherwise gradient updates will be close to 0!')\n"
-            "if learning_rate > 1: print(f'Unsloth: Your learning rate of `{learning_rate}` is way too larger > 1! "
-            "Consider decreasing it to 1e-1, otherwise gradient updates will explode!')\n"
+            "use_strict_mode = os.environ.get('UNSLOTH_USE_STRICT_MODE', '1') == '1'\n"
+            "lower_limit_msg = f'Unsloth: Your learning rate of `{learning_rate}` is too small and less than 1e-7! "
+            "Consider increasing it, otherwise gradient updates will be close to 0!'\n"
+            "upper_limit_msg = f'Unsloth: Your learning rate of `{learning_rate}` is way too and more than 1! "
+            "Consider decreasing it to 1e-1, otherwise gradient updates will explode!'\n"
+            "if learning_rate < 1e-7:\n"
+            "    if use_strict_mode: raise FloatingPointError(lower_limit_msg)\n"
+            "    else: print(lower_limit_msg)\n"
+            "if learning_rate > 1:\n"
+            "    if use_strict_mode: raise OverflowError(upper_limit_msg)\n"
+            "    else: print(upper_limit_msg)\n"
         )
         extra_args += learning_rate_check