fix: duplicate optim setting
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@@ -492,10 +492,10 @@ class TrainerBuilderBase(abc.ABC):
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optim_args = self.cfg.optim_args
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training_args_kwargs["optim_args"] = optim_args
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if self.cfg.optimizer == "adamw_anyprecision":
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if Path(self.cfg.torchdistx_path).exists():
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sys.path.append(self.cfg.torchdistx_path)
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importlib.import_module("torchdistx")
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if self.cfg.optimizer == "adamw_anyprecision":
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if Path(self.cfg.torchdistx_path).exists():
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sys.path.append(self.cfg.torchdistx_path)
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importlib.import_module("torchdistx")
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if self.cfg.optim_target_modules:
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training_args_kwargs["optim_target_modules"] = self.cfg.optim_target_modules
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@@ -706,21 +706,6 @@ class HFCausalTrainerBuilder(TrainerBuilderBase):
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training_arguments_kwargs["group_by_length"] = self.cfg.group_by_length
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training_arguments_kwargs["curriculum_sampling"] = self.cfg.curriculum_sampling
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training_arguments_kwargs["optim"] = (
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self.cfg.optimizer if self.cfg.optimizer else "adamw_hf"
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)
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if self.cfg.optim_args:
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if isinstance(self.cfg.optim_args, dict):
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optim_args = ",".join(
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[f"{key}={value}" for key, value in self.cfg.optim_args.items()]
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)
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else:
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optim_args = self.cfg.optim_args
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training_arguments_kwargs["optim_args"] = optim_args
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if self.cfg.optim_target_modules:
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training_arguments_kwargs["optim_target_modules"] = (
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self.cfg.optim_target_modules
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)
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training_arguments_kwargs["embedding_lr"] = self.cfg.embedding_lr
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training_arguments_kwargs["embedding_lr_scale"] = self.cfg.embedding_lr_scale
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training_arguments_kwargs["lr_groups"] = self.cfg.lr_groups
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@@ -1082,7 +1067,6 @@ class HFRLTrainerBuilder(TrainerBuilderBase):
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training_args_kwargs["num_train_epochs"] = self.cfg.num_epochs
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training_args = training_args_cls( # pylint: disable=unexpected-keyword-arg
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logging_first_step=True,
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optim=self.cfg.optimizer,
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**training_args_kwargs,
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)
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