add dataset stage check
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@ -186,6 +186,18 @@ def get_train_args(
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else:
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model_args.compute_dtype = torch.float16
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# transfer training stage to dataset stage
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dataset_stage = general_args.stage
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if general_args.stage == "ppo":
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dataset_stage = "sft"
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elif general_args.stage == "dpo":
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dataset_stage = "rm"
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for dataset_attr in data_args.dataset_list:
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if dataset_attr.stage and dataset_attr.stage != dataset_stage:
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raise ValueError("Dataset {} is not supported for the stage {}"
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.format(dataset_attr.dataset_name, general_args.stage))
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model_args.model_max_length = data_args.max_source_length + data_args.max_target_length
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# Log on each process the small summary:
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