datasets = [
    [
        dict(
            abbr='LongBench_narrativeqa',
            eval_cfg=dict(
                evaluator=dict(
                    type='opencompass.datasets.LongBenchF1Evaluator'),
                pred_role='BOT'),
            infer_cfg=dict(
                inferencer=dict(
                    max_out_len=128,
                    type='opencompass.openicl.icl_inferencer.GenInferencer'),
                prompt_template=dict(
                    template=dict(round=[
                        dict(
                            prompt=
                            'You are given a story, which can be either a novel or a movie script, and a question. Answer the question as concisely as you can, using a single phrase if possible. Do not provide any explanation.\n\nStory: {context}\n\nNow, answer the question based on the story as concisely as you can, using a single phrase if possible. Do not provide any explanation.\n\nQuestion: {input}\n\nAnswer:',
                            role='HUMAN'),
                    ]),
                    type=
                    'opencompass.openicl.icl_prompt_template.PromptTemplate'),
                retriever=dict(
                    type='opencompass.openicl.icl_retriever.ZeroRetriever')),
            name='narrativeqa',
            path='opencompass/Longbench',
            reader_cfg=dict(
                input_columns=[
                    'context',
                    'input',
                ],
                output_column='answers',
                test_split='test',
                train_split='test'),
            type='opencompass.datasets.LongBenchnarrativeqaDataset'),
    ],
]
eval = dict(runner=dict(task=dict(dump_details=True)))
models = [
    dict(
        abbr='mask_gdn-1.3B',
        batch_padding=False,
        batch_size=16,
        max_out_len=100,
        max_seq_len=16384,
        path='/mnt/jfzn/msj/train_exp/mask_gdn_1B_hrr-rank4',
        run_cfg=dict(num_gpus=1),
        tokenizer_path='/mnt/jfzn/msj/train_exp/mask_gdn_1B_hrr-rank4',
        type='opencompass.models.HuggingFaceCausalLM'),
]
work_dir = 'outputs/default/20251127_164548'