| datasets = [ | |
| [ | |
| dict( | |
| abbr='LongBench_multifieldqa_en', | |
| eval_cfg=dict( | |
| evaluator=dict( | |
| type='opencompass.datasets.LongBenchF1Evaluator'), | |
| pred_role='BOT'), | |
| infer_cfg=dict( | |
| inferencer=dict( | |
| max_out_len=64, | |
| type='opencompass.openicl.icl_inferencer.GenInferencer'), | |
| prompt_template=dict( | |
| template=dict(round=[ | |
| dict( | |
| prompt= | |
| 'Read the following text and answer briefly.\n\n{context}\n\nNow, answer the following question based on the above text, only give me the answer and do not output any other words.\n\nQuestion: {input}\nAnswer:', | |
| role='HUMAN'), | |
| ]), | |
| type= | |
| 'opencompass.openicl.icl_prompt_template.PromptTemplate'), | |
| retriever=dict( | |
| type='opencompass.openicl.icl_retriever.ZeroRetriever')), | |
| name='multifieldqa_en', | |
| path='opencompass/Longbench', | |
| reader_cfg=dict( | |
| input_columns=[ | |
| 'context', | |
| 'input', | |
| ], | |
| output_column='answers', | |
| test_split='test', | |
| train_split='test'), | |
| type='opencompass.datasets.LongBenchmultifieldqa_enDataset'), | |
| ], | |
| ] | |
| 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' | |