vllm-clearml/results_2024-06-29T02-27-23.641279.json

{
  "results": {
    "mmlu": {
      "acc,none": 0.5438683948155534,
      "acc_stderr,none": 0.004046605401658642,
      "alias": "mmlu"
    },
    "mmlu_humanities": {
      "alias": " - humanities",
      "acc,none": 0.4973432518597237,
      "acc_stderr,none": 0.0069921729107274965
    },
    "mmlu_formal_logic": {
      "alias": "  - formal_logic",
      "acc,none": 0.36507936507936506,
      "acc_stderr,none": 0.04306241259127153
    },
    "mmlu_high_school_european_history": {
      "alias": "  - high_school_european_history",
      "acc,none": 0.6484848484848484,
      "acc_stderr,none": 0.0372820699868265
    },
    "mmlu_high_school_us_history": {
      "alias": "  - high_school_us_history",
      "acc,none": 0.6764705882352942,
      "acc_stderr,none": 0.03283472056108561
    },
    "mmlu_high_school_world_history": {
      "alias": "  - high_school_world_history",
      "acc,none": 0.7088607594936709,
      "acc_stderr,none": 0.029571601065753374
    },
    "mmlu_international_law": {
      "alias": "  - international_law",
      "acc,none": 0.6942148760330579,
      "acc_stderr,none": 0.04205953933884124
    },
    "mmlu_jurisprudence": {
      "alias": "  - jurisprudence",
      "acc,none": 0.6851851851851852,
      "acc_stderr,none": 0.04489931073591312
    },
    "mmlu_logical_fallacies": {
      "alias": "  - logical_fallacies",
      "acc,none": 0.7116564417177914,
      "acc_stderr,none": 0.035590395316173425
    },
    "mmlu_moral_disputes": {
      "alias": "  - moral_disputes",
      "acc,none": 0.630057803468208,
      "acc_stderr,none": 0.025992472029306383
    },
    "mmlu_moral_scenarios": {
      "alias": "  - moral_scenarios",
      "acc,none": 0.3195530726256983,
      "acc_stderr,none": 0.015595520294147402
    },
    "mmlu_philosophy": {
      "alias": "  - philosophy",
      "acc,none": 0.594855305466238,
      "acc_stderr,none": 0.027882383791325953
    },
    "mmlu_prehistory": {
      "alias": "  - prehistory",
      "acc,none": 0.5524691358024691,
      "acc_stderr,none": 0.027667138569422715
    },
    "mmlu_professional_law": {
      "alias": "  - professional_law",
      "acc,none": 0.4048239895697523,
      "acc_stderr,none": 0.012536743830953994
    },
    "mmlu_world_religions": {
      "alias": "  - world_religions",
      "acc,none": 0.6900584795321637,
      "acc_stderr,none": 0.035469769593931624
    },
    "mmlu_other": {
      "alias": " - other",
      "acc,none": 0.5909237206308336,
      "acc_stderr,none": 0.008549729756636936
    },
    "mmlu_business_ethics": {
      "alias": "  - business_ethics",
      "acc,none": 0.61,
      "acc_stderr,none": 0.04902071300001974
    },
    "mmlu_clinical_knowledge": {
      "alias": "  - clinical_knowledge",
      "acc,none": 0.5735849056603773,
      "acc_stderr,none": 0.030437794342983042
    },
    "mmlu_college_medicine": {
      "alias": "  - college_medicine",
      "acc,none": 0.49710982658959535,
      "acc_stderr,none": 0.038124005659748335
    },
    "mmlu_global_facts": {
      "alias": "  - global_facts",
      "acc,none": 0.34,
      "acc_stderr,none": 0.04760952285695235
    },
    "mmlu_human_aging": {
      "alias": "  - human_aging",
      "acc,none": 0.5964125560538116,
      "acc_stderr,none": 0.032928028193303135
    },
    "mmlu_management": {
      "alias": "  - management",
      "acc,none": 0.7669902912621359,
      "acc_stderr,none": 0.04185832598928315
    },
    "mmlu_marketing": {
      "alias": "  - marketing",
      "acc,none": 0.8076923076923077,
      "acc_stderr,none": 0.025819233256483727
    },
    "mmlu_medical_genetics": {
      "alias": "  - medical_genetics",
      "acc,none": 0.56,
      "acc_stderr,none": 0.04988876515698589
    },
    "mmlu_miscellaneous": {
      "alias": "  - miscellaneous",
      "acc,none": 0.6845466155810983,
      "acc_stderr,none": 0.016617501738763397
    },
    "mmlu_nutrition": {
      "alias": "  - nutrition",
      "acc,none": 0.6503267973856209,
      "acc_stderr,none": 0.0273053080762747
    },
    "mmlu_professional_accounting": {
      "alias": "  - professional_accounting",
      "acc,none": 0.42907801418439717,
      "acc_stderr,none": 0.02952591430255855
    },
    "mmlu_professional_medicine": {
      "alias": "  - professional_medicine",
      "acc,none": 0.4338235294117647,
      "acc_stderr,none": 0.03010563657001664
    },
    "mmlu_virology": {
      "alias": "  - virology",
      "acc,none": 0.43373493975903615,
      "acc_stderr,none": 0.03858158940685515
    },
    "mmlu_social_sciences": {
      "alias": " - social_sciences",
      "acc,none": 0.6360090997725056,
      "acc_stderr,none": 0.008459352068826637
    },
    "mmlu_econometrics": {
      "alias": "  - econometrics",
      "acc,none": 0.34210526315789475,
      "acc_stderr,none": 0.04462917535336936
    },
    "mmlu_high_school_geography": {
      "alias": "  - high_school_geography",
      "acc,none": 0.7272727272727273,
      "acc_stderr,none": 0.03173071239071724
    },
    "mmlu_high_school_government_and_politics": {
      "alias": "  - high_school_government_and_politics",
      "acc,none": 0.7979274611398963,
      "acc_stderr,none": 0.02897908979429673
    },
    "mmlu_high_school_macroeconomics": {
      "alias": "  - high_school_macroeconomics",
      "acc,none": 0.5384615384615384,
      "acc_stderr,none": 0.025275892070240644
    },
    "mmlu_high_school_microeconomics": {
      "alias": "  - high_school_microeconomics",
      "acc,none": 0.6176470588235294,
      "acc_stderr,none": 0.03156663099215416
    },
    "mmlu_high_school_psychology": {
      "alias": "  - high_school_psychology",
      "acc,none": 0.7321100917431193,
      "acc_stderr,none": 0.018987462257978652
    },
    "mmlu_human_sexuality": {
      "alias": "  - human_sexuality",
      "acc,none": 0.6412213740458015,
      "acc_stderr,none": 0.04206739313864908
    },
    "mmlu_professional_psychology": {
      "alias": "  - professional_psychology",
      "acc,none": 0.5294117647058824,
      "acc_stderr,none": 0.020192808271433788
    },
    "mmlu_public_relations": {
      "alias": "  - public_relations",
      "acc,none": 0.5636363636363636,
      "acc_stderr,none": 0.04750185058907296
    },
    "mmlu_security_studies": {
      "alias": "  - security_studies",
      "acc,none": 0.689795918367347,
      "acc_stderr,none": 0.02961345987248438
    },
    "mmlu_sociology": {
      "alias": "  - sociology",
      "acc,none": 0.736318407960199,
      "acc_stderr,none": 0.031157150869355568
    },
    "mmlu_us_foreign_policy": {
      "alias": "  - us_foreign_policy",
      "acc,none": 0.77,
      "acc_stderr,none": 0.042295258468165044
    },
    "mmlu_stem": {
      "alias": " - stem",
      "acc,none": 0.4770060260069775,
      "acc_stderr,none": 0.00876253277535237
    },
    "mmlu_abstract_algebra": {
      "alias": "  - abstract_algebra",
      "acc,none": 0.38,
      "acc_stderr,none": 0.04878317312145633
    },
    "mmlu_anatomy": {
      "alias": "  - anatomy",
      "acc,none": 0.4666666666666667,
      "acc_stderr,none": 0.043097329010363554
    },
    "mmlu_astronomy": {
      "alias": "  - astronomy",
      "acc,none": 0.5526315789473685,
      "acc_stderr,none": 0.04046336883978251
    },
    "mmlu_college_biology": {
      "alias": "  - college_biology",
      "acc,none": 0.5486111111111112,
      "acc_stderr,none": 0.04161402398403279
    },
    "mmlu_college_chemistry": {
      "alias": "  - college_chemistry",
      "acc,none": 0.39,
      "acc_stderr,none": 0.04902071300001975
    },
    "mmlu_college_computer_science": {
      "alias": "  - college_computer_science",
      "acc,none": 0.53,
      "acc_stderr,none": 0.05016135580465919
    },
    "mmlu_college_mathematics": {
      "alias": "  - college_mathematics",
      "acc,none": 0.31,
      "acc_stderr,none": 0.04648231987117316
    },
    "mmlu_college_physics": {
      "alias": "  - college_physics",
      "acc,none": 0.37254901960784315,
      "acc_stderr,none": 0.04810840148082633
    },
    "mmlu_computer_security": {
      "alias": "  - computer_security",
      "acc,none": 0.71,
      "acc_stderr,none": 0.045604802157206845
    },
    "mmlu_conceptual_physics": {
      "alias": "  - conceptual_physics",
      "acc,none": 0.4765957446808511,
      "acc_stderr,none": 0.03265019475033582
    },
    "mmlu_electrical_engineering": {
      "alias": "  - electrical_engineering",
      "acc,none": 0.5793103448275863,
      "acc_stderr,none": 0.0411391498118926
    },
    "mmlu_elementary_mathematics": {
      "alias": "  - elementary_mathematics",
      "acc,none": 0.4417989417989418,
      "acc_stderr,none": 0.025576257061253833
    },
    "mmlu_high_school_biology": {
      "alias": "  - high_school_biology",
      "acc,none": 0.6161290322580645,
      "acc_stderr,none": 0.027666182075539645
    },
    "mmlu_high_school_chemistry": {
      "alias": "  - high_school_chemistry",
      "acc,none": 0.46798029556650245,
      "acc_stderr,none": 0.035107665979592154
    },
    "mmlu_high_school_computer_science": {
      "alias": "  - high_school_computer_science",
      "acc,none": 0.56,
      "acc_stderr,none": 0.04988876515698589
    },
    "mmlu_high_school_mathematics": {
      "alias": "  - high_school_mathematics",
      "acc,none": 0.37777777777777777,
      "acc_stderr,none": 0.029560707392465718
    },
    "mmlu_high_school_physics": {
      "alias": "  - high_school_physics",
      "acc,none": 0.33774834437086093,
      "acc_stderr,none": 0.03861557546255169
    },
    "mmlu_high_school_statistics": {
      "alias": "  - high_school_statistics",
      "acc,none": 0.4861111111111111,
      "acc_stderr,none": 0.03408655867977749
    },
    "mmlu_machine_learning": {
      "alias": "  - machine_learning",
      "acc,none": 0.4017857142857143,
      "acc_stderr,none": 0.04653333146973647
    }
  },
  "groups": {
    "mmlu": {
      "acc,none": 0.5438683948155534,
      "acc_stderr,none": 0.004046605401658642,
      "alias": "mmlu"
    },
    "mmlu_humanities": {
      "alias": " - humanities",
      "acc,none": 0.4973432518597237,
      "acc_stderr,none": 0.0069921729107274965
    },
    "mmlu_other": {
      "alias": " - other",
      "acc,none": 0.5909237206308336,
      "acc_stderr,none": 0.008549729756636936
    },
    "mmlu_social_sciences": {
      "alias": " - social_sciences",
      "acc,none": 0.6360090997725056,
      "acc_stderr,none": 0.008459352068826637
    },
    "mmlu_stem": {
      "alias": " - stem",
      "acc,none": 0.4770060260069775,
      "acc_stderr,none": 0.00876253277535237
    }
  },
  "group_subtasks": {
    "mmlu_stem": [
      "mmlu_abstract_algebra",
      "mmlu_college_biology",
      "mmlu_high_school_biology",
      "mmlu_conceptual_physics",
      "mmlu_computer_security",
      "mmlu_college_physics",
      "mmlu_college_chemistry",
      "mmlu_high_school_statistics",
      "mmlu_anatomy",
      "mmlu_high_school_mathematics",
      "mmlu_machine_learning",
      "mmlu_high_school_physics",
      "mmlu_electrical_engineering",
      "mmlu_college_computer_science",
      "mmlu_high_school_chemistry",
      "mmlu_astronomy",
      "mmlu_high_school_computer_science",
      "mmlu_elementary_mathematics",
      "mmlu_college_mathematics"
    ],
    "mmlu_other": [
      "mmlu_business_ethics",
      "mmlu_marketing",
      "mmlu_medical_genetics",
      "mmlu_clinical_knowledge",
      "mmlu_global_facts",
      "mmlu_human_aging",
      "mmlu_professional_medicine",
      "mmlu_nutrition",
      "mmlu_management",
      "mmlu_college_medicine",
      "mmlu_professional_accounting",
      "mmlu_virology",
      "mmlu_miscellaneous"
    ],
    "mmlu_social_sciences": [
      "mmlu_public_relations",
      "mmlu_high_school_macroeconomics",
      "mmlu_human_sexuality",
      "mmlu_high_school_geography",
      "mmlu_high_school_psychology",
      "mmlu_high_school_microeconomics",
      "mmlu_high_school_government_and_politics",
      "mmlu_us_foreign_policy",
      "mmlu_sociology",
      "mmlu_security_studies",
      "mmlu_econometrics",
      "mmlu_professional_psychology"
    ],
    "mmlu_humanities": [
      "mmlu_philosophy",
      "mmlu_logical_fallacies",
      "mmlu_moral_disputes",
      "mmlu_jurisprudence",
      "mmlu_high_school_us_history",
      "mmlu_high_school_world_history",
      "mmlu_world_religions",
      "mmlu_moral_scenarios",
      "mmlu_prehistory",
      "mmlu_formal_logic",
      "mmlu_international_law",
      "mmlu_professional_law",
      "mmlu_high_school_european_history"
    ],
    "mmlu": [
      "mmlu_humanities",
      "mmlu_social_sciences",
      "mmlu_other",
      "mmlu_stem"
    ]
  },
  "configs": {
    "mmlu_abstract_algebra": {
      "task": "mmlu_abstract_algebra",
      "task_alias": "abstract_algebra",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "abstract_algebra",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_anatomy": {
      "task": "mmlu_anatomy",
      "task_alias": "anatomy",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "anatomy",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_astronomy": {
      "task": "mmlu_astronomy",
      "task_alias": "astronomy",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "astronomy",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_business_ethics": {
      "task": "mmlu_business_ethics",
      "task_alias": "business_ethics",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "business_ethics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_clinical_knowledge": {
      "task": "mmlu_clinical_knowledge",
      "task_alias": "clinical_knowledge",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "clinical_knowledge",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_college_biology": {
      "task": "mmlu_college_biology",
      "task_alias": "college_biology",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "college_biology",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_college_chemistry": {
      "task": "mmlu_college_chemistry",
      "task_alias": "college_chemistry",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "college_chemistry",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_college_computer_science": {
      "task": "mmlu_college_computer_science",
      "task_alias": "college_computer_science",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "college_computer_science",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_college_mathematics": {
      "task": "mmlu_college_mathematics",
      "task_alias": "college_mathematics",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "college_mathematics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_college_medicine": {
      "task": "mmlu_college_medicine",
      "task_alias": "college_medicine",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "college_medicine",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_college_physics": {
      "task": "mmlu_college_physics",
      "task_alias": "college_physics",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "college_physics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_computer_security": {
      "task": "mmlu_computer_security",
      "task_alias": "computer_security",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "computer_security",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_conceptual_physics": {
      "task": "mmlu_conceptual_physics",
      "task_alias": "conceptual_physics",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "conceptual_physics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_econometrics": {
      "task": "mmlu_econometrics",
      "task_alias": "econometrics",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "econometrics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_electrical_engineering": {
      "task": "mmlu_electrical_engineering",
      "task_alias": "electrical_engineering",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "electrical_engineering",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_elementary_mathematics": {
      "task": "mmlu_elementary_mathematics",
      "task_alias": "elementary_mathematics",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "elementary_mathematics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_formal_logic": {
      "task": "mmlu_formal_logic",
      "task_alias": "formal_logic",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "formal_logic",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_global_facts": {
      "task": "mmlu_global_facts",
      "task_alias": "global_facts",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "global_facts",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_biology": {
      "task": "mmlu_high_school_biology",
      "task_alias": "high_school_biology",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_biology",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_chemistry": {
      "task": "mmlu_high_school_chemistry",
      "task_alias": "high_school_chemistry",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_chemistry",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_computer_science": {
      "task": "mmlu_high_school_computer_science",
      "task_alias": "high_school_computer_science",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_computer_science",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_european_history": {
      "task": "mmlu_high_school_european_history",
      "task_alias": "high_school_european_history",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_european_history",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_geography": {
      "task": "mmlu_high_school_geography",
      "task_alias": "high_school_geography",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_geography",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_government_and_politics": {
      "task": "mmlu_high_school_government_and_politics",
      "task_alias": "high_school_government_and_politics",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_government_and_politics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_macroeconomics": {
      "task": "mmlu_high_school_macroeconomics",
      "task_alias": "high_school_macroeconomics",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_macroeconomics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_mathematics": {
      "task": "mmlu_high_school_mathematics",
      "task_alias": "high_school_mathematics",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_mathematics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_microeconomics": {
      "task": "mmlu_high_school_microeconomics",
      "task_alias": "high_school_microeconomics",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_microeconomics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_physics": {
      "task": "mmlu_high_school_physics",
      "task_alias": "high_school_physics",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_physics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_psychology": {
      "task": "mmlu_high_school_psychology",
      "task_alias": "high_school_psychology",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_psychology",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_statistics": {
      "task": "mmlu_high_school_statistics",
      "task_alias": "high_school_statistics",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_statistics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_us_history": {
      "task": "mmlu_high_school_us_history",
      "task_alias": "high_school_us_history",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_us_history",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_high_school_world_history": {
      "task": "mmlu_high_school_world_history",
      "task_alias": "high_school_world_history",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "high_school_world_history",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_human_aging": {
      "task": "mmlu_human_aging",
      "task_alias": "human_aging",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "human_aging",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_human_sexuality": {
      "task": "mmlu_human_sexuality",
      "task_alias": "human_sexuality",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "human_sexuality",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_international_law": {
      "task": "mmlu_international_law",
      "task_alias": "international_law",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "international_law",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about international law.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_jurisprudence": {
      "task": "mmlu_jurisprudence",
      "task_alias": "jurisprudence",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "jurisprudence",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_logical_fallacies": {
      "task": "mmlu_logical_fallacies",
      "task_alias": "logical_fallacies",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "logical_fallacies",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_machine_learning": {
      "task": "mmlu_machine_learning",
      "task_alias": "machine_learning",
      "group": "mmlu_stem",
      "group_alias": "stem",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "machine_learning",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_management": {
      "task": "mmlu_management",
      "task_alias": "management",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "management",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about management.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_marketing": {
      "task": "mmlu_marketing",
      "task_alias": "marketing",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "marketing",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_medical_genetics": {
      "task": "mmlu_medical_genetics",
      "task_alias": "medical_genetics",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "medical_genetics",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_miscellaneous": {
      "task": "mmlu_miscellaneous",
      "task_alias": "miscellaneous",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "miscellaneous",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_moral_disputes": {
      "task": "mmlu_moral_disputes",
      "task_alias": "moral_disputes",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "moral_disputes",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_moral_scenarios": {
      "task": "mmlu_moral_scenarios",
      "task_alias": "moral_scenarios",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "moral_scenarios",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_nutrition": {
      "task": "mmlu_nutrition",
      "task_alias": "nutrition",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "nutrition",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_philosophy": {
      "task": "mmlu_philosophy",
      "task_alias": "philosophy",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "philosophy",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_prehistory": {
      "task": "mmlu_prehistory",
      "task_alias": "prehistory",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "prehistory",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_professional_accounting": {
      "task": "mmlu_professional_accounting",
      "task_alias": "professional_accounting",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "professional_accounting",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_professional_law": {
      "task": "mmlu_professional_law",
      "task_alias": "professional_law",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "professional_law",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_professional_medicine": {
      "task": "mmlu_professional_medicine",
      "task_alias": "professional_medicine",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "professional_medicine",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_professional_psychology": {
      "task": "mmlu_professional_psychology",
      "task_alias": "professional_psychology",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "professional_psychology",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_public_relations": {
      "task": "mmlu_public_relations",
      "task_alias": "public_relations",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "public_relations",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_security_studies": {
      "task": "mmlu_security_studies",
      "task_alias": "security_studies",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "security_studies",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_sociology": {
      "task": "mmlu_sociology",
      "task_alias": "sociology",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "sociology",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_us_foreign_policy": {
      "task": "mmlu_us_foreign_policy",
      "task_alias": "us_foreign_policy",
      "group": "mmlu_social_sciences",
      "group_alias": "social_sciences",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "us_foreign_policy",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_virology": {
      "task": "mmlu_virology",
      "task_alias": "virology",
      "group": "mmlu_other",
      "group_alias": "other",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "virology",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about virology.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    },
    "mmlu_world_religions": {
      "task": "mmlu_world_religions",
      "task_alias": "world_religions",
      "group": "mmlu_humanities",
      "group_alias": "humanities",
      "dataset_path": "hails/mmlu_no_train",
      "dataset_name": "world_religions",
      "test_split": "test",
      "fewshot_split": "dev",
      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
      "doc_to_target": "answer",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n"
      },
      "num_fewshot": 5,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 0.0
      }
    }
  },
  "versions": {
    "mmlu_abstract_algebra": 0.0,
    "mmlu_anatomy": 0.0,
    "mmlu_astronomy": 0.0,
    "mmlu_business_ethics": 0.0,
    "mmlu_clinical_knowledge": 0.0,
    "mmlu_college_biology": 0.0,
    "mmlu_college_chemistry": 0.0,
    "mmlu_college_computer_science": 0.0,
    "mmlu_college_mathematics": 0.0,
    "mmlu_college_medicine": 0.0,
    "mmlu_college_physics": 0.0,
    "mmlu_computer_security": 0.0,
    "mmlu_conceptual_physics": 0.0,
    "mmlu_econometrics": 0.0,
    "mmlu_electrical_engineering": 0.0,
    "mmlu_elementary_mathematics": 0.0,
    "mmlu_formal_logic": 0.0,
    "mmlu_global_facts": 0.0,
    "mmlu_high_school_biology": 0.0,
    "mmlu_high_school_chemistry": 0.0,
    "mmlu_high_school_computer_science": 0.0,
    "mmlu_high_school_european_history": 0.0,
    "mmlu_high_school_geography": 0.0,
    "mmlu_high_school_government_and_politics": 0.0,
    "mmlu_high_school_macroeconomics": 0.0,
    "mmlu_high_school_mathematics": 0.0,
    "mmlu_high_school_microeconomics": 0.0,
    "mmlu_high_school_physics": 0.0,
    "mmlu_high_school_psychology": 0.0,
    "mmlu_high_school_statistics": 0.0,
    "mmlu_high_school_us_history": 0.0,
    "mmlu_high_school_world_history": 0.0,
    "mmlu_human_aging": 0.0,
    "mmlu_human_sexuality": 0.0,
    "mmlu_international_law": 0.0,
    "mmlu_jurisprudence": 0.0,
    "mmlu_logical_fallacies": 0.0,
    "mmlu_machine_learning": 0.0,
    "mmlu_management": 0.0,
    "mmlu_marketing": 0.0,
    "mmlu_medical_genetics": 0.0,
    "mmlu_miscellaneous": 0.0,
    "mmlu_moral_disputes": 0.0,
    "mmlu_moral_scenarios": 0.0,
    "mmlu_nutrition": 0.0,
    "mmlu_philosophy": 0.0,
    "mmlu_prehistory": 0.0,
    "mmlu_professional_accounting": 0.0,
    "mmlu_professional_law": 0.0,
    "mmlu_professional_medicine": 0.0,
    "mmlu_professional_psychology": 0.0,
    "mmlu_public_relations": 0.0,
    "mmlu_security_studies": 0.0,
    "mmlu_sociology": 0.0,
    "mmlu_us_foreign_policy": 0.0,
    "mmlu_virology": 0.0,
    "mmlu_world_religions": 0.0
  },
  "n-shot": {
    "mmlu": 0,
    "mmlu_abstract_algebra": 5,
    "mmlu_anatomy": 5,
    "mmlu_astronomy": 5,
    "mmlu_business_ethics": 5,
    "mmlu_clinical_knowledge": 5,
    "mmlu_college_biology": 5,
    "mmlu_college_chemistry": 5,
    "mmlu_college_computer_science": 5,
    "mmlu_college_mathematics": 5,
    "mmlu_college_medicine": 5,
    "mmlu_college_physics": 5,
    "mmlu_computer_security": 5,
    "mmlu_conceptual_physics": 5,
    "mmlu_econometrics": 5,
    "mmlu_electrical_engineering": 5,
    "mmlu_elementary_mathematics": 5,
    "mmlu_formal_logic": 5,
    "mmlu_global_facts": 5,
    "mmlu_high_school_biology": 5,
    "mmlu_high_school_chemistry": 5,
    "mmlu_high_school_computer_science": 5,
    "mmlu_high_school_european_history": 5,
    "mmlu_high_school_geography": 5,
    "mmlu_high_school_government_and_politics": 5,
    "mmlu_high_school_macroeconomics": 5,
    "mmlu_high_school_mathematics": 5,
    "mmlu_high_school_microeconomics": 5,
    "mmlu_high_school_physics": 5,
    "mmlu_high_school_psychology": 5,
    "mmlu_high_school_statistics": 5,
    "mmlu_high_school_us_history": 5,
    "mmlu_high_school_world_history": 5,
    "mmlu_human_aging": 5,
    "mmlu_human_sexuality": 5,
    "mmlu_humanities": 5,
    "mmlu_international_law": 5,
    "mmlu_jurisprudence": 5,
    "mmlu_logical_fallacies": 5,
    "mmlu_machine_learning": 5,
    "mmlu_management": 5,
    "mmlu_marketing": 5,
    "mmlu_medical_genetics": 5,
    "mmlu_miscellaneous": 5,
    "mmlu_moral_disputes": 5,
    "mmlu_moral_scenarios": 5,
    "mmlu_nutrition": 5,
    "mmlu_other": 5,
    "mmlu_philosophy": 5,
    "mmlu_prehistory": 5,
    "mmlu_professional_accounting": 5,
    "mmlu_professional_law": 5,
    "mmlu_professional_medicine": 5,
    "mmlu_professional_psychology": 5,
    "mmlu_public_relations": 5,
    "mmlu_security_studies": 5,
    "mmlu_social_sciences": 5,
    "mmlu_sociology": 5,
    "mmlu_stem": 5,
    "mmlu_us_foreign_policy": 5,
    "mmlu_virology": 5,
    "mmlu_world_religions": 5
  },
  "higher_is_better": {
    "mmlu": {
      "acc": true
    },
    "mmlu_abstract_algebra": {
      "acc": true
    },
    "mmlu_anatomy": {
      "acc": true
    },
    "mmlu_astronomy": {
      "acc": true
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    "mmlu_college_chemistry": {
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    "mmlu_college_medicine": {
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    "mmlu_formal_logic": {
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    "mmlu_global_facts": {
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    "mmlu_high_school_biology": {
      "acc": true
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    "mmlu_high_school_chemistry": {
      "acc": true
    },
    "mmlu_high_school_computer_science": {
      "acc": true
    },
    "mmlu_high_school_european_history": {
      "acc": true
    },
    "mmlu_high_school_geography": {
      "acc": true
    },
    "mmlu_high_school_government_and_politics": {
      "acc": true
    },
    "mmlu_high_school_macroeconomics": {
      "acc": true
    },
    "mmlu_high_school_mathematics": {
      "acc": true
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    "mmlu_high_school_microeconomics": {
      "acc": true
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    "mmlu_high_school_physics": {
      "acc": true
    },
    "mmlu_high_school_psychology": {
      "acc": true
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    "mmlu_high_school_statistics": {
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    "mmlu_high_school_us_history": {
      "acc": true
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    "mmlu_high_school_world_history": {
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    "mmlu_human_aging": {
      "acc": true
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    "mmlu_human_sexuality": {
      "acc": true
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    "mmlu_humanities": {
      "acc": true
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    "mmlu_jurisprudence": {
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    "mmlu_management": {
      "acc": true
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    "mmlu_marketing": {
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    "mmlu_miscellaneous": {
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    "mmlu_moral_disputes": {
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    "mmlu_other": {
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    "mmlu_philosophy": {
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    "mmlu_professional_accounting": {
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    "mmlu_professional_law": {
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    "mmlu_professional_medicine": {
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    "mmlu_professional_psychology": {
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    "mmlu_public_relations": {
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    "mmlu_security_studies": {
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    "mmlu_social_sciences": {
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    "mmlu_sociology": {
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    "mmlu_stem": {
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    "mmlu_us_foreign_policy": {
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    "mmlu_virology": {
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    "mmlu_world_religions": {
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  },
  "n-samples": {
    "mmlu_philosophy": {
      "original": 311,
      "effective": 311
    },
    "mmlu_logical_fallacies": {
      "original": 163,
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    },
    "mmlu_moral_disputes": {
      "original": 346,
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    "mmlu_jurisprudence": {
      "original": 108,
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    },
    "mmlu_high_school_us_history": {
      "original": 204,
      "effective": 204
    },
    "mmlu_high_school_world_history": {
      "original": 237,
      "effective": 237
    },
    "mmlu_world_religions": {
      "original": 171,
      "effective": 171
    },
    "mmlu_moral_scenarios": {
      "original": 895,
      "effective": 895
    },
    "mmlu_prehistory": {
      "original": 324,
      "effective": 324
    },
    "mmlu_formal_logic": {
      "original": 126,
      "effective": 126
    },
    "mmlu_international_law": {
      "original": 121,
      "effective": 121
    },
    "mmlu_professional_law": {
      "original": 1534,
      "effective": 1534
    },
    "mmlu_high_school_european_history": {
      "original": 165,
      "effective": 165
    },
    "mmlu_public_relations": {
      "original": 110,
      "effective": 110
    },
    "mmlu_high_school_macroeconomics": {
      "original": 390,
      "effective": 390
    },
    "mmlu_human_sexuality": {
      "original": 131,
      "effective": 131
    },
    "mmlu_high_school_geography": {
      "original": 198,
      "effective": 198
    },
    "mmlu_high_school_psychology": {
      "original": 545,
      "effective": 545
    },
    "mmlu_high_school_microeconomics": {
      "original": 238,
      "effective": 238
    },
    "mmlu_high_school_government_and_politics": {
      "original": 193,
      "effective": 193
    },
    "mmlu_us_foreign_policy": {
      "original": 100,
      "effective": 100
    },
    "mmlu_sociology": {
      "original": 201,
      "effective": 201
    },
    "mmlu_security_studies": {
      "original": 245,
      "effective": 245
    },
    "mmlu_econometrics": {
      "original": 114,
      "effective": 114
    },
    "mmlu_professional_psychology": {
      "original": 612,
      "effective": 612
    },
    "mmlu_business_ethics": {
      "original": 100,
      "effective": 100
    },
    "mmlu_marketing": {
      "original": 234,
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    },
    "mmlu_medical_genetics": {
      "original": 100,
      "effective": 100
    },
    "mmlu_clinical_knowledge": {
      "original": 265,
      "effective": 265
    },
    "mmlu_global_facts": {
      "original": 100,
      "effective": 100
    },
    "mmlu_human_aging": {
      "original": 223,
      "effective": 223
    },
    "mmlu_professional_medicine": {
      "original": 272,
      "effective": 272
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    "mmlu_nutrition": {
      "original": 306,
      "effective": 306
    },
    "mmlu_management": {
      "original": 103,
      "effective": 103
    },
    "mmlu_college_medicine": {
      "original": 173,
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    "mmlu_professional_accounting": {
      "original": 282,
      "effective": 282
    },
    "mmlu_virology": {
      "original": 166,
      "effective": 166
    },
    "mmlu_miscellaneous": {
      "original": 783,
      "effective": 783
    },
    "mmlu_abstract_algebra": {
      "original": 100,
      "effective": 100
    },
    "mmlu_college_biology": {
      "original": 144,
      "effective": 144
    },
    "mmlu_high_school_biology": {
      "original": 310,
      "effective": 310
    },
    "mmlu_conceptual_physics": {
      "original": 235,
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    "mmlu_computer_security": {
      "original": 100,
      "effective": 100
    },
    "mmlu_college_physics": {
      "original": 102,
      "effective": 102
    },
    "mmlu_college_chemistry": {
      "original": 100,
      "effective": 100
    },
    "mmlu_high_school_statistics": {
      "original": 216,
      "effective": 216
    },
    "mmlu_anatomy": {
      "original": 135,
      "effective": 135
    },
    "mmlu_high_school_mathematics": {
      "original": 270,
      "effective": 270
    },
    "mmlu_machine_learning": {
      "original": 112,
      "effective": 112
    },
    "mmlu_high_school_physics": {
      "original": 151,
      "effective": 151
    },
    "mmlu_electrical_engineering": {
      "original": 145,
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    "mmlu_college_computer_science": {
      "original": 100,
      "effective": 100
    },
    "mmlu_high_school_chemistry": {
      "original": 203,
      "effective": 203
    },
    "mmlu_astronomy": {
      "original": 152,
      "effective": 152
    },
    "mmlu_high_school_computer_science": {
      "original": 100,
      "effective": 100
    },
    "mmlu_elementary_mathematics": {
      "original": 378,
      "effective": 378
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    "mmlu_college_mathematics": {
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  "config": {
    "model": "vllm",
    "model_args": "pretrained=/cache/abhinav/models/Phase1/gptq-Qwen/Qwen2-1.5B-Instruct-garage-bAInd/Open-Platypus-mse-damp0.1-ns512-seqlen4K,tensor_parallel_size=2,dtype=auto,add_bos_token=True,gpu_memory_utilization=0.4,data_parallel_size=1,max_model_len=4096",
    "batch_size": "auto",
    "batch_sizes": [],
    "device": "cuda",
    "use_cache": null,
    "limit": null,
    "bootstrap_iters": 100000,
    "gen_kwargs": null,
    "random_seed": 0,
    "numpy_seed": 1234,
    "torch_seed": 1234,
    "fewshot_seed": 1234
  },
  "git_hash": null,
  "date": 1719624343.9120553,
  "pretty_env_info": "PyTorch version: 2.3.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.3 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.29.6\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.1.105\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 545.23.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4900.22\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.4\n[pip3] torch==2.3.0\n[pip3] triton==2.3.0\n[conda] Could not collect",
  "transformers_version": "4.41.2",
  "upper_git_hash": null,
  "task_hashes": {},
  "model_source": "vllm",
  "model_name": "/cache/abhinav/models/Phase1/gptq-Qwen/Qwen2-1.5B-Instruct-garage-bAInd/Open-Platypus-mse-damp0.1-ns512-seqlen4K",
  "model_name_sanitized": "__cache__abhinav__models__Phase1__gptq-Qwen__Qwen2-1.5B-Instruct-garage-bAInd__Open-Platypus-mse-damp0.1-ns512-seqlen4K",
  "system_instruction": null,
  "system_instruction_sha": null,
  "fewshot_as_multiturn": false,
  "chat_template": null,
  "chat_template_sha": null,
  "start_time": 7638031.049041288,
  "end_time": 7641735.991916678,
  "total_evaluation_time_seconds": "3704.942875389941"
}