{
  "results": {
    "ifeval": {
      "alias": "ifeval",
      "prompt_level_strict_acc,none": 0.8125,
      "prompt_level_strict_acc_stderr,none": 0.10077822185373188,
      "inst_level_strict_acc,none": 0.8333333333333334,
      "inst_level_strict_acc_stderr,none": "N/A",
      "prompt_level_loose_acc,none": 0.8125,
      "prompt_level_loose_acc_stderr,none": 0.10077822185373188,
      "inst_level_loose_acc,none": 0.875,
      "inst_level_loose_acc_stderr,none": "N/A"
    },
    "mmlu": {
      "acc,none": 0.7088815789473685,
      "acc_stderr,none": 0.012041450801133636,
      "alias": "mmlu"
    },
    "mmlu_humanities": {
      "acc,none": 0.8028846153846154,
      "acc_stderr,none": 0.02739400408056615,
      "alias": " - humanities"
    },
    "mmlu_formal_logic": {
      "alias": "  - formal_logic",
      "acc,none": 0.6875,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_high_school_european_history": {
      "alias": "  - high_school_european_history",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_high_school_us_history": {
      "alias": "  - high_school_us_history",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_high_school_world_history": {
      "alias": "  - high_school_world_history",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_international_law": {
      "alias": "  - international_law",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_jurisprudence": {
      "alias": "  - jurisprudence",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_logical_fallacies": {
      "alias": "  - logical_fallacies",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_moral_disputes": {
      "alias": "  - moral_disputes",
      "acc,none": 0.625,
      "acc_stderr,none": 0.125
    },
    "mmlu_moral_scenarios": {
      "alias": "  - moral_scenarios",
      "acc,none": 0.625,
      "acc_stderr,none": 0.125
    },
    "mmlu_philosophy": {
      "alias": "  - philosophy",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_prehistory": {
      "alias": "  - prehistory",
      "acc,none": 0.6875,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_professional_law": {
      "alias": "  - professional_law",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_world_religions": {
      "alias": "  - world_religions",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_other": {
      "acc,none": 0.75,
      "acc_stderr,none": 0.028846153846153848,
      "alias": " - other"
    },
    "mmlu_business_ethics": {
      "alias": "  - business_ethics",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_clinical_knowledge": {
      "alias": "  - clinical_knowledge",
      "acc,none": 0.6875,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_college_medicine": {
      "alias": "  - college_medicine",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_global_facts": {
      "alias": "  - global_facts",
      "acc,none": 0.5625,
      "acc_stderr,none": 0.128086884574495
    },
    "mmlu_human_aging": {
      "alias": "  - human_aging",
      "acc,none": 0.75,
      "acc_stderr,none": 0.11180339887498948
    },
    "mmlu_management": {
      "alias": "  - management",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_marketing": {
      "alias": "  - marketing",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_medical_genetics": {
      "alias": "  - medical_genetics",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_miscellaneous": {
      "alias": "  - miscellaneous",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_nutrition": {
      "alias": "  - nutrition",
      "acc,none": 0.6875,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_professional_accounting": {
      "alias": "  - professional_accounting",
      "acc,none": 0.5,
      "acc_stderr,none": 0.12909944487358055
    },
    "mmlu_professional_medicine": {
      "alias": "  - professional_medicine",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_virology": {
      "alias": "  - virology",
      "acc,none": 0.4375,
      "acc_stderr,none": 0.128086884574495
    },
    "mmlu_social_sciences": {
      "acc,none": 0.8385416666666666,
      "acc_stderr,none": 0.025762391391041032,
      "alias": " - social sciences"
    },
    "mmlu_econometrics": {
      "alias": "  - econometrics",
      "acc,none": 0.625,
      "acc_stderr,none": 0.125
    },
    "mmlu_high_school_geography": {
      "alias": "  - high_school_geography",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_high_school_government_and_politics": {
      "alias": "  - high_school_government_and_politics",
      "acc,none": 1.0,
      "acc_stderr,none": 0.0
    },
    "mmlu_high_school_macroeconomics": {
      "alias": "  - high_school_macroeconomics",
      "acc,none": 0.6875,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_high_school_microeconomics": {
      "alias": "  - high_school_microeconomics",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_high_school_psychology": {
      "alias": "  - high_school_psychology",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_human_sexuality": {
      "alias": "  - human_sexuality",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_professional_psychology": {
      "alias": "  - professional_psychology",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_public_relations": {
      "alias": "  - public_relations",
      "acc,none": 0.625,
      "acc_stderr,none": 0.125
    },
    "mmlu_security_studies": {
      "alias": "  - security_studies",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_sociology": {
      "alias": "  - sociology",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_us_foreign_policy": {
      "alias": "  - us_foreign_policy",
      "acc,none": 1.0,
      "acc_stderr,none": 0.0
    },
    "mmlu_stem": {
      "acc,none": 0.6217105263157895,
      "acc_stderr,none": 0.018126960046215203,
      "alias": "stem"
    },
    "mmlu_abstract_algebra": {
      "alias": " - abstract_algebra",
      "acc,none": 0.3125,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_anatomy": {
      "alias": " - anatomy",
      "acc,none": 0.75,
      "acc_stderr,none": 0.11180339887498948
    },
    "mmlu_astronomy": {
      "alias": " - astronomy",
      "acc,none": 0.9375,
      "acc_stderr,none": 0.0625
    },
    "mmlu_college_biology": {
      "alias": " - college_biology",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_college_chemistry": {
      "alias": " - college_chemistry",
      "acc,none": 0.3125,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_college_computer_science": {
      "alias": " - college_computer_science",
      "acc,none": 0.4375,
      "acc_stderr,none": 0.128086884574495
    },
    "mmlu_college_mathematics": {
      "alias": " - college_mathematics",
      "acc,none": 0.25,
      "acc_stderr,none": 0.11180339887498948
    },
    "mmlu_college_physics": {
      "alias": " - college_physics",
      "acc,none": 0.625,
      "acc_stderr,none": 0.125
    },
    "mmlu_computer_security": {
      "alias": " - computer_security",
      "acc,none": 0.625,
      "acc_stderr,none": 0.125
    },
    "mmlu_conceptual_physics": {
      "alias": " - conceptual_physics",
      "acc,none": 0.75,
      "acc_stderr,none": 0.11180339887498948
    },
    "mmlu_electrical_engineering": {
      "alias": " - electrical_engineering",
      "acc,none": 0.5625,
      "acc_stderr,none": 0.128086884574495
    },
    "mmlu_elementary_mathematics": {
      "alias": " - elementary_mathematics",
      "acc,none": 0.5,
      "acc_stderr,none": 0.12909944487358055
    },
    "mmlu_high_school_biology": {
      "alias": " - high_school_biology",
      "acc,none": 1.0,
      "acc_stderr,none": 0.0
    },
    "mmlu_high_school_chemistry": {
      "alias": " - high_school_chemistry",
      "acc,none": 0.75,
      "acc_stderr,none": 0.11180339887498948
    },
    "mmlu_high_school_computer_science": {
      "alias": " - high_school_computer_science",
      "acc,none": 0.875,
      "acc_stderr,none": 0.08539125638299665
    },
    "mmlu_high_school_mathematics": {
      "alias": " - high_school_mathematics",
      "acc,none": 0.3125,
      "acc_stderr,none": 0.11967838846954226
    },
    "mmlu_high_school_physics": {
      "alias": " - high_school_physics",
      "acc,none": 0.5625,
      "acc_stderr,none": 0.128086884574495
    },
    "mmlu_high_school_statistics": {
      "alias": " - high_school_statistics",
      "acc,none": 0.8125,
      "acc_stderr,none": 0.10077822185373188
    },
    "mmlu_machine_learning": {
      "alias": " - machine_learning",
      "acc,none": 0.625,
      "acc_stderr,none": 0.125
    }
  },
  "groups": {
    "mmlu": {
      "acc,none": 0.7088815789473685,
      "acc_stderr,none": 0.012041450801133636,
      "alias": "mmlu"
    },
    "mmlu_humanities": {
      "acc,none": 0.8028846153846154,
      "acc_stderr,none": 0.02739400408056615,
      "alias": " - humanities"
    },
    "mmlu_other": {
      "acc,none": 0.75,
      "acc_stderr,none": 0.028846153846153848,
      "alias": " - other"
    },
    "mmlu_social_sciences": {
      "acc,none": 0.8385416666666666,
      "acc_stderr,none": 0.025762391391041032,
      "alias": " - social sciences"
    },
    "mmlu_stem": {
      "acc,none": 0.6217105263157895,
      "acc_stderr,none": 0.018126960046215203,
      "alias": "stem"
    }
  },
  "group_subtasks": {
    "ifeval": [],
    "mmlu_humanities": [
      "mmlu_moral_disputes",
      "mmlu_high_school_european_history",
      "mmlu_moral_scenarios",
      "mmlu_formal_logic",
      "mmlu_prehistory",
      "mmlu_professional_law",
      "mmlu_world_religions",
      "mmlu_international_law",
      "mmlu_high_school_us_history",
      "mmlu_high_school_world_history",
      "mmlu_logical_fallacies",
      "mmlu_jurisprudence",
      "mmlu_philosophy"
    ],
    "mmlu_social_sciences": [
      "mmlu_professional_psychology",
      "mmlu_high_school_psychology",
      "mmlu_econometrics",
      "mmlu_public_relations",
      "mmlu_us_foreign_policy",
      "mmlu_high_school_microeconomics",
      "mmlu_high_school_macroeconomics",
      "mmlu_sociology",
      "mmlu_high_school_geography",
      "mmlu_high_school_government_and_politics",
      "mmlu_security_studies",
      "mmlu_human_sexuality"
    ],
    "mmlu_other": [
      "mmlu_professional_accounting",
      "mmlu_miscellaneous",
      "mmlu_marketing",
      "mmlu_business_ethics",
      "mmlu_human_aging",
      "mmlu_professional_medicine",
      "mmlu_nutrition",
      "mmlu_college_medicine",
      "mmlu_virology",
      "mmlu_medical_genetics",
      "mmlu_clinical_knowledge",
      "mmlu_global_facts",
      "mmlu_management"
    ],
    "mmlu": [
      "mmlu_stem",
      "mmlu_other",
      "mmlu_social_sciences",
      "mmlu_humanities"
    ],
    "mmlu_stem": [
      "mmlu_elementary_mathematics",
      "mmlu_high_school_biology",
      "mmlu_electrical_engineering",
      "mmlu_high_school_mathematics",
      "mmlu_astronomy",
      "mmlu_machine_learning",
      "mmlu_college_chemistry",
      "mmlu_abstract_algebra",
      "mmlu_high_school_chemistry",
      "mmlu_computer_security",
      "mmlu_college_biology",
      "mmlu_high_school_computer_science",
      "mmlu_anatomy",
      "mmlu_college_mathematics",
      "mmlu_high_school_statistics",
      "mmlu_high_school_physics",
      "mmlu_conceptual_physics",
      "mmlu_college_computer_science",
      "mmlu_college_physics"
    ]
  },
  "configs": {
    "ifeval": {
      "task": "ifeval",
      "dataset_path": "google/IFEval",
      "test_split": "train",
      "doc_to_text": "prompt",
      "doc_to_target": 0,
      "unsafe_code": false,
      "process_results": "def process_results(doc, results):\n    inp = InputExample(\n        key=doc[\"key\"],\n        instruction_id_list=doc[\"instruction_id_list\"],\n        prompt=doc[\"prompt\"],\n        kwargs=doc[\"kwargs\"],\n    )\n    response = results[0]\n\n    out_strict = test_instruction_following_strict(inp, response)\n    out_loose = test_instruction_following_loose(inp, response)\n\n    return {\n        \"prompt_level_strict_acc\": out_strict.follow_all_instructions,\n        \"inst_level_strict_acc\": out_strict.follow_instruction_list,\n        \"prompt_level_loose_acc\": out_loose.follow_all_instructions,\n        \"inst_level_loose_acc\": out_loose.follow_instruction_list,\n    }\n",
      "description": "",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "num_fewshot": 0,
      "metric_list": [
        {
          "metric": "prompt_level_strict_acc",
          "aggregation": "mean",
          "higher_is_better": true
        },
        {
          "metric": "inst_level_strict_acc",
          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
          "higher_is_better": true
        },
        {
          "metric": "prompt_level_loose_acc",
          "aggregation": "mean",
          "higher_is_better": true
        },
        {
          "metric": "inst_level_loose_acc",
          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
          "higher_is_better": true
        }
      ],
      "output_type": "generate_until",
      "generation_kwargs": {
        "until": [],
        "do_sample": false,
        "temperature": 0.0,
        "max_gen_toks": 1280
      },
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 4.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_abstract_algebra": {
      "task": "mmlu_abstract_algebra",
      "task_alias": "abstract_algebra",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "abstract_algebra",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_anatomy": {
      "task": "mmlu_anatomy",
      "task_alias": "anatomy",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "anatomy",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_astronomy": {
      "task": "mmlu_astronomy",
      "task_alias": "astronomy",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "astronomy",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_business_ethics": {
      "task": "mmlu_business_ethics",
      "task_alias": "business_ethics",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "business_ethics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_clinical_knowledge": {
      "task": "mmlu_clinical_knowledge",
      "task_alias": "clinical_knowledge",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "clinical_knowledge",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_college_biology": {
      "task": "mmlu_college_biology",
      "task_alias": "college_biology",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "college_biology",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_college_chemistry": {
      "task": "mmlu_college_chemistry",
      "task_alias": "college_chemistry",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "college_chemistry",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_college_computer_science": {
      "task": "mmlu_college_computer_science",
      "task_alias": "college_computer_science",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "college_computer_science",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_college_mathematics": {
      "task": "mmlu_college_mathematics",
      "task_alias": "college_mathematics",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "college_mathematics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_college_medicine": {
      "task": "mmlu_college_medicine",
      "task_alias": "college_medicine",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "college_medicine",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_college_physics": {
      "task": "mmlu_college_physics",
      "task_alias": "college_physics",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "college_physics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_computer_security": {
      "task": "mmlu_computer_security",
      "task_alias": "computer_security",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "computer_security",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_conceptual_physics": {
      "task": "mmlu_conceptual_physics",
      "task_alias": "conceptual_physics",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "conceptual_physics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_econometrics": {
      "task": "mmlu_econometrics",
      "task_alias": "econometrics",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "econometrics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_electrical_engineering": {
      "task": "mmlu_electrical_engineering",
      "task_alias": "electrical_engineering",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "electrical_engineering",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_elementary_mathematics": {
      "task": "mmlu_elementary_mathematics",
      "task_alias": "elementary_mathematics",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "elementary_mathematics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_formal_logic": {
      "task": "mmlu_formal_logic",
      "task_alias": "formal_logic",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "formal_logic",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_global_facts": {
      "task": "mmlu_global_facts",
      "task_alias": "global_facts",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "global_facts",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_biology": {
      "task": "mmlu_high_school_biology",
      "task_alias": "high_school_biology",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_biology",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_chemistry": {
      "task": "mmlu_high_school_chemistry",
      "task_alias": "high_school_chemistry",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_chemistry",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_computer_science": {
      "task": "mmlu_high_school_computer_science",
      "task_alias": "high_school_computer_science",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_computer_science",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_european_history": {
      "task": "mmlu_high_school_european_history",
      "task_alias": "high_school_european_history",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_european_history",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_geography": {
      "task": "mmlu_high_school_geography",
      "task_alias": "high_school_geography",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_geography",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_government_and_politics": {
      "task": "mmlu_high_school_government_and_politics",
      "task_alias": "high_school_government_and_politics",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_government_and_politics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_macroeconomics": {
      "task": "mmlu_high_school_macroeconomics",
      "task_alias": "high_school_macroeconomics",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_macroeconomics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_mathematics": {
      "task": "mmlu_high_school_mathematics",
      "task_alias": "high_school_mathematics",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_mathematics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_microeconomics": {
      "task": "mmlu_high_school_microeconomics",
      "task_alias": "high_school_microeconomics",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_microeconomics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_physics": {
      "task": "mmlu_high_school_physics",
      "task_alias": "high_school_physics",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_physics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_psychology": {
      "task": "mmlu_high_school_psychology",
      "task_alias": "high_school_psychology",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_psychology",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_statistics": {
      "task": "mmlu_high_school_statistics",
      "task_alias": "high_school_statistics",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_statistics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_us_history": {
      "task": "mmlu_high_school_us_history",
      "task_alias": "high_school_us_history",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_us_history",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_high_school_world_history": {
      "task": "mmlu_high_school_world_history",
      "task_alias": "high_school_world_history",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "high_school_world_history",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_human_aging": {
      "task": "mmlu_human_aging",
      "task_alias": "human_aging",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "human_aging",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_human_sexuality": {
      "task": "mmlu_human_sexuality",
      "task_alias": "human_sexuality",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "human_sexuality",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_international_law": {
      "task": "mmlu_international_law",
      "task_alias": "international_law",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "international_law",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_jurisprudence": {
      "task": "mmlu_jurisprudence",
      "task_alias": "jurisprudence",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "jurisprudence",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_logical_fallacies": {
      "task": "mmlu_logical_fallacies",
      "task_alias": "logical_fallacies",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "logical_fallacies",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_machine_learning": {
      "task": "mmlu_machine_learning",
      "task_alias": "machine_learning",
      "tag": "mmlu_stem_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "machine_learning",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_management": {
      "task": "mmlu_management",
      "task_alias": "management",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "management",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_marketing": {
      "task": "mmlu_marketing",
      "task_alias": "marketing",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "marketing",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_medical_genetics": {
      "task": "mmlu_medical_genetics",
      "task_alias": "medical_genetics",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "medical_genetics",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_miscellaneous": {
      "task": "mmlu_miscellaneous",
      "task_alias": "miscellaneous",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "miscellaneous",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_moral_disputes": {
      "task": "mmlu_moral_disputes",
      "task_alias": "moral_disputes",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "moral_disputes",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_moral_scenarios": {
      "task": "mmlu_moral_scenarios",
      "task_alias": "moral_scenarios",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "moral_scenarios",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_nutrition": {
      "task": "mmlu_nutrition",
      "task_alias": "nutrition",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "nutrition",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_philosophy": {
      "task": "mmlu_philosophy",
      "task_alias": "philosophy",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "philosophy",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_prehistory": {
      "task": "mmlu_prehistory",
      "task_alias": "prehistory",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "prehistory",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_professional_accounting": {
      "task": "mmlu_professional_accounting",
      "task_alias": "professional_accounting",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "professional_accounting",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_professional_law": {
      "task": "mmlu_professional_law",
      "task_alias": "professional_law",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "professional_law",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_professional_medicine": {
      "task": "mmlu_professional_medicine",
      "task_alias": "professional_medicine",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "professional_medicine",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_professional_psychology": {
      "task": "mmlu_professional_psychology",
      "task_alias": "professional_psychology",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "professional_psychology",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_public_relations": {
      "task": "mmlu_public_relations",
      "task_alias": "public_relations",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "public_relations",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_security_studies": {
      "task": "mmlu_security_studies",
      "task_alias": "security_studies",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "security_studies",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_sociology": {
      "task": "mmlu_sociology",
      "task_alias": "sociology",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "sociology",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_us_foreign_policy": {
      "task": "mmlu_us_foreign_policy",
      "task_alias": "us_foreign_policy",
      "tag": "mmlu_social_sciences_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "us_foreign_policy",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_virology": {
      "task": "mmlu_virology",
      "task_alias": "virology",
      "tag": "mmlu_other_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "virology",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    },
    "mmlu_world_religions": {
      "task": "mmlu_world_religions",
      "task_alias": "world_religions",
      "tag": "mmlu_humanities_tasks",
      "dataset_path": "cais/mmlu",
      "dataset_name": "world_religions",
      "dataset_kwargs": {
        "trust_remote_code": true
      },
      "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",
      "unsafe_code": false,
      "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": 0,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 1.0,
        "pretrained": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "tokenizer": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
        "max_gen_toks": 4096,
        "max_model_len": 8192,
        "enable_prefix_caching": true,
        "enable_chunked_prefill": true,
        "tensor_parallel_size": 8
      }
    }
  },
  "versions": {
    "ifeval": 4.0,
    "mmlu": 2,
    "mmlu_abstract_algebra": 1.0,
    "mmlu_anatomy": 1.0,
    "mmlu_astronomy": 1.0,
    "mmlu_business_ethics": 1.0,
    "mmlu_clinical_knowledge": 1.0,
    "mmlu_college_biology": 1.0,
    "mmlu_college_chemistry": 1.0,
    "mmlu_college_computer_science": 1.0,
    "mmlu_college_mathematics": 1.0,
    "mmlu_college_medicine": 1.0,
    "mmlu_college_physics": 1.0,
    "mmlu_computer_security": 1.0,
    "mmlu_conceptual_physics": 1.0,
    "mmlu_econometrics": 1.0,
    "mmlu_electrical_engineering": 1.0,
    "mmlu_elementary_mathematics": 1.0,
    "mmlu_formal_logic": 1.0,
    "mmlu_global_facts": 1.0,
    "mmlu_high_school_biology": 1.0,
    "mmlu_high_school_chemistry": 1.0,
    "mmlu_high_school_computer_science": 1.0,
    "mmlu_high_school_european_history": 1.0,
    "mmlu_high_school_geography": 1.0,
    "mmlu_high_school_government_and_politics": 1.0,
    "mmlu_high_school_macroeconomics": 1.0,
    "mmlu_high_school_mathematics": 1.0,
    "mmlu_high_school_microeconomics": 1.0,
    "mmlu_high_school_physics": 1.0,
    "mmlu_high_school_psychology": 1.0,
    "mmlu_high_school_statistics": 1.0,
    "mmlu_high_school_us_history": 1.0,
    "mmlu_high_school_world_history": 1.0,
    "mmlu_human_aging": 1.0,
    "mmlu_human_sexuality": 1.0,
    "mmlu_humanities": 2,
    "mmlu_international_law": 1.0,
    "mmlu_jurisprudence": 1.0,
    "mmlu_logical_fallacies": 1.0,
    "mmlu_machine_learning": 1.0,
    "mmlu_management": 1.0,
    "mmlu_marketing": 1.0,
    "mmlu_medical_genetics": 1.0,
    "mmlu_miscellaneous": 1.0,
    "mmlu_moral_disputes": 1.0,
    "mmlu_moral_scenarios": 1.0,
    "mmlu_nutrition": 1.0,
    "mmlu_other": 2,
    "mmlu_philosophy": 1.0,
    "mmlu_prehistory": 1.0,
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    },
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      "original": 100,
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    "mmlu_anatomy": {
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      "effective": 16
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    "mmlu_high_school_statistics": {
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    },
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      "original": 100,
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    },
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      "original": 102,
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    "mmlu_professional_accounting": {
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    "mmlu_miscellaneous": {
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      "effective": 16
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    "mmlu_marketing": {
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      "original": 100,
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    "mmlu_professional_medicine": {
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    },
    "mmlu_college_medicine": {
      "original": 173,
      "effective": 16
    },
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      "effective": 16
    },
    "mmlu_medical_genetics": {
      "original": 100,
      "effective": 16
    },
    "mmlu_clinical_knowledge": {
      "original": 265,
      "effective": 16
    },
    "mmlu_global_facts": {
      "original": 100,
      "effective": 16
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      "original": 103,
      "effective": 16
    },
    "mmlu_professional_psychology": {
      "original": 612,
      "effective": 16
    },
    "mmlu_high_school_psychology": {
      "original": 545,
      "effective": 16
    },
    "mmlu_econometrics": {
      "original": 114,
      "effective": 16
    },
    "mmlu_public_relations": {
      "original": 110,
      "effective": 16
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    "mmlu_us_foreign_policy": {
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      "effective": 16
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      "effective": 16
    },
    "mmlu_sociology": {
      "original": 201,
      "effective": 16
    },
    "mmlu_high_school_geography": {
      "original": 198,
      "effective": 16
    },
    "mmlu_high_school_government_and_politics": {
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    },
    "mmlu_security_studies": {
      "original": 245,
      "effective": 16
    },
    "mmlu_human_sexuality": {
      "original": 131,
      "effective": 16
    },
    "mmlu_moral_disputes": {
      "original": 346,
      "effective": 16
    },
    "mmlu_high_school_european_history": {
      "original": 165,
      "effective": 16
    },
    "mmlu_moral_scenarios": {
      "original": 895,
      "effective": 16
    },
    "mmlu_formal_logic": {
      "original": 126,
      "effective": 16
    },
    "mmlu_prehistory": {
      "original": 324,
      "effective": 16
    },
    "mmlu_professional_law": {
      "original": 1534,
      "effective": 16
    },
    "mmlu_world_religions": {
      "original": 171,
      "effective": 16
    },
    "mmlu_international_law": {
      "original": 121,
      "effective": 16
    },
    "mmlu_high_school_us_history": {
      "original": 204,
      "effective": 16
    },
    "mmlu_high_school_world_history": {
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      "effective": 16
    },
    "mmlu_logical_fallacies": {
      "original": 163,
      "effective": 16
    },
    "mmlu_jurisprudence": {
      "original": 108,
      "effective": 16
    },
    "mmlu_philosophy": {
      "original": 311,
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    "ifeval": {
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    "model": "vllm",
    "model_args": "pretrained=/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged,tokenizer=/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged,max_gen_toks=4096,max_model_len=8192,enable_prefix_caching=True,enable_chunked_prefill=True,tensor_parallel_size=8",
    "batch_size": "auto",
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    "device": null,
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    "limit": 16.0,
    "bootstrap_iters": 100000,
    "gen_kwargs": null,
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    "fewshot_seed": 1234
  },
  "git_hash": "ff41a85",
  "date": 1752425792.898692,
  "pretty_env_info": "PyTorch version: 2.7.0+cu126\nIs debug build: False\nCUDA used to build PyTorch: 12.6\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11.2.0] (64-bit runtime)\nPython platform: Linux-5.15.0-1053-nvidia-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 11.5.119\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: 535.161.08\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:                      43 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 7742 64-Core Processor\nCPU family:                         23\nModel:                              49\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           0\nFrequency boost:                    enabled\nCPU max MHz:                        2250.0000\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4491.75\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 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 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 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 avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es\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 (32 instances)\nNUMA node(s):                       8\nNUMA node0 CPU(s):                  0-15,128-143\nNUMA node1 CPU(s):                  16-31,144-159\nNUMA node2 CPU(s):                  32-47,160-175\nNUMA node3 CPU(s):                  48-63,176-191\nNUMA node4 CPU(s):                  64-79,192-207\nNUMA node5 CPU(s):                  80-95,208-223\nNUMA node6 CPU(s):                  96-111,224-239\nNUMA node7 CPU(s):                  112-127,240-255\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:             Mitigation; untrained return thunk; SMT enabled with STIBP protection\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, 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==2.2.6\n[pip3] nvidia-cublas-cu12==12.6.4.1\n[pip3] nvidia-cuda-cupti-cu12==12.6.80\n[pip3] nvidia-cuda-nvrtc-cu12==12.6.77\n[pip3] nvidia-cuda-runtime-cu12==12.6.77\n[pip3] nvidia-cudnn-cu12==9.5.1.17\n[pip3] nvidia-cufft-cu12==11.3.0.4\n[pip3] nvidia-curand-cu12==10.3.7.77\n[pip3] nvidia-cusolver-cu12==11.7.1.2\n[pip3] nvidia-cusparse-cu12==12.5.4.2\n[pip3] nvidia-cusparselt-cu12==0.6.3\n[pip3] nvidia-nccl-cu12==2.26.2\n[pip3] nvidia-nvjitlink-cu12==12.6.85\n[pip3] nvidia-nvtx-cu12==12.6.77\n[pip3] torch==2.7.0\n[pip3] torchaudio==2.7.0\n[pip3] torchvision==0.22.0\n[pip3] triton==3.3.0\n[conda] blas                      1.0                         mkl  \n[conda] cuda-cudart               12.1.105                      0    nvidia\n[conda] cuda-cupti                12.1.105                      0    nvidia\n[conda] cuda-libraries            12.1.0                        0    nvidia\n[conda] cuda-nvrtc                12.1.105                      0    nvidia\n[conda] cuda-nvtx                 12.1.105                      0    nvidia\n[conda] cuda-opencl               12.9.19                       0    nvidia\n[conda] cuda-runtime              12.1.0                        0    nvidia\n[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch\n[conda] libcublas                 12.1.0.26                     0    nvidia\n[conda] libcufft                  11.0.2.4                      0    nvidia\n[conda] libcurand                 10.3.10.19                    0    nvidia\n[conda] libcusolver               11.4.4.55                     0    nvidia\n[conda] libcusparse               12.0.2.55                     0    nvidia\n[conda] libjpeg-turbo             2.0.0                h9bf148f_0    pytorch\n[conda] libnvjitlink              12.1.105                      0    nvidia\n[conda] mkl                       2023.1.0         h213fc3f_46344  \n[conda] mkl-service               2.4.0           py311h5eee18b_2  \n[conda] mkl_fft                   1.3.11          py311h5eee18b_0  \n[conda] mkl_random                1.2.8           py311ha02d727_0  \n[conda] numpy                     1.26.4                   pypi_0    pypi\n[conda] nvidia-cublas-cu12        12.1.3.1                 pypi_0    pypi\n[conda] nvidia-cuda-cupti-cu12    12.1.105                 pypi_0    pypi\n[conda] nvidia-cuda-nvrtc-cu12    12.1.105                 pypi_0    pypi\n[conda] nvidia-cuda-runtime-cu12  12.1.105                 pypi_0    pypi\n[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi\n[conda] nvidia-cufft-cu12         11.0.2.54                pypi_0    pypi\n[conda] nvidia-curand-cu12        10.3.2.106               pypi_0    pypi\n[conda] nvidia-cusolver-cu12      11.4.5.107               pypi_0    pypi\n[conda] nvidia-cusparse-cu12      12.1.0.106               pypi_0    pypi\n[conda] nvidia-nccl-cu12          2.20.5                   pypi_0    pypi\n[conda] nvidia-nvjitlink-cu12     12.9.41                  pypi_0    pypi\n[conda] nvidia-nvtx-cu12          12.1.105                 pypi_0    pypi\n[conda] pytorch-cuda              12.1                 ha16c6d3_6    pytorch\n[conda] pytorch-mutex             1.0                        cuda    pytorch\n[conda] torch                     2.4.0                    pypi_0    pypi\n[conda] torchaudio                2.5.1               py311_cu121    pytorch\n[conda] torchvision               0.19.0                   pypi_0    pypi\n[conda] triton                    3.0.0                    pypi_0    pypi",
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  "max_length": 8192,
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  "model_source": "vllm",
  "model_name": "/home/dgxuser/workspace/Mango/axolotl/24B-Retrain/merged",
  "model_name_sanitized": "__home__dgxuser__workspace__Mango__axolotl__24B-Retrain__merged",
  "system_instruction": null,
  "system_instruction_sha": null,
  "fewshot_as_multiturn": true,
  "chat_template": "{%- set today = strftime_now(\"%Y-%m-%d\") %}\n{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris.\\nYour knowledge base was last updated on 2023-10-01. The current date is \" + today + \".\\n\\nWhen you're not sure about some information, you say that you don't have the information and don't make up anything.\\nIf the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. \\\"What are some good restaurants around me?\\\" => \\\"Where are you?\\\" or \\\"When is the next flight to Tokyo\\\" => \\\"Where do you travel from?\\\")\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n    {%- if messages[0]['content'] is string %}\n        {%- set system_message = messages[0]['content'] %}\n    {%- else %}\n        {%- set system_message = messages[0]['content'][0]['text'] %}\n    {%- endif %}\n    {%- set loop_messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = default_system_message %}\n    {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n    {%- if message['role'] == 'user' %}\n        {%- if message['content'] is string %}\n            {{- '[INST]' + message['content'] + '[/INST]' }}\n        {%- else %}\n            {{- '[INST]' }}\n            {%- for block in message['content'] %}\n                {%- if block['type'] == 'text' %}\n                    {{- block['text'] }}\n                {%- elif block['type'] in ['image', 'image_url'] %}\n                    {{- '[IMG]' }}\n                {%- else %}\n                    {{- raise_exception('Only text and image blocks are supported in message content!') }}\n                {%- endif %}\n            {%- endfor %}\n            {{- '[/INST]' }}\n        {%- endif %}\n    {%- elif message['role'] == 'system' %}\n        {%- if message['content'] is string %}\n            {{- '[SYSTEM_PROMPT]' + message['content'] + '[/SYSTEM_PROMPT]' }}\n        {%- else %}\n            {{- '[SYSTEM_PROMPT]' + message['content'][0]['text'] + '[/SYSTEM_PROMPT]' }}\n        {%- endif %}\n    {%- elif message['role'] == 'assistant' %}\n        {%- if message['content'] is string %}\n            {{- message['content'] + eos_token }}\n        {%- else %}\n            {{- message['content'][0]['text'] + eos_token }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Only user, system and assistant roles are supported!') }}\n    {%- endif %}\n{%- endfor %}",
  "chat_template_sha": "5f42291cf1b71a8eeae031eafd5bdc669586dbbbebba344a5d641322af152aa7",
  "start_time": 1331416.233509223,
  "end_time": 1331614.076114171,
  "total_evaluation_time_seconds": "197.8426049479749"
}