diff --git "a/results_2024-06-29T01-06-21.272851.json" "b/results_2024-06-29T01-06-21.272851.json"
deleted file mode 100644--- "a/results_2024-06-29T01-06-21.272851.json"
+++ /dev/null
@@ -1,4035 +0,0 @@
-{
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-    "mmlu": {
-      "acc,none": 0.6364477994587665,
-      "acc_stderr,none": 0.0038271694585367516,
-      "alias": " - mmlu"
-    },
-    "mmlu_humanities": {
-      "alias": "  - humanities",
-      "acc,none": 0.5895855472901169,
-      "acc_stderr,none": 0.006760272274548804
-    },
-    "mmlu_other": {
-      "alias": "  - other",
-      "acc,none": 0.7055037013196009,
-      "acc_stderr,none": 0.007845586852292294
-    },
-    "mmlu_social_sciences": {
-      "alias": "  - social_sciences",
-      "acc,none": 0.7432564185895353,
-      "acc_stderr,none": 0.007701333272557918
-    },
-    "mmlu_stem": {
-      "alias": "  - stem",
-      "acc,none": 0.5340945131620679,
-      "acc_stderr,none": 0.008514164103258936
-    },
-    "truthfulqa": {
-      "bleu_diff,none": 3.006407428437984,
-      "bleu_diff_stderr,none": 0.6902983955128965,
-      "bleu_max,none": 22.15536379157621,
-      "bleu_max_stderr,none": 0.7500703499499018,
-      "rouge2_max,none": 33.70863440140025,
-      "rouge2_max_stderr,none": 0.9588688279748141,
-      "rougeL_acc,none": 0.5128518971848225,
-      "rougeL_acc_stderr,none": 0.017497717944299843,
-      "rougeL_diff,none": 3.7826634155902985,
-      "rougeL_diff_stderr,none": 0.958164425989176,
-      "rouge1_acc,none": 0.5410036719706243,
-      "rouge1_acc_stderr,none": 0.017444544447661182,
-      "rouge1_max,none": 47.813085751155874,
-      "rouge1_max_stderr,none": 0.8351008973483007,
-      "rouge2_acc,none": 0.4541003671970624,
-      "rouge2_acc_stderr,none": 0.017429593091323504,
-      "bleu_acc,none": 0.5091799265605875,
-      "bleu_acc_stderr,none": 0.01750055072481974,
-      "rouge2_diff,none": 3.5225531232870635,
-      "rouge2_diff_stderr,none": 1.0505034205658943,
-      "rouge1_diff,none": 4.221115729669922,
-      "rouge1_diff_stderr,none": 0.9451610499576943,
-      "acc,none": 0.5182294709510535,
-      "acc_stderr,none": 0.011594047810301133,
-      "rougeL_max,none": 44.3329487904666,
-      "rougeL_max_stderr,none": 0.8588505055776223,
-      "alias": " - truthfulqa"
-    }
-  },
-  "group_subtasks": {
-    "eq_bench": [],
-    "truthfulqa": [
-      "truthfulqa_gen",
-      "truthfulqa_mc1",
-      "truthfulqa_mc2"
-    ],
-    "mmlu_stem": [
-      "mmlu_high_school_chemistry",
-      "mmlu_college_physics",
-      "mmlu_college_mathematics",
-      "mmlu_astronomy",
-      "mmlu_high_school_physics",
-      "mmlu_computer_security",
-      "mmlu_elementary_mathematics",
-      "mmlu_electrical_engineering",
-      "mmlu_college_biology",
-      "mmlu_machine_learning",
-      "mmlu_high_school_biology",
-      "mmlu_high_school_mathematics",
-      "mmlu_anatomy",
-      "mmlu_high_school_statistics",
-      "mmlu_college_chemistry",
-      "mmlu_conceptual_physics",
-      "mmlu_high_school_computer_science",
-      "mmlu_college_computer_science",
-      "mmlu_abstract_algebra"
-    ],
-    "mmlu_other": [
-      "mmlu_professional_medicine",
-      "mmlu_professional_accounting",
-      "mmlu_management",
-      "mmlu_global_facts",
-      "mmlu_college_medicine",
-      "mmlu_business_ethics",
-      "mmlu_nutrition",
-      "mmlu_medical_genetics",
-      "mmlu_virology",
-      "mmlu_human_aging",
-      "mmlu_clinical_knowledge",
-      "mmlu_miscellaneous",
-      "mmlu_marketing"
-    ],
-    "mmlu_social_sciences": [
-      "mmlu_high_school_psychology",
-      "mmlu_sociology",
-      "mmlu_high_school_government_and_politics",
-      "mmlu_public_relations",
-      "mmlu_high_school_macroeconomics",
-      "mmlu_high_school_geography",
-      "mmlu_high_school_microeconomics",
-      "mmlu_security_studies",
-      "mmlu_us_foreign_policy",
-      "mmlu_professional_psychology",
-      "mmlu_human_sexuality",
-      "mmlu_econometrics"
-    ],
-    "mmlu_humanities": [
-      "mmlu_high_school_european_history",
-      "mmlu_formal_logic",
-      "mmlu_moral_scenarios",
-      "mmlu_moral_disputes",
-      "mmlu_world_religions",
-      "mmlu_high_school_world_history",
-      "mmlu_logical_fallacies",
-      "mmlu_international_law",
-      "mmlu_philosophy",
-      "mmlu_professional_law",
-      "mmlu_high_school_us_history",
-      "mmlu_prehistory",
-      "mmlu_jurisprudence"
-    ],
-    "mmlu": [
-      "mmlu_humanities",
-      "mmlu_social_sciences",
-      "mmlu_other",
-      "mmlu_stem"
-    ],
-    "Open LLM Leaderboard": [
-      "gsm8k",
-      "winogrande",
-      "mmlu",
-      "truthfulqa",
-      "hellaswag",
-      "arc_challenge"
-    ]
-  },
-  "configs": {
-    "arc_challenge": {
-      "task": "arc_challenge",
-      "group": "Open LLM Leaderboard",
-      "dataset_path": "allenai/ai2_arc",
-      "dataset_name": "ARC-Challenge",
-      "training_split": "train",
-      "validation_split": "validation",
-      "test_split": "test",
-      "fewshot_split": "validation",
-      "doc_to_text": "Question: {{question}}\nAnswer:",
-      "doc_to_target": "{{choices.label.index(answerKey)}}",
-      "doc_to_choice": "{{choices.text}}",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 25,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "acc_norm",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "Question: {{question}}\nAnswer:",
-      "metadata": {
-        "version": 1.0
-      }
-    },
-    "eq_bench": {
-      "task": "eq_bench",
-      "dataset_path": "pbevan11/EQ-Bench",
-      "validation_split": "validation",
-      "doc_to_text": "prompt",
-      "doc_to_target": "reference_answer_fullscale",
-      "process_results": "def calculate_score_fullscale(docs, results):\n    reference = eval(docs[\"reference_answer_fullscale\"])\n    user = dict(re.findall(r\"(\\w+):\\s+(\\d+)\", results[0]))\n    # First check that the emotions specified in the answer match those in the reference\n    if len(user.items()) != 4:\n        # print('! Error: 4 emotions were not returned')\n        # print(user)\n        return {\"eqbench\": 0, \"percent_parseable\": 0}\n    emotions_dict = {}\n    for emotion, user_emotion_score in user.items():\n        for i in range(1, 5):\n            if emotion == reference[f\"emotion{i}\"]:\n                emotions_dict[emotion] = True\n    if len(emotions_dict) != 4:\n        print(\"! Error: emotions did not match reference\")\n        print(user)\n        return {\"eqbench\": 0, \"percent_parseable\": 0}\n\n    difference_tally = (\n        0  # Tally of differerence from reference answers for this question\n    )\n\n    # Iterate over each emotion in the user's answers.\n    for emotion, user_emotion_score in user.items():\n        # If this emotion is in the reference, calculate the difference between the user's score and the reference score.\n        for i in range(1, 5):\n            if emotion == reference[f\"emotion{i}\"]:\n                d = abs(\n                    float(user_emotion_score) - float(reference[f\"emotion{i}_score\"])\n                )\n                # this will be a value between 0 and 10\n                if d == 0:\n                    scaled_difference = 0\n                elif d <= 5:\n                    # S-shaped scaling function\n                    # https://www.desmos.com/calculator\n                    # 6.5\\cdot\\ \\frac{1}{\\left(1\\ +\\ e^{\\left(-1.2\\cdot\\left(x-4\\right)\\right)}\\right)}\n                    scaled_difference = 6.5 * (1 / (1 + math.e ** (-1.2 * (d - 4))))\n\n                else:\n                    scaled_difference = d\n                difference_tally += scaled_difference\n\n    # Inverting the difference tally so that the closer the answer is to reference, the higher the score.\n    # The adjustment constant is chosen such that answering randomly produces a score of zero.\n    adjust_const = 0.7477\n    final_score = 10 - (difference_tally * adjust_const)\n    final_score_percent = final_score * 10\n\n    return {\"eqbench\": final_score_percent, \"percent_parseable\": 100}\n",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 0,
-      "metric_list": [
-        {
-          "metric": "eqbench",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "percent_parseable",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "do_sample": false,
-        "temperature": 0.0,
-        "max_gen_toks": 80,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 2.1
-      }
-    },
-    "gsm8k": {
-      "task": "gsm8k",
-      "group": "Open LLM Leaderboard",
-      "dataset_path": "gsm8k",
-      "dataset_name": "main",
-      "training_split": "train",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Question: {{question}}\nAnswer:",
-      "doc_to_target": "{{answer}}",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "exact_match",
-          "aggregation": "mean",
-          "higher_is_better": true,
-          "ignore_case": true,
-          "ignore_punctuation": false,
-          "regexes_to_ignore": [
-            ",",
-            "\\$",
-            "(?s).*#### ",
-            "\\.$"
-          ]
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "until": [
-          "Question:",
-          "</s>",
-          "<|im_end|>"
-        ],
-        "do_sample": false,
-        "temperature": 0.0
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "strict-match",
-          "filter": [
-            {
-              "function": "regex",
-              "regex_pattern": "#### (\\-?[0-9\\.\\,]+)"
-            },
-            {
-              "function": "take_first"
-            }
-          ]
-        },
-        {
-          "name": "flexible-extract",
-          "filter": [
-            {
-              "function": "regex",
-              "group_select": -1,
-              "regex_pattern": "(-?[$0-9.,]{2,})|(-?[0-9]+)"
-            },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 3.0
-      }
-    },
-    "hellaswag": {
-      "task": "hellaswag",
-      "group": "Open LLM Leaderboard",
-      "dataset_path": "hellaswag",
-      "training_split": "train",
-      "validation_split": "validation",
-      "fewshot_split": "train",
-      "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n    def _process_doc(doc):\n        ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n        out_doc = {\n            \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n            \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n            \"gold\": int(doc[\"label\"]),\n        }\n        return out_doc\n\n    return dataset.map(_process_doc)\n",
-      "doc_to_text": "{{query}}",
-      "doc_to_target": "{{label}}",
-      "doc_to_choice": "choices",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 10,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "acc_norm",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.0
-      }
-    },
-    "mmlu_abstract_algebra": {
-      "task": "mmlu_abstract_algebra",
-      "task_alias": "abstract_algebra",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "abstract_algebra",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_anatomy": {
-      "task": "mmlu_anatomy",
-      "task_alias": "anatomy",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "anatomy",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_astronomy": {
-      "task": "mmlu_astronomy",
-      "task_alias": "astronomy",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "astronomy",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_business_ethics": {
-      "task": "mmlu_business_ethics",
-      "task_alias": "business_ethics",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "business_ethics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_clinical_knowledge": {
-      "task": "mmlu_clinical_knowledge",
-      "task_alias": "clinical_knowledge",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "clinical_knowledge",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_college_biology": {
-      "task": "mmlu_college_biology",
-      "task_alias": "college_biology",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "college_biology",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_college_chemistry": {
-      "task": "mmlu_college_chemistry",
-      "task_alias": "college_chemistry",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "college_chemistry",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_college_computer_science": {
-      "task": "mmlu_college_computer_science",
-      "task_alias": "college_computer_science",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "college_computer_science",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_college_mathematics": {
-      "task": "mmlu_college_mathematics",
-      "task_alias": "college_mathematics",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "college_mathematics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_college_medicine": {
-      "task": "mmlu_college_medicine",
-      "task_alias": "college_medicine",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "college_medicine",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_college_physics": {
-      "task": "mmlu_college_physics",
-      "task_alias": "college_physics",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "college_physics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_computer_security": {
-      "task": "mmlu_computer_security",
-      "task_alias": "computer_security",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "computer_security",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_conceptual_physics": {
-      "task": "mmlu_conceptual_physics",
-      "task_alias": "conceptual_physics",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "conceptual_physics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_econometrics": {
-      "task": "mmlu_econometrics",
-      "task_alias": "econometrics",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "econometrics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_electrical_engineering": {
-      "task": "mmlu_electrical_engineering",
-      "task_alias": "electrical_engineering",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "electrical_engineering",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_elementary_mathematics": {
-      "task": "mmlu_elementary_mathematics",
-      "task_alias": "elementary_mathematics",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "elementary_mathematics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_formal_logic": {
-      "task": "mmlu_formal_logic",
-      "task_alias": "formal_logic",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "formal_logic",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_global_facts": {
-      "task": "mmlu_global_facts",
-      "task_alias": "global_facts",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "global_facts",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_biology": {
-      "task": "mmlu_high_school_biology",
-      "task_alias": "high_school_biology",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_biology",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_chemistry": {
-      "task": "mmlu_high_school_chemistry",
-      "task_alias": "high_school_chemistry",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_chemistry",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_computer_science": {
-      "task": "mmlu_high_school_computer_science",
-      "task_alias": "high_school_computer_science",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_computer_science",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_european_history": {
-      "task": "mmlu_high_school_european_history",
-      "task_alias": "high_school_european_history",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_european_history",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_geography": {
-      "task": "mmlu_high_school_geography",
-      "task_alias": "high_school_geography",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_geography",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_government_and_politics": {
-      "task": "mmlu_high_school_government_and_politics",
-      "task_alias": "high_school_government_and_politics",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_government_and_politics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_macroeconomics": {
-      "task": "mmlu_high_school_macroeconomics",
-      "task_alias": "high_school_macroeconomics",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_macroeconomics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_mathematics": {
-      "task": "mmlu_high_school_mathematics",
-      "task_alias": "high_school_mathematics",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_mathematics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_microeconomics": {
-      "task": "mmlu_high_school_microeconomics",
-      "task_alias": "high_school_microeconomics",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_microeconomics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_physics": {
-      "task": "mmlu_high_school_physics",
-      "task_alias": "high_school_physics",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_physics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_psychology": {
-      "task": "mmlu_high_school_psychology",
-      "task_alias": "high_school_psychology",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_psychology",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_statistics": {
-      "task": "mmlu_high_school_statistics",
-      "task_alias": "high_school_statistics",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_statistics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_us_history": {
-      "task": "mmlu_high_school_us_history",
-      "task_alias": "high_school_us_history",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_us_history",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_high_school_world_history": {
-      "task": "mmlu_high_school_world_history",
-      "task_alias": "high_school_world_history",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "high_school_world_history",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_human_aging": {
-      "task": "mmlu_human_aging",
-      "task_alias": "human_aging",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "human_aging",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_human_sexuality": {
-      "task": "mmlu_human_sexuality",
-      "task_alias": "human_sexuality",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "human_sexuality",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_international_law": {
-      "task": "mmlu_international_law",
-      "task_alias": "international_law",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "international_law",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about international law.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_jurisprudence": {
-      "task": "mmlu_jurisprudence",
-      "task_alias": "jurisprudence",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "jurisprudence",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_logical_fallacies": {
-      "task": "mmlu_logical_fallacies",
-      "task_alias": "logical_fallacies",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "logical_fallacies",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_machine_learning": {
-      "task": "mmlu_machine_learning",
-      "task_alias": "machine_learning",
-      "group": "mmlu_stem",
-      "group_alias": "stem",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "machine_learning",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_management": {
-      "task": "mmlu_management",
-      "task_alias": "management",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "management",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about management.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_marketing": {
-      "task": "mmlu_marketing",
-      "task_alias": "marketing",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "marketing",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_medical_genetics": {
-      "task": "mmlu_medical_genetics",
-      "task_alias": "medical_genetics",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "medical_genetics",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_miscellaneous": {
-      "task": "mmlu_miscellaneous",
-      "task_alias": "miscellaneous",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "miscellaneous",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_moral_disputes": {
-      "task": "mmlu_moral_disputes",
-      "task_alias": "moral_disputes",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "moral_disputes",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_moral_scenarios": {
-      "task": "mmlu_moral_scenarios",
-      "task_alias": "moral_scenarios",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "moral_scenarios",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_nutrition": {
-      "task": "mmlu_nutrition",
-      "task_alias": "nutrition",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "nutrition",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_philosophy": {
-      "task": "mmlu_philosophy",
-      "task_alias": "philosophy",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "philosophy",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_prehistory": {
-      "task": "mmlu_prehistory",
-      "task_alias": "prehistory",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "prehistory",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_professional_accounting": {
-      "task": "mmlu_professional_accounting",
-      "task_alias": "professional_accounting",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "professional_accounting",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_professional_law": {
-      "task": "mmlu_professional_law",
-      "task_alias": "professional_law",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "professional_law",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_professional_medicine": {
-      "task": "mmlu_professional_medicine",
-      "task_alias": "professional_medicine",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "professional_medicine",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_professional_psychology": {
-      "task": "mmlu_professional_psychology",
-      "task_alias": "professional_psychology",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "professional_psychology",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_public_relations": {
-      "task": "mmlu_public_relations",
-      "task_alias": "public_relations",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "public_relations",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_security_studies": {
-      "task": "mmlu_security_studies",
-      "task_alias": "security_studies",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "security_studies",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_sociology": {
-      "task": "mmlu_sociology",
-      "task_alias": "sociology",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "sociology",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_us_foreign_policy": {
-      "task": "mmlu_us_foreign_policy",
-      "task_alias": "us_foreign_policy",
-      "group": "mmlu_social_sciences",
-      "group_alias": "social_sciences",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "us_foreign_policy",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_virology": {
-      "task": "mmlu_virology",
-      "task_alias": "virology",
-      "group": "mmlu_other",
-      "group_alias": "other",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "virology",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about virology.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "mmlu_world_religions": {
-      "task": "mmlu_world_religions",
-      "task_alias": "world_religions",
-      "group": "mmlu_humanities",
-      "group_alias": "humanities",
-      "dataset_path": "hails/mmlu_no_train",
-      "dataset_name": "world_religions",
-      "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",
-      "doc_to_choice": [
-        "A",
-        "B",
-        "C",
-        "D"
-      ],
-      "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "first_n"
-      },
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 0.0
-      }
-    },
-    "truthfulqa_gen": {
-      "task": "truthfulqa_gen",
-      "group": "truthfulqa",
-      "dataset_path": "truthful_qa",
-      "dataset_name": "generation",
-      "validation_split": "validation",
-      "process_docs": "def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset:\n    return dataset.map(preprocess_function)\n",
-      "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
-      "doc_to_target": " ",
-      "process_results": "def process_results_gen(doc, results):\n    completion = results[0]\n    true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n    all_refs = true_refs + false_refs\n\n    # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n    # # BLEURT\n    # bleurt_scores_true = self.bleurt.compute(\n    #     predictions=[completion] * len(true_refs), references=true_refs\n    # )[\"scores\"]\n    # bleurt_scores_false = self.bleurt.compute(\n    #     predictions=[completion] * len(false_refs), references=false_refs\n    # )[\"scores\"]\n    # bleurt_correct = max(bleurt_scores_true)\n    # bleurt_incorrect = max(bleurt_scores_false)\n    # bleurt_max = bleurt_correct\n    # bleurt_diff = bleurt_correct - bleurt_incorrect\n    # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n    # BLEU\n    bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n    bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n    bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n    bleu_max = bleu_correct\n    bleu_diff = bleu_correct - bleu_incorrect\n    bleu_acc = int(bleu_correct > bleu_incorrect)\n\n    # ROUGE-N\n    rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n    # ROUGE-1\n    rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n    rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n    rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n    rouge1_max = rouge1_correct\n    rouge1_diff = rouge1_correct - rouge1_incorrect\n    rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n    # ROUGE-2\n    rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n    rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n    rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n    rouge2_max = rouge2_correct\n    rouge2_diff = rouge2_correct - rouge2_incorrect\n    rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n    # ROUGE-L\n    rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n    rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n    rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n    rougeL_max = rougeL_correct\n    rougeL_diff = rougeL_correct - rougeL_incorrect\n    rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n    return {\n        # \"bleurt_max\": bleurt_max,\n        # \"bleurt_acc\": bleurt_acc,\n        # \"bleurt_diff\": bleurt_diff,\n        \"bleu_max\": bleu_max,\n        \"bleu_acc\": bleu_acc,\n        \"bleu_diff\": bleu_diff,\n        \"rouge1_max\": rouge1_max,\n        \"rouge1_acc\": rouge1_acc,\n        \"rouge1_diff\": rouge1_diff,\n        \"rouge2_max\": rouge2_max,\n        \"rouge2_acc\": rouge2_acc,\n        \"rouge2_diff\": rouge2_diff,\n        \"rougeL_max\": rougeL_max,\n        \"rougeL_acc\": rougeL_acc,\n        \"rougeL_diff\": rougeL_diff,\n    }\n",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 0,
-      "metric_list": [
-        {
-          "metric": "bleu_max",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "bleu_acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "bleu_diff",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rouge1_max",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rouge1_acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rouge1_diff",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rouge2_max",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rouge2_acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rouge2_diff",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rougeL_max",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rougeL_acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        },
-        {
-          "metric": "rougeL_diff",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "until": [
-          "\n\n"
-        ],
-        "do_sample": false
-      },
-      "repeats": 1,
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "question",
-      "metadata": {
-        "version": 3.0
-      }
-    },
-    "truthfulqa_mc1": {
-      "task": "truthfulqa_mc1",
-      "group": "truthfulqa",
-      "dataset_path": "truthful_qa",
-      "dataset_name": "multiple_choice",
-      "validation_split": "validation",
-      "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
-      "doc_to_target": 0,
-      "doc_to_choice": "{{mc1_targets.choices}}",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 0,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "question",
-      "metadata": {
-        "version": 2.0
-      }
-    },
-    "truthfulqa_mc2": {
-      "task": "truthfulqa_mc2",
-      "group": "truthfulqa",
-      "dataset_path": "truthful_qa",
-      "dataset_name": "multiple_choice",
-      "validation_split": "validation",
-      "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
-      "doc_to_target": 0,
-      "doc_to_choice": "{{mc2_targets.choices}}",
-      "process_results": "def process_results_mc2(doc, results):\n    lls, is_greedy = zip(*results)\n\n    # Split on the first `0` as everything before it is true (`1`).\n    split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n    # Compute the normalized probability mass for the correct answer.\n    ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n    p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n    p_true = p_true / (sum(p_true) + sum(p_false))\n\n    return {\"acc\": sum(p_true)}\n",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 0,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "question",
-      "metadata": {
-        "version": 2.0
-      }
-    },
-    "winogrande": {
-      "task": "winogrande",
-      "group": "Open LLM Leaderboard",
-      "dataset_path": "winogrande",
-      "dataset_name": "winogrande_xl",
-      "training_split": "train",
-      "validation_split": "validation",
-      "fewshot_split": "train",
-      "doc_to_text": "def doc_to_text(doc):\n    answer_to_num = {\"1\": 0, \"2\": 1}\n    return answer_to_num[doc[\"answer\"]]\n",
-      "doc_to_target": "def doc_to_target(doc):\n    idx = doc[\"sentence\"].index(\"_\") + 1\n    return doc[\"sentence\"][idx:].strip()\n",
-      "doc_to_choice": "def doc_to_choice(doc):\n    idx = doc[\"sentence\"].index(\"_\")\n    options = [doc[\"option1\"], doc[\"option2\"]]\n    return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 5,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "sentence",
-      "metadata": {
-        "version": 1.0
-      }
-    }
-  },
-  "versions": {
-    "arc_challenge": 1.0,
-    "eq_bench": 2.1,
-    "gsm8k": 3.0,
-    "hellaswag": 1.0,
-    "mmlu_abstract_algebra": 0.0,
-    "mmlu_anatomy": 0.0,
-    "mmlu_astronomy": 0.0,
-    "mmlu_business_ethics": 0.0,
-    "mmlu_clinical_knowledge": 0.0,
-    "mmlu_college_biology": 0.0,
-    "mmlu_college_chemistry": 0.0,
-    "mmlu_college_computer_science": 0.0,
-    "mmlu_college_mathematics": 0.0,
-    "mmlu_college_medicine": 0.0,
-    "mmlu_college_physics": 0.0,
-    "mmlu_computer_security": 0.0,
-    "mmlu_conceptual_physics": 0.0,
-    "mmlu_econometrics": 0.0,
-    "mmlu_electrical_engineering": 0.0,
-    "mmlu_elementary_mathematics": 0.0,
-    "mmlu_formal_logic": 0.0,
-    "mmlu_global_facts": 0.0,
-    "mmlu_high_school_biology": 0.0,
-    "mmlu_high_school_chemistry": 0.0,
-    "mmlu_high_school_computer_science": 0.0,
-    "mmlu_high_school_european_history": 0.0,
-    "mmlu_high_school_geography": 0.0,
-    "mmlu_high_school_government_and_politics": 0.0,
-    "mmlu_high_school_macroeconomics": 0.0,
-    "mmlu_high_school_mathematics": 0.0,
-    "mmlu_high_school_microeconomics": 0.0,
-    "mmlu_high_school_physics": 0.0,
-    "mmlu_high_school_psychology": 0.0,
-    "mmlu_high_school_statistics": 0.0,
-    "mmlu_high_school_us_history": 0.0,
-    "mmlu_high_school_world_history": 0.0,
-    "mmlu_human_aging": 0.0,
-    "mmlu_human_sexuality": 0.0,
-    "mmlu_international_law": 0.0,
-    "mmlu_jurisprudence": 0.0,
-    "mmlu_logical_fallacies": 0.0,
-    "mmlu_machine_learning": 0.0,
-    "mmlu_management": 0.0,
-    "mmlu_marketing": 0.0,
-    "mmlu_medical_genetics": 0.0,
-    "mmlu_miscellaneous": 0.0,
-    "mmlu_moral_disputes": 0.0,
-    "mmlu_moral_scenarios": 0.0,
-    "mmlu_nutrition": 0.0,
-    "mmlu_philosophy": 0.0,
-    "mmlu_prehistory": 0.0,
-    "mmlu_professional_accounting": 0.0,
-    "mmlu_professional_law": 0.0,
-    "mmlu_professional_medicine": 0.0,
-    "mmlu_professional_psychology": 0.0,
-    "mmlu_public_relations": 0.0,
-    "mmlu_security_studies": 0.0,
-    "mmlu_sociology": 0.0,
-    "mmlu_us_foreign_policy": 0.0,
-    "mmlu_virology": 0.0,
-    "mmlu_world_religions": 0.0,
-    "truthfulqa_gen": 3.0,
-    "truthfulqa_mc1": 2.0,
-    "truthfulqa_mc2": 2.0,
-    "winogrande": 1.0
-  },
-  "n-shot": {
-    "Open LLM Leaderboard": 5,
-    "arc_challenge": 25,
-    "eq_bench": 0,
-    "gsm8k": 5,
-    "hellaswag": 10,
-    "mmlu": 0,
-    "mmlu_abstract_algebra": 5,
-    "mmlu_anatomy": 5,
-    "mmlu_astronomy": 5,
-    "mmlu_business_ethics": 5,
-    "mmlu_clinical_knowledge": 5,
-    "mmlu_college_biology": 5,
-    "mmlu_college_chemistry": 5,
-    "mmlu_college_computer_science": 5,
-    "mmlu_college_mathematics": 5,
-    "mmlu_college_medicine": 5,
-    "mmlu_college_physics": 5,
-    "mmlu_computer_security": 5,
-    "mmlu_conceptual_physics": 5,
-    "mmlu_econometrics": 5,
-    "mmlu_electrical_engineering": 5,
-    "mmlu_elementary_mathematics": 5,
-    "mmlu_formal_logic": 5,
-    "mmlu_global_facts": 5,
-    "mmlu_high_school_biology": 5,
-    "mmlu_high_school_chemistry": 5,
-    "mmlu_high_school_computer_science": 5,
-    "mmlu_high_school_european_history": 5,
-    "mmlu_high_school_geography": 5,
-    "mmlu_high_school_government_and_politics": 5,
-    "mmlu_high_school_macroeconomics": 5,
-    "mmlu_high_school_mathematics": 5,
-    "mmlu_high_school_microeconomics": 5,
-    "mmlu_high_school_physics": 5,
-    "mmlu_high_school_psychology": 5,
-    "mmlu_high_school_statistics": 5,
-    "mmlu_high_school_us_history": 5,
-    "mmlu_high_school_world_history": 5,
-    "mmlu_human_aging": 5,
-    "mmlu_human_sexuality": 5,
-    "mmlu_humanities": 5,
-    "mmlu_international_law": 5,
-    "mmlu_jurisprudence": 5,
-    "mmlu_logical_fallacies": 5,
-    "mmlu_machine_learning": 5,
-    "mmlu_management": 5,
-    "mmlu_marketing": 5,
-    "mmlu_medical_genetics": 5,
-    "mmlu_miscellaneous": 5,
-    "mmlu_moral_disputes": 5,
-    "mmlu_moral_scenarios": 5,
-    "mmlu_nutrition": 5,
-    "mmlu_other": 5,
-    "mmlu_philosophy": 5,
-    "mmlu_prehistory": 5,
-    "mmlu_professional_accounting": 5,
-    "mmlu_professional_law": 5,
-    "mmlu_professional_medicine": 5,
-    "mmlu_professional_psychology": 5,
-    "mmlu_public_relations": 5,
-    "mmlu_security_studies": 5,
-    "mmlu_social_sciences": 5,
-    "mmlu_sociology": 5,
-    "mmlu_stem": 5,
-    "mmlu_us_foreign_policy": 5,
-    "mmlu_virology": 5,
-    "mmlu_world_religions": 5,
-    "truthfulqa": 0,
-    "truthfulqa_gen": 0,
-    "truthfulqa_mc1": 0,
-    "truthfulqa_mc2": 0,
-    "winogrande": 5
-  },
-  "higher_is_better": {
-    "Open LLM Leaderboard": {
-      "exact_match": true,
-      "acc": true,
-      "bleu_max": true,
-      "bleu_acc": true,
-      "bleu_diff": true,
-      "rouge1_max": true,
-      "rouge1_acc": true,
-      "rouge1_diff": true,
-      "rouge2_max": true,
-      "rouge2_acc": true,
-      "rouge2_diff": true,
-      "rougeL_max": true,
-      "rougeL_acc": true,
-      "rougeL_diff": true,
-      "acc_norm": true
-    },
-    "arc_challenge": {
-      "acc": true,
-      "acc_norm": true
-    },
-    "eq_bench": {
-      "eqbench": true,
-      "percent_parseable": true
-    },
-    "gsm8k": {
-      "exact_match": true
-    },
-    "hellaswag": {
-      "acc": true,
-      "acc_norm": true
-    },
-    "mmlu": {
-      "acc": true
-    },
-    "mmlu_abstract_algebra": {
-      "acc": true
-    },
-    "mmlu_anatomy": {
-      "acc": true
-    },
-    "mmlu_astronomy": {
-      "acc": true
-    },
-    "mmlu_business_ethics": {
-      "acc": true
-    },
-    "mmlu_clinical_knowledge": {
-      "acc": true
-    },
-    "mmlu_college_biology": {
-      "acc": true
-    },
-    "mmlu_college_chemistry": {
-      "acc": true
-    },
-    "mmlu_college_computer_science": {
-      "acc": true
-    },
-    "mmlu_college_mathematics": {
-      "acc": true
-    },
-    "mmlu_college_medicine": {
-      "acc": true
-    },
-    "mmlu_college_physics": {
-      "acc": true
-    },
-    "mmlu_computer_security": {
-      "acc": true
-    },
-    "mmlu_conceptual_physics": {
-      "acc": true
-    },
-    "mmlu_econometrics": {
-      "acc": true
-    },
-    "mmlu_electrical_engineering": {
-      "acc": true
-    },
-    "mmlu_elementary_mathematics": {
-      "acc": true
-    },
-    "mmlu_formal_logic": {
-      "acc": true
-    },
-    "mmlu_global_facts": {
-      "acc": true
-    },
-    "mmlu_high_school_biology": {
-      "acc": true
-    },
-    "mmlu_high_school_chemistry": {
-      "acc": true
-    },
-    "mmlu_high_school_computer_science": {
-      "acc": true
-    },
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-}
\ No newline at end of file