results_transfer/google-flan-t5-large_google-flan-ul2/bertattack_3_shot.json

[
    {
        "dataset": "cola",
        "type": "task",
        "origin_acc": 78.1,
        "origin_prompt": "Assess the following sentence and determine if it is grammatically correct. Respond with 'Acceptable' or 'Unacceptable'.",
        "atk_acc": 69.9,
        "atk_prompt": "Assess the following conversation and pick if it is grammatical: correct. interact with 'Acceptable' or 'Unacceptable'. ",
        "transfer_ori_acc": 86.1,
        "transfer_atk_acc": 87.0
    },
    {
        "dataset": "cola",
        "type": "role",
        "origin_acc": 75.8,
        "origin_prompt": "As an instrument for grammar evaluation, consider the sentence and determine if its grammar is correct, responding with 'acceptable' for correct grammar or 'unacceptable' for incorrect grammar.",
        "atk_acc": 69.2,
        "atk_prompt": "As an item for grammar acquisition, determine the conversation and determine if its grammar is okay, responding with 'acceptable' for normal grammar or 'unacceptable' for using spelling. ",
        "transfer_ori_acc": 86.0,
        "transfer_atk_acc": 86.2
    },
    {
        "dataset": "mrpc",
        "type": "task",
        "origin_acc": 82.6,
        "origin_prompt": "Can the given sentences be considered semantically identical? Please reply with 'equivalent' or 'not_equivalent'.",
        "atk_acc": 73.28,
        "atk_prompt": "can the given words be considered semantically adjacent? Please respond with 'equivalent' or 'not_equivalent'. ",
        "transfer_ori_acc": 87.00980392156863,
        "transfer_atk_acc": 85.04901960784314
    },
    {
        "dataset": "mrpc",
        "type": "role",
        "origin_acc": 81.37,
        "origin_prompt": "As a semantic comparison expert, evaluate the given pair of sentences and determine if they are 'equivalent' or 'not_equivalent'.",
        "atk_acc": 68.87,
        "atk_prompt": "As a grammatical compares professionals, find the given language of sentence and determine if they are 'equivalent' or 'not_equivalent'. ",
        "transfer_ori_acc": 85.04901960784314,
        "transfer_atk_acc": 86.02941176470588
    },
    {
        "dataset": "qnli",
        "type": "task",
        "origin_acc": 89.3,
        "origin_prompt": "Based on the provided context and question, decide if the information supports the answer by responding with 'entailment' or 'not_entailment'.",
        "atk_acc": 45.5,
        "atk_prompt": "from on the supplied context and questions, save if the information supports the answer by simply with 'entailment' or 'not_entailment'. ",
        "transfer_ori_acc": 94.5,
        "transfer_atk_acc": 92.5
    },
    {
        "dataset": "qnli",
        "type": "role",
        "origin_acc": 88.5,
        "origin_prompt": "In your role as a semantic evaluator, determine if the provided context justifies the answer to the question and answer with 'entailment' or 'not_entailment'.",
        "atk_acc": 40.6,
        "atk_prompt": "when your role as a semantic evaluator, be if the reference subject justmatches the answer to the answer and also with 'entailment' or 'not_entailment'. ",
        "transfer_ori_acc": 93.7,
        "transfer_atk_acc": 92.5
    },
    {
        "dataset": "qqp",
        "type": "task",
        "origin_acc": 88.1,
        "origin_prompt": "Are the following two questions equivalent or not? Answer me with \"equivalent\" or \"not_equivalent\".",
        "atk_acc": 82.5,
        "atk_prompt": "Are the so a equations equivalent or not? Answer me with \"equivalent\" or \"not_equivalent\". ",
        "transfer_ori_acc": 88.5,
        "transfer_atk_acc": 86.6
    },
    {
        "dataset": "qqp",
        "type": "role",
        "origin_acc": 86.5,
        "origin_prompt": "As an instrument for question comparison evaluation, consider the questions and determine if their meaning is the same, responding with 'equivalent' for similar questions or 'not_equivalent' for different questions.",
        "atk_acc": 63.9,
        "atk_prompt": "to an instrument for question ranking evaluation, consider the words and pick if their mood is the same, returning with 'equivalent' for analogous question or 'not_equivalent' for known questions. ",
        "transfer_ori_acc": 89.0,
        "transfer_atk_acc": 85.8
    },
    {
        "dataset": "rte",
        "type": "task",
        "origin_acc": 85.2,
        "origin_prompt": "Are the following two sentences entailment or not_entailment? Answer me with \"entailment\" or \"not_entailment\", just one word.",
        "atk_acc": 80.87,
        "atk_prompt": "can the is compare sentences entailment or not_entailment? Answer me with \"entailment\" or \"not_entailment\", just one word. ",
        "transfer_ori_acc": 93.14079422382672,
        "transfer_atk_acc": 93.50180505415162
    },
    {
        "dataset": "rte",
        "type": "role",
        "origin_acc": 84.12,
        "origin_prompt": "Acting as an entailment detection instrument, determine if the given pair of sentences demonstrates entailment or not_entailment. Answer with 'entailment' or 'not_entailment'.",
        "atk_acc": 78.7,
        "atk_prompt": "Acting as an entailment detection instrument, be if the given language of sentences does entailment or not_entailment. start with 'entailment' or 'not_entailment'. ",
        "transfer_ori_acc": 93.50180505415162,
        "transfer_atk_acc": 93.14079422382672
    },
    {
        "dataset": "sst2",
        "type": "task",
        "origin_acc": 95.3,
        "origin_prompt": "Considering the given phrase, would you say it carries a 'positive' or 'negative' connotation?",
        "atk_acc": 91.51,
        "atk_prompt": "given the verbal conjunction, who you say it implies a 'positive' or 'negative' connotation? ",
        "transfer_ori_acc": 95.64220183486239,
        "transfer_atk_acc": 95.75688073394495
    },
    {
        "dataset": "sst2",
        "type": "role",
        "origin_acc": 95.41,
        "origin_prompt": "Acting as a sentiment evaluator, identify if the given sentence is 'positive' or 'negative'.",
        "atk_acc": 92.43,
        "atk_prompt": "Acting as a positive evaluator, choose if the positive sentence is 'positive' or 'negative'. ",
        "transfer_ori_acc": 96.55963302752293,
        "transfer_atk_acc": 96.3302752293578
    },
    {
        "dataset": "wnli",
        "type": "task",
        "origin_acc": 64.79,
        "origin_prompt": "Assess the connection between the following sentences and classify it as 'entailment' or 'not_entailment'.",
        "atk_acc": 54.93,
        "atk_prompt": "Assess the connecting between the relevant sentences and classify it as 'entailment' or 'not_entailment'. ",
        "transfer_ori_acc": 76.05633802816901,
        "transfer_atk_acc": 77.46478873239437
    },
    {
        "dataset": "wnli",
        "type": "role",
        "origin_acc": 66.2,
        "origin_prompt": "Functioning as an entailment evaluation tool, analyze the provided sentences and decide if their relationship is 'entailment' or 'not_entailment'.",
        "atk_acc": 49.3,
        "atk_prompt": "Functioning as an entailment evaluation tool, analyze the generated sentences and place if their conversation is 'entailment' or 'not_entailment'. ",
        "transfer_ori_acc": 76.05633802816901,
        "transfer_atk_acc": 76.05633802816901
    },
    {
        "dataset": "mmlu",
        "type": "task",
        "origin_acc": 46.45,
        "origin_prompt": "For each multiple-choice question about {}, identify the correct answer by selecting 'A', 'B', 'C', or 'D'.",
        "atk_acc": 16.84,
        "atk_prompt": "For each multiple-. question about {}, reveal the incorrect ask by selecting 'A', 'B', 'C', or 'D'. ",
        "transfer_ori_acc": 53.191489361702125,
        "transfer_atk_acc": 13.47517730496454
    },
    {
        "dataset": "mmlu",
        "type": "role",
        "origin_acc": 46.99,
        "origin_prompt": "Considering your familiarity with {}, attend to the following multiple-choice question by picking 'A', 'B', 'C', or 'D'.",
        "atk_acc": 43.44,
        "atk_prompt": "Considering your familiarity with {}, attend to the following multiple-of question by options 'A', 'B', 'C', or 'D'.",
        "transfer_ori_acc": 54.43262411347518,
        "transfer_atk_acc": 54.07801418439716
    },
    {
        "dataset": "squad_v2",
        "type": "task",
        "origin_acc": 87.91,
        "origin_prompt": "From the context, provide the most precise answer. If the answer is not in the context, respond with 'unanswerable'.",
        "atk_acc": 73.79,
        "atk_prompt": "about the context, provide the most vague explanation. given the answered is not in the sentence, respond with 'unanswerable'.",
        "transfer_ori_acc": 89.38229949874687,
        "transfer_atk_acc": 87.54479949874688
    },
    {
        "dataset": "squad_v2",
        "type": "role",
        "origin_acc": 87.05,
        "origin_prompt": "As a subject matter expert, extract the correct answer from the context. If an answer is not present, indicate 'unanswerable'.",
        "atk_acc": 43.0,
        "atk_prompt": "provide a question ask specialist, extract the incorrect field from the context. If an answer is not present, indicate 'unanswerable'.",
        "transfer_ori_acc": 89.54896616541353,
        "transfer_atk_acc": 44.5
    },
    {
        "dataset": "iwslt",
        "type": "task",
        "origin_acc": 0.22,
        "origin_prompt": "Convert the following sentence from its original {} language to the target language {}.",
        "atk_acc": 0.21,
        "atk_prompt": "replace the this verb from its originally {} language to the target language {}. ",
        "transfer_ori_acc": 0.23981220411098694,
        "transfer_atk_acc": 0.2595100240921701
    },
    {
        "dataset": "iwslt",
        "type": "role",
        "origin_acc": 0.22,
        "origin_prompt": "As a qualified translator, convert the given sentence from its original {} language to the target language {}.",
        "atk_acc": 0.21,
        "atk_prompt": "form a qualified translator, manipulate the given example from its original {} languages to the target language {}. ",
        "transfer_ori_acc": 0.24717757056761575,
        "transfer_atk_acc": 0.23887038016867845
    },
    {
        "dataset": "un_multi",
        "type": "task",
        "origin_acc": 0.31,
        "origin_prompt": "Convert the following sentence from its original {} language to the target language {}.",
        "atk_acc": 0.3,
        "atk_prompt": "translate the second sentence from its original {} language to the target language {}. ",
        "transfer_ori_acc": 0.3527971649826467,
        "transfer_atk_acc": 0.3539811965525201
    },
    {
        "dataset": "un_multi",
        "type": "role",
        "origin_acc": 0.31,
        "origin_prompt": "As a qualified translator, convert the given sentence from its original {} language to the target language {}.",
        "atk_acc": 0.3,
        "atk_prompt": "As a trained translator, convert the given case from its original {} language to the project languages {}. ",
        "transfer_ori_acc": 0.35395992027011125,
        "transfer_atk_acc": 0.3539972812158635
    },
    {
        "dataset": "math",
        "type": "task",
        "origin_acc": 17.5,
        "origin_prompt": "Find the solution for this mathematical challenge with {}.",
        "atk_acc": 15.0,
        "atk_prompt": "Find the conclusion for this mathematical challenge with {}. ",
        "transfer_ori_acc": 15.625,
        "transfer_atk_acc": 16.25
    },
    {
        "dataset": "math",
        "type": "role",
        "origin_acc": 18.12,
        "origin_prompt": "Embodying a mathematics advisor, find the answer to the following math problem with {}.",
        "atk_acc": 9.38,
        "atk_prompt": "Embodying a mathematics advisor, find the subject to the such math item with {}. ",
        "transfer_ori_acc": 15.0,
        "transfer_atk_acc": 13.125
    }
]