| { |
| "results": { |
| "arc_challenge": { |
| "alias": "arc_challenge", |
| "acc,none": 0.20051194539249148, |
| "acc_stderr,none": 0.01170031805049937, |
| "acc_norm,none": 0.24232081911262798, |
| "acc_norm_stderr,none": 0.012521593295800115 |
| }, |
| "arc_easy": { |
| "alias": "arc_easy", |
| "acc,none": 0.2748316498316498, |
| "acc_stderr,none": 0.009160538115254942, |
| "acc_norm,none": 0.2849326599326599, |
| "acc_norm_stderr,none": 0.009262170695590658 |
| }, |
| "blimp": { |
| "acc,none": 0.5510895522388058, |
| "acc_stderr,none": 0.0016758550523395018, |
| "alias": "blimp" |
| }, |
| "blimp_adjunct_island": { |
| "alias": " - blimp_adjunct_island", |
| "acc,none": 0.672, |
| "acc_stderr,none": 0.014853842487270336 |
| }, |
| "blimp_anaphor_gender_agreement": { |
| "alias": " - blimp_anaphor_gender_agreement", |
| "acc,none": 0.281, |
| "acc_stderr,none": 0.01422115470843493 |
| }, |
| "blimp_anaphor_number_agreement": { |
| "alias": " - blimp_anaphor_number_agreement", |
| "acc,none": 0.457, |
| "acc_stderr,none": 0.01576069159013638 |
| }, |
| "blimp_animate_subject_passive": { |
| "alias": " - blimp_animate_subject_passive", |
| "acc,none": 0.617, |
| "acc_stderr,none": 0.015380102325652708 |
| }, |
| "blimp_animate_subject_trans": { |
| "alias": " - blimp_animate_subject_trans", |
| "acc,none": 0.791, |
| "acc_stderr,none": 0.012864077288499328 |
| }, |
| "blimp_causative": { |
| "alias": " - blimp_causative", |
| "acc,none": 0.42, |
| "acc_stderr,none": 0.015615500115072956 |
| }, |
| "blimp_complex_NP_island": { |
| "alias": " - blimp_complex_NP_island", |
| "acc,none": 0.464, |
| "acc_stderr,none": 0.015778243024904586 |
| }, |
| "blimp_coordinate_structure_constraint_complex_left_branch": { |
| "alias": " - blimp_coordinate_structure_constraint_complex_left_branch", |
| "acc,none": 0.145, |
| "acc_stderr,none": 0.011139977517890127 |
| }, |
| "blimp_coordinate_structure_constraint_object_extraction": { |
| "alias": " - blimp_coordinate_structure_constraint_object_extraction", |
| "acc,none": 0.578, |
| "acc_stderr,none": 0.015625625112620663 |
| }, |
| "blimp_determiner_noun_agreement_1": { |
| "alias": " - blimp_determiner_noun_agreement_1", |
| "acc,none": 0.602, |
| "acc_stderr,none": 0.01548663410285892 |
| }, |
| "blimp_determiner_noun_agreement_2": { |
| "alias": " - blimp_determiner_noun_agreement_2", |
| "acc,none": 0.527, |
| "acc_stderr,none": 0.015796218551302612 |
| }, |
| "blimp_determiner_noun_agreement_irregular_1": { |
| "alias": " - blimp_determiner_noun_agreement_irregular_1", |
| "acc,none": 0.54, |
| "acc_stderr,none": 0.015768596914394375 |
| }, |
| "blimp_determiner_noun_agreement_irregular_2": { |
| "alias": " - blimp_determiner_noun_agreement_irregular_2", |
| "acc,none": 0.568, |
| "acc_stderr,none": 0.015672320237336206 |
| }, |
| "blimp_determiner_noun_agreement_with_adj_2": { |
| "alias": " - blimp_determiner_noun_agreement_with_adj_2", |
| "acc,none": 0.483, |
| "acc_stderr,none": 0.015810153729833437 |
| }, |
| "blimp_determiner_noun_agreement_with_adj_irregular_1": { |
| "alias": " - blimp_determiner_noun_agreement_with_adj_irregular_1", |
| "acc,none": 0.467, |
| "acc_stderr,none": 0.015784807891138782 |
| }, |
| "blimp_determiner_noun_agreement_with_adj_irregular_2": { |
| "alias": " - blimp_determiner_noun_agreement_with_adj_irregular_2", |
| "acc,none": 0.533, |
| "acc_stderr,none": 0.015784807891138775 |
| }, |
| "blimp_determiner_noun_agreement_with_adjective_1": { |
| "alias": " - blimp_determiner_noun_agreement_with_adjective_1", |
| "acc,none": 0.516, |
| "acc_stderr,none": 0.015811198373114874 |
| }, |
| "blimp_distractor_agreement_relational_noun": { |
| "alias": " - blimp_distractor_agreement_relational_noun", |
| "acc,none": 0.286, |
| "acc_stderr,none": 0.01429714686251791 |
| }, |
| "blimp_distractor_agreement_relative_clause": { |
| "alias": " - blimp_distractor_agreement_relative_clause", |
| "acc,none": 0.327, |
| "acc_stderr,none": 0.014842213153411237 |
| }, |
| "blimp_drop_argument": { |
| "alias": " - blimp_drop_argument", |
| "acc,none": 0.696, |
| "acc_stderr,none": 0.014553205687950427 |
| }, |
| "blimp_ellipsis_n_bar_1": { |
| "alias": " - blimp_ellipsis_n_bar_1", |
| "acc,none": 0.208, |
| "acc_stderr,none": 0.01284137457209692 |
| }, |
| "blimp_ellipsis_n_bar_2": { |
| "alias": " - blimp_ellipsis_n_bar_2", |
| "acc,none": 0.369, |
| "acc_stderr,none": 0.015266698139154615 |
| }, |
| "blimp_existential_there_object_raising": { |
| "alias": " - blimp_existential_there_object_raising", |
| "acc,none": 0.781, |
| "acc_stderr,none": 0.013084731950262012 |
| }, |
| "blimp_existential_there_quantifiers_1": { |
| "alias": " - blimp_existential_there_quantifiers_1", |
| "acc,none": 0.764, |
| "acc_stderr,none": 0.013434451402438681 |
| }, |
| "blimp_existential_there_quantifiers_2": { |
| "alias": " - blimp_existential_there_quantifiers_2", |
| "acc,none": 0.076, |
| "acc_stderr,none": 0.008384169266796396 |
| }, |
| "blimp_existential_there_subject_raising": { |
| "alias": " - blimp_existential_there_subject_raising", |
| "acc,none": 0.526, |
| "acc_stderr,none": 0.015797897758042762 |
| }, |
| "blimp_expletive_it_object_raising": { |
| "alias": " - blimp_expletive_it_object_raising", |
| "acc,none": 0.7, |
| "acc_stderr,none": 0.014498627873361427 |
| }, |
| "blimp_inchoative": { |
| "alias": " - blimp_inchoative", |
| "acc,none": 0.395, |
| "acc_stderr,none": 0.015466551464829344 |
| }, |
| "blimp_intransitive": { |
| "alias": " - blimp_intransitive", |
| "acc,none": 0.558, |
| "acc_stderr,none": 0.015712507211864214 |
| }, |
| "blimp_irregular_past_participle_adjectives": { |
| "alias": " - blimp_irregular_past_participle_adjectives", |
| "acc,none": 0.782, |
| "acc_stderr,none": 0.013063179040595299 |
| }, |
| "blimp_irregular_past_participle_verbs": { |
| "alias": " - blimp_irregular_past_participle_verbs", |
| "acc,none": 0.696, |
| "acc_stderr,none": 0.014553205687950446 |
| }, |
| "blimp_irregular_plural_subject_verb_agreement_1": { |
| "alias": " - blimp_irregular_plural_subject_verb_agreement_1", |
| "acc,none": 0.594, |
| "acc_stderr,none": 0.015537226438634599 |
| }, |
| "blimp_irregular_plural_subject_verb_agreement_2": { |
| "alias": " - blimp_irregular_plural_subject_verb_agreement_2", |
| "acc,none": 0.584, |
| "acc_stderr,none": 0.015594460144140596 |
| }, |
| "blimp_left_branch_island_echo_question": { |
| "alias": " - blimp_left_branch_island_echo_question", |
| "acc,none": 0.73, |
| "acc_stderr,none": 0.014046255632633918 |
| }, |
| "blimp_left_branch_island_simple_question": { |
| "alias": " - blimp_left_branch_island_simple_question", |
| "acc,none": 0.267, |
| "acc_stderr,none": 0.013996674851796266 |
| }, |
| "blimp_matrix_question_npi_licensor_present": { |
| "alias": " - blimp_matrix_question_npi_licensor_present", |
| "acc,none": 0.022, |
| "acc_stderr,none": 0.004640855259274703 |
| }, |
| "blimp_npi_present_1": { |
| "alias": " - blimp_npi_present_1", |
| "acc,none": 0.46, |
| "acc_stderr,none": 0.015768596914394382 |
| }, |
| "blimp_npi_present_2": { |
| "alias": " - blimp_npi_present_2", |
| "acc,none": 0.436, |
| "acc_stderr,none": 0.015689173023144064 |
| }, |
| "blimp_only_npi_licensor_present": { |
| "alias": " - blimp_only_npi_licensor_present", |
| "acc,none": 0.976, |
| "acc_stderr,none": 0.004842256441727064 |
| }, |
| "blimp_only_npi_scope": { |
| "alias": " - blimp_only_npi_scope", |
| "acc,none": 0.555, |
| "acc_stderr,none": 0.01572330188676094 |
| }, |
| "blimp_passive_1": { |
| "alias": " - blimp_passive_1", |
| "acc,none": 0.759, |
| "acc_stderr,none": 0.013531522534515445 |
| }, |
| "blimp_passive_2": { |
| "alias": " - blimp_passive_2", |
| "acc,none": 0.627, |
| "acc_stderr,none": 0.015300493622922812 |
| }, |
| "blimp_principle_A_c_command": { |
| "alias": " - blimp_principle_A_c_command", |
| "acc,none": 0.617, |
| "acc_stderr,none": 0.015380102325652713 |
| }, |
| "blimp_principle_A_case_1": { |
| "alias": " - blimp_principle_A_case_1", |
| "acc,none": 1.0, |
| "acc_stderr,none": 0.0 |
| }, |
| "blimp_principle_A_case_2": { |
| "alias": " - blimp_principle_A_case_2", |
| "acc,none": 0.445, |
| "acc_stderr,none": 0.015723301886760934 |
| }, |
| "blimp_principle_A_domain_1": { |
| "alias": " - blimp_principle_A_domain_1", |
| "acc,none": 0.994, |
| "acc_stderr,none": 0.0024433521993298484 |
| }, |
| "blimp_principle_A_domain_2": { |
| "alias": " - blimp_principle_A_domain_2", |
| "acc,none": 0.591, |
| "acc_stderr,none": 0.015555094373257946 |
| }, |
| "blimp_principle_A_domain_3": { |
| "alias": " - blimp_principle_A_domain_3", |
| "acc,none": 0.51, |
| "acc_stderr,none": 0.015816135752773193 |
| }, |
| "blimp_principle_A_reconstruction": { |
| "alias": " - blimp_principle_A_reconstruction", |
| "acc,none": 0.413, |
| "acc_stderr,none": 0.015577986829936531 |
| }, |
| "blimp_regular_plural_subject_verb_agreement_1": { |
| "alias": " - blimp_regular_plural_subject_verb_agreement_1", |
| "acc,none": 0.567, |
| "acc_stderr,none": 0.01567663091218133 |
| }, |
| "blimp_regular_plural_subject_verb_agreement_2": { |
| "alias": " - blimp_regular_plural_subject_verb_agreement_2", |
| "acc,none": 0.585, |
| "acc_stderr,none": 0.01558903518560463 |
| }, |
| "blimp_sentential_negation_npi_licensor_present": { |
| "alias": " - blimp_sentential_negation_npi_licensor_present", |
| "acc,none": 0.99, |
| "acc_stderr,none": 0.0031480009386767663 |
| }, |
| "blimp_sentential_negation_npi_scope": { |
| "alias": " - blimp_sentential_negation_npi_scope", |
| "acc,none": 0.49, |
| "acc_stderr,none": 0.015816135752773203 |
| }, |
| "blimp_sentential_subject_island": { |
| "alias": " - blimp_sentential_subject_island", |
| "acc,none": 0.544, |
| "acc_stderr,none": 0.01575792855397917 |
| }, |
| "blimp_superlative_quantifiers_1": { |
| "alias": " - blimp_superlative_quantifiers_1", |
| "acc,none": 0.353, |
| "acc_stderr,none": 0.015120172605483711 |
| }, |
| "blimp_superlative_quantifiers_2": { |
| "alias": " - blimp_superlative_quantifiers_2", |
| "acc,none": 0.161, |
| "acc_stderr,none": 0.011628164696727181 |
| }, |
| "blimp_tough_vs_raising_1": { |
| "alias": " - blimp_tough_vs_raising_1", |
| "acc,none": 0.351, |
| "acc_stderr,none": 0.015100563798316405 |
| }, |
| "blimp_tough_vs_raising_2": { |
| "alias": " - blimp_tough_vs_raising_2", |
| "acc,none": 0.686, |
| "acc_stderr,none": 0.01468399195108797 |
| }, |
| "blimp_transitive": { |
| "alias": " - blimp_transitive", |
| "acc,none": 0.651, |
| "acc_stderr,none": 0.015080663991563109 |
| }, |
| "blimp_wh_island": { |
| "alias": " - blimp_wh_island", |
| "acc,none": 0.643, |
| "acc_stderr,none": 0.015158521721486774 |
| }, |
| "blimp_wh_questions_object_gap": { |
| "alias": " - blimp_wh_questions_object_gap", |
| "acc,none": 0.597, |
| "acc_stderr,none": 0.015518757419066529 |
| }, |
| "blimp_wh_questions_subject_gap": { |
| "alias": " - blimp_wh_questions_subject_gap", |
| "acc,none": 0.939, |
| "acc_stderr,none": 0.007572076091557422 |
| }, |
| "blimp_wh_questions_subject_gap_long_distance": { |
| "alias": " - blimp_wh_questions_subject_gap_long_distance", |
| "acc,none": 0.964, |
| "acc_stderr,none": 0.005893957816165543 |
| }, |
| "blimp_wh_vs_that_no_gap": { |
| "alias": " - blimp_wh_vs_that_no_gap", |
| "acc,none": 0.996, |
| "acc_stderr,none": 0.001996994739098729 |
| }, |
| "blimp_wh_vs_that_no_gap_long_distance": { |
| "alias": " - blimp_wh_vs_that_no_gap_long_distance", |
| "acc,none": 1.0, |
| "acc_stderr,none": 0.0 |
| }, |
| "blimp_wh_vs_that_with_gap": { |
| "alias": " - blimp_wh_vs_that_with_gap", |
| "acc,none": 0.0, |
| "acc_stderr,none": 0.0 |
| }, |
| "blimp_wh_vs_that_with_gap_long_distance": { |
| "alias": " - blimp_wh_vs_that_with_gap_long_distance", |
| "acc,none": 0.001, |
| "acc_stderr,none": 0.001000000000000003 |
| }, |
| "lambada_openai": { |
| "alias": "lambada_openai", |
| "perplexity,none": 705298.0654509069, |
| "perplexity_stderr,none": 50679.76677030163, |
| "acc,none": 0.0, |
| "acc_stderr,none": 0.0 |
| }, |
| "logiqa": { |
| "alias": "logiqa", |
| "acc,none": 0.20890937019969277, |
| "acc_stderr,none": 0.01594539939642392, |
| "acc_norm,none": 0.23195084485407066, |
| "acc_norm_stderr,none": 0.0165552524979259 |
| }, |
| "mmlu": { |
| "acc,none": 0.22952570858852014, |
| "acc_stderr,none": 0.0035430866300488776, |
| "alias": "mmlu" |
| }, |
| "mmlu_humanities": { |
| "acc,none": 0.24208289054197663, |
| "acc_stderr,none": 0.0062426684031394305, |
| "alias": " - humanities" |
| }, |
| "mmlu_formal_logic": { |
| "alias": " - formal_logic", |
| "acc,none": 0.2857142857142857, |
| "acc_stderr,none": 0.04040610178208841 |
| }, |
| "mmlu_high_school_european_history": { |
| "alias": " - high_school_european_history", |
| "acc,none": 0.21818181818181817, |
| "acc_stderr,none": 0.03225078108306289 |
| }, |
| "mmlu_high_school_us_history": { |
| "alias": " - high_school_us_history", |
| "acc,none": 0.25, |
| "acc_stderr,none": 0.03039153369274154 |
| }, |
| "mmlu_high_school_world_history": { |
| "alias": " - high_school_world_history", |
| "acc,none": 0.270042194092827, |
| "acc_stderr,none": 0.028900721906293426 |
| }, |
| "mmlu_international_law": { |
| "alias": " - international_law", |
| "acc,none": 0.2396694214876033, |
| "acc_stderr,none": 0.03896878985070417 |
| }, |
| "mmlu_jurisprudence": { |
| "alias": " - jurisprudence", |
| "acc,none": 0.25925925925925924, |
| "acc_stderr,none": 0.04236511258094634 |
| }, |
| "mmlu_logical_fallacies": { |
| "alias": " - logical_fallacies", |
| "acc,none": 0.22085889570552147, |
| "acc_stderr,none": 0.032591773927421776 |
| }, |
| "mmlu_moral_disputes": { |
| "alias": " - moral_disputes", |
| "acc,none": 0.24855491329479767, |
| "acc_stderr,none": 0.023267528432100174 |
| }, |
| "mmlu_moral_scenarios": { |
| "alias": " - moral_scenarios", |
| "acc,none": 0.23798882681564246, |
| "acc_stderr,none": 0.014242630070574885 |
| }, |
| "mmlu_philosophy": { |
| "alias": " - philosophy", |
| "acc,none": 0.1864951768488746, |
| "acc_stderr,none": 0.02212243977248077 |
| }, |
| "mmlu_prehistory": { |
| "alias": " - prehistory", |
| "acc,none": 0.21604938271604937, |
| "acc_stderr,none": 0.022899162918445813 |
| }, |
| "mmlu_professional_law": { |
| "alias": " - professional_law", |
| "acc,none": 0.2457627118644068, |
| "acc_stderr,none": 0.01099615663514269 |
| }, |
| "mmlu_world_religions": { |
| "alias": " - world_religions", |
| "acc,none": 0.3216374269005848, |
| "acc_stderr,none": 0.03582529442573122 |
| }, |
| "mmlu_other": { |
| "acc,none": 0.23978113936272932, |
| "acc_stderr,none": 0.00764225029165751, |
| "alias": " - other" |
| }, |
| "mmlu_business_ethics": { |
| "alias": " - business_ethics", |
| "acc,none": 0.3, |
| "acc_stderr,none": 0.046056618647183814 |
| }, |
| "mmlu_clinical_knowledge": { |
| "alias": " - clinical_knowledge", |
| "acc,none": 0.21509433962264152, |
| "acc_stderr,none": 0.025288394502891377 |
| }, |
| "mmlu_college_medicine": { |
| "alias": " - college_medicine", |
| "acc,none": 0.20809248554913296, |
| "acc_stderr,none": 0.030952890217749884 |
| }, |
| "mmlu_global_facts": { |
| "alias": " - global_facts", |
| "acc,none": 0.18, |
| "acc_stderr,none": 0.038612291966536955 |
| }, |
| "mmlu_human_aging": { |
| "alias": " - human_aging", |
| "acc,none": 0.31390134529147984, |
| "acc_stderr,none": 0.03114679648297246 |
| }, |
| "mmlu_management": { |
| "alias": " - management", |
| "acc,none": 0.17475728155339806, |
| "acc_stderr,none": 0.03760178006026621 |
| }, |
| "mmlu_marketing": { |
| "alias": " - marketing", |
| "acc,none": 0.2905982905982906, |
| "acc_stderr,none": 0.029745048572674057 |
| }, |
| "mmlu_medical_genetics": { |
| "alias": " - medical_genetics", |
| "acc,none": 0.3, |
| "acc_stderr,none": 0.046056618647183814 |
| }, |
| "mmlu_miscellaneous": { |
| "alias": " - miscellaneous", |
| "acc,none": 0.23754789272030652, |
| "acc_stderr,none": 0.015218733046150195 |
| }, |
| "mmlu_nutrition": { |
| "alias": " - nutrition", |
| "acc,none": 0.22549019607843138, |
| "acc_stderr,none": 0.023929155517351284 |
| }, |
| "mmlu_professional_accounting": { |
| "alias": " - professional_accounting", |
| "acc,none": 0.23404255319148937, |
| "acc_stderr,none": 0.025257861359432407 |
| }, |
| "mmlu_professional_medicine": { |
| "alias": " - professional_medicine", |
| "acc,none": 0.18382352941176472, |
| "acc_stderr,none": 0.02352924218519311 |
| }, |
| "mmlu_virology": { |
| "alias": " - virology", |
| "acc,none": 0.28313253012048195, |
| "acc_stderr,none": 0.03507295431370518 |
| }, |
| "mmlu_social_sciences": { |
| "acc,none": 0.2170945726356841, |
| "acc_stderr,none": 0.007428786285788534, |
| "alias": " - social sciences" |
| }, |
| "mmlu_econometrics": { |
| "alias": " - econometrics", |
| "acc,none": 0.23684210526315788, |
| "acc_stderr,none": 0.039994238792813386 |
| }, |
| "mmlu_high_school_geography": { |
| "alias": " - high_school_geography", |
| "acc,none": 0.17676767676767677, |
| "acc_stderr,none": 0.027178752639044915 |
| }, |
| "mmlu_high_school_government_and_politics": { |
| "alias": " - high_school_government_and_politics", |
| "acc,none": 0.19689119170984457, |
| "acc_stderr,none": 0.02869787397186069 |
| }, |
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| "wikitext": { |
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| "groups": { |
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| "mmlu": { |
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| "alias": "mmlu" |
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| }, |
| "group_subtasks": { |
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| "arc_challenge": [], |
| "blimp": [ |
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| "blimp_anaphor_gender_agreement", |
| "blimp_anaphor_number_agreement", |
| "blimp_animate_subject_passive", |
| "blimp_animate_subject_trans", |
| "blimp_causative", |
| "blimp_complex_NP_island", |
| "blimp_coordinate_structure_constraint_complex_left_branch", |
| "blimp_coordinate_structure_constraint_object_extraction", |
| "blimp_determiner_noun_agreement_1", |
| "blimp_determiner_noun_agreement_2", |
| "blimp_determiner_noun_agreement_irregular_1", |
| "blimp_determiner_noun_agreement_irregular_2", |
| "blimp_determiner_noun_agreement_with_adj_2", |
| "blimp_determiner_noun_agreement_with_adj_irregular_1", |
| "blimp_determiner_noun_agreement_with_adj_irregular_2", |
| "blimp_determiner_noun_agreement_with_adjective_1", |
| "blimp_distractor_agreement_relational_noun", |
| "blimp_distractor_agreement_relative_clause", |
| "blimp_drop_argument", |
| "blimp_ellipsis_n_bar_1", |
| "blimp_ellipsis_n_bar_2", |
| "blimp_existential_there_object_raising", |
| "blimp_existential_there_quantifiers_1", |
| "blimp_existential_there_quantifiers_2", |
| "blimp_existential_there_subject_raising", |
| "blimp_expletive_it_object_raising", |
| "blimp_inchoative", |
| "blimp_intransitive", |
| "blimp_irregular_past_participle_adjectives", |
| "blimp_irregular_past_participle_verbs", |
| "blimp_irregular_plural_subject_verb_agreement_1", |
| "blimp_irregular_plural_subject_verb_agreement_2", |
| "blimp_left_branch_island_echo_question", |
| "blimp_left_branch_island_simple_question", |
| "blimp_matrix_question_npi_licensor_present", |
| "blimp_npi_present_1", |
| "blimp_npi_present_2", |
| "blimp_only_npi_licensor_present", |
| "blimp_only_npi_scope", |
| "blimp_passive_1", |
| "blimp_passive_2", |
| "blimp_principle_A_c_command", |
| "blimp_principle_A_case_1", |
| "blimp_principle_A_case_2", |
| "blimp_principle_A_domain_1", |
| "blimp_principle_A_domain_2", |
| "blimp_principle_A_domain_3", |
| "blimp_principle_A_reconstruction", |
| "blimp_regular_plural_subject_verb_agreement_1", |
| "blimp_regular_plural_subject_verb_agreement_2", |
| "blimp_sentential_negation_npi_licensor_present", |
| "blimp_sentential_negation_npi_scope", |
| "blimp_sentential_subject_island", |
| "blimp_superlative_quantifiers_1", |
| "blimp_superlative_quantifiers_2", |
| "blimp_tough_vs_raising_1", |
| "blimp_tough_vs_raising_2", |
| "blimp_transitive", |
| "blimp_wh_island", |
| "blimp_wh_questions_object_gap", |
| "blimp_wh_questions_subject_gap", |
| "blimp_wh_questions_subject_gap_long_distance", |
| "blimp_wh_vs_that_no_gap", |
| "blimp_wh_vs_that_no_gap_long_distance", |
| "blimp_wh_vs_that_with_gap", |
| "blimp_wh_vs_that_with_gap_long_distance" |
| ], |
| "lambada_openai": [], |
| "logiqa": [], |
| "mmlu_humanities": [ |
| "mmlu_moral_disputes", |
| "mmlu_high_school_world_history", |
| "mmlu_jurisprudence", |
| "mmlu_philosophy", |
| "mmlu_high_school_us_history", |
| "mmlu_professional_law", |
| "mmlu_logical_fallacies", |
| "mmlu_moral_scenarios", |
| "mmlu_formal_logic", |
| "mmlu_prehistory", |
| "mmlu_high_school_european_history", |
| "mmlu_world_religions", |
| "mmlu_international_law" |
| ], |
| "mmlu_social_sciences": [ |
| "mmlu_us_foreign_policy", |
| "mmlu_sociology", |
| "mmlu_econometrics", |
| "mmlu_security_studies", |
| "mmlu_high_school_geography", |
| "mmlu_public_relations", |
| "mmlu_high_school_microeconomics", |
| "mmlu_professional_psychology", |
| "mmlu_high_school_macroeconomics", |
| "mmlu_human_sexuality", |
| "mmlu_high_school_government_and_politics", |
| "mmlu_high_school_psychology" |
| ], |
| "mmlu_other": [ |
| "mmlu_college_medicine", |
| "mmlu_medical_genetics", |
| "mmlu_business_ethics", |
| "mmlu_miscellaneous", |
| "mmlu_nutrition", |
| "mmlu_clinical_knowledge", |
| "mmlu_human_aging", |
| "mmlu_professional_accounting", |
| "mmlu_marketing", |
| "mmlu_global_facts", |
| "mmlu_professional_medicine", |
| "mmlu_virology", |
| "mmlu_management" |
| ], |
| "mmlu_stem": [ |
| "mmlu_elementary_mathematics", |
| "mmlu_electrical_engineering", |
| "mmlu_high_school_computer_science", |
| "mmlu_high_school_physics", |
| "mmlu_college_mathematics", |
| "mmlu_college_chemistry", |
| "mmlu_machine_learning", |
| "mmlu_high_school_mathematics", |
| "mmlu_computer_security", |
| "mmlu_conceptual_physics", |
| "mmlu_high_school_statistics", |
| "mmlu_high_school_biology", |
| "mmlu_astronomy", |
| "mmlu_college_computer_science", |
| "mmlu_college_biology", |
| "mmlu_college_physics", |
| "mmlu_anatomy", |
| "mmlu_high_school_chemistry", |
| "mmlu_abstract_algebra" |
| ], |
| "mmlu": [ |
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| "mmlu_social_sciences", |
| "mmlu_humanities" |
| ], |
| "piqa": [], |
| "sciq": [], |
| "wikitext": [], |
| "winogrande": [], |
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| }, |
| "configs": { |
| "arc_challenge": { |
| "task": "arc_challenge", |
| "tag": [ |
| "ai2_arc" |
| ], |
| "dataset_path": "allenai/ai2_arc", |
| "dataset_name": "ARC-Challenge", |
| "training_split": "train", |
| "validation_split": "validation", |
| "test_split": "test", |
| "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", |
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| "metric_list": [ |
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| "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": { |
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| }, |
| "arc_easy": { |
| "task": "arc_easy", |
| "tag": [ |
| "ai2_arc" |
| ], |
| "dataset_path": "allenai/ai2_arc", |
| "dataset_name": "ARC-Easy", |
| "training_split": "train", |
| "validation_split": "validation", |
| "test_split": "test", |
| "doc_to_text": "Question: {{question}}\nAnswer:", |
| "doc_to_target": "{{choices.label.index(answerKey)}}", |
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| "description": "", |
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| "fewshot_delimiter": "\n\n", |
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| "metric_list": [ |
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| "higher_is_better": true |
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| { |
| "metric": "acc_norm", |
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| "higher_is_better": true |
| } |
| ], |
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| "doc_to_decontamination_query": "Question: {{question}}\nAnswer:", |
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| }, |
| "blimp_adjunct_island": { |
| "task": "blimp_adjunct_island", |
| "dataset_path": "blimp", |
| "dataset_name": "adjunct_island", |
| "validation_split": "train", |
| "doc_to_text": "", |
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| "output_type": "multiple_choice", |
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| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
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| } |
| }, |
| "blimp_anaphor_gender_agreement": { |
| "task": "blimp_anaphor_gender_agreement", |
| "dataset_path": "blimp", |
| "dataset_name": "anaphor_gender_agreement", |
| "validation_split": "train", |
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| "output_type": "multiple_choice", |
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| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
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| }, |
| "blimp_anaphor_number_agreement": { |
| "task": "blimp_anaphor_number_agreement", |
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| "dataset_name": "anaphor_number_agreement", |
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| "blimp_animate_subject_passive": { |
| "task": "blimp_animate_subject_passive", |
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| "blimp_animate_subject_trans": { |
| "task": "blimp_animate_subject_trans", |
| "dataset_path": "blimp", |
| "dataset_name": "animate_subject_trans", |
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| "blimp_causative": { |
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| "dataset_name": "causative", |
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| "blimp_complex_NP_island": { |
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| "dataset_name": "complex_NP_island", |
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| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "blimp_wh_questions_object_gap": { |
| "task": "blimp_wh_questions_object_gap", |
| "dataset_path": "blimp", |
| "dataset_name": "wh_questions_object_gap", |
| "validation_split": "train", |
| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "blimp_wh_questions_subject_gap": { |
| "task": "blimp_wh_questions_subject_gap", |
| "dataset_path": "blimp", |
| "dataset_name": "wh_questions_subject_gap", |
| "validation_split": "train", |
| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "blimp_wh_questions_subject_gap_long_distance": { |
| "task": "blimp_wh_questions_subject_gap_long_distance", |
| "dataset_path": "blimp", |
| "dataset_name": "wh_questions_subject_gap_long_distance", |
| "validation_split": "train", |
| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "blimp_wh_vs_that_no_gap": { |
| "task": "blimp_wh_vs_that_no_gap", |
| "dataset_path": "blimp", |
| "dataset_name": "wh_vs_that_no_gap", |
| "validation_split": "train", |
| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "blimp_wh_vs_that_no_gap_long_distance": { |
| "task": "blimp_wh_vs_that_no_gap_long_distance", |
| "dataset_path": "blimp", |
| "dataset_name": "wh_vs_that_no_gap_long_distance", |
| "validation_split": "train", |
| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "blimp_wh_vs_that_with_gap": { |
| "task": "blimp_wh_vs_that_with_gap", |
| "dataset_path": "blimp", |
| "dataset_name": "wh_vs_that_with_gap", |
| "validation_split": "train", |
| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "blimp_wh_vs_that_with_gap_long_distance": { |
| "task": "blimp_wh_vs_that_with_gap_long_distance", |
| "dataset_path": "blimp", |
| "dataset_name": "wh_vs_that_with_gap_long_distance", |
| "validation_split": "train", |
| "doc_to_text": "", |
| "doc_to_target": 0, |
| "doc_to_choice": "{{[sentence_good, sentence_bad]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "lambada_openai": { |
| "task": "lambada_openai", |
| "tag": [ |
| "lambada" |
| ], |
| "dataset_path": "EleutherAI/lambada_openai", |
| "dataset_name": "default", |
| "dataset_kwargs": { |
| "trust_remote_code": true |
| }, |
| "test_split": "test", |
| "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", |
| "doc_to_target": "{{' '+text.split(' ')[-1]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "perplexity", |
| "aggregation": "perplexity", |
| "higher_is_better": false |
| }, |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "loglikelihood", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{text}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "logiqa": { |
| "task": "logiqa", |
| "dataset_path": "EleutherAI/logiqa", |
| "dataset_name": "logiqa", |
| "dataset_kwargs": { |
| "trust_remote_code": true |
| }, |
| "training_split": "train", |
| "validation_split": "validation", |
| "test_split": "test", |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: <passage>\n Question: <question>\n Choices:\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n", |
| "doc_to_target": "def doc_to_target(doc) -> int:\n choices = [\"a\", \"b\", \"c\", \"d\"]\n return choices.index(doc[\"label\"].strip())\n", |
| "doc_to_choice": "{{options}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "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": "{{context}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_abstract_algebra": { |
| "task": "mmlu_abstract_algebra", |
| "task_alias": "abstract_algebra", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_anatomy": { |
| "task": "mmlu_anatomy", |
| "task_alias": "anatomy", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_astronomy": { |
| "task": "mmlu_astronomy", |
| "task_alias": "astronomy", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_business_ethics": { |
| "task": "mmlu_business_ethics", |
| "task_alias": "business_ethics", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_clinical_knowledge": { |
| "task": "mmlu_clinical_knowledge", |
| "task_alias": "clinical_knowledge", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_college_biology": { |
| "task": "mmlu_college_biology", |
| "task_alias": "college_biology", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_college_chemistry": { |
| "task": "mmlu_college_chemistry", |
| "task_alias": "college_chemistry", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_college_computer_science": { |
| "task": "mmlu_college_computer_science", |
| "task_alias": "college_computer_science", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_college_mathematics": { |
| "task": "mmlu_college_mathematics", |
| "task_alias": "college_mathematics", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_college_medicine": { |
| "task": "mmlu_college_medicine", |
| "task_alias": "college_medicine", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_college_physics": { |
| "task": "mmlu_college_physics", |
| "task_alias": "college_physics", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_computer_security": { |
| "task": "mmlu_computer_security", |
| "task_alias": "computer_security", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_conceptual_physics": { |
| "task": "mmlu_conceptual_physics", |
| "task_alias": "conceptual_physics", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_econometrics": { |
| "task": "mmlu_econometrics", |
| "task_alias": "econometrics", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_electrical_engineering": { |
| "task": "mmlu_electrical_engineering", |
| "task_alias": "electrical_engineering", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_elementary_mathematics": { |
| "task": "mmlu_elementary_mathematics", |
| "task_alias": "elementary_mathematics", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_formal_logic": { |
| "task": "mmlu_formal_logic", |
| "task_alias": "formal_logic", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_global_facts": { |
| "task": "mmlu_global_facts", |
| "task_alias": "global_facts", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_biology": { |
| "task": "mmlu_high_school_biology", |
| "task_alias": "high_school_biology", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_chemistry": { |
| "task": "mmlu_high_school_chemistry", |
| "task_alias": "high_school_chemistry", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_computer_science": { |
| "task": "mmlu_high_school_computer_science", |
| "task_alias": "high_school_computer_science", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_european_history": { |
| "task": "mmlu_high_school_european_history", |
| "task_alias": "high_school_european_history", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_geography": { |
| "task": "mmlu_high_school_geography", |
| "task_alias": "high_school_geography", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_government_and_politics": { |
| "task": "mmlu_high_school_government_and_politics", |
| "task_alias": "high_school_government_and_politics", |
| "tag": "mmlu_social_sciences_tasks", |
| "dataset_path": "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_macroeconomics": { |
| "task": "mmlu_high_school_macroeconomics", |
| "task_alias": "high_school_macroeconomics", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_mathematics": { |
| "task": "mmlu_high_school_mathematics", |
| "task_alias": "high_school_mathematics", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_microeconomics": { |
| "task": "mmlu_high_school_microeconomics", |
| "task_alias": "high_school_microeconomics", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_physics": { |
| "task": "mmlu_high_school_physics", |
| "task_alias": "high_school_physics", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_psychology": { |
| "task": "mmlu_high_school_psychology", |
| "task_alias": "high_school_psychology", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_statistics": { |
| "task": "mmlu_high_school_statistics", |
| "task_alias": "high_school_statistics", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_us_history": { |
| "task": "mmlu_high_school_us_history", |
| "task_alias": "high_school_us_history", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_high_school_world_history": { |
| "task": "mmlu_high_school_world_history", |
| "task_alias": "high_school_world_history", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_human_aging": { |
| "task": "mmlu_human_aging", |
| "task_alias": "human_aging", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_human_sexuality": { |
| "task": "mmlu_human_sexuality", |
| "task_alias": "human_sexuality", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_international_law": { |
| "task": "mmlu_international_law", |
| "task_alias": "international_law", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_jurisprudence": { |
| "task": "mmlu_jurisprudence", |
| "task_alias": "jurisprudence", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_logical_fallacies": { |
| "task": "mmlu_logical_fallacies", |
| "task_alias": "logical_fallacies", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_machine_learning": { |
| "task": "mmlu_machine_learning", |
| "task_alias": "machine_learning", |
| "tag": "mmlu_stem_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_management": { |
| "task": "mmlu_management", |
| "task_alias": "management", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_marketing": { |
| "task": "mmlu_marketing", |
| "task_alias": "marketing", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_medical_genetics": { |
| "task": "mmlu_medical_genetics", |
| "task_alias": "medical_genetics", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_miscellaneous": { |
| "task": "mmlu_miscellaneous", |
| "task_alias": "miscellaneous", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_moral_disputes": { |
| "task": "mmlu_moral_disputes", |
| "task_alias": "moral_disputes", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_moral_scenarios": { |
| "task": "mmlu_moral_scenarios", |
| "task_alias": "moral_scenarios", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_nutrition": { |
| "task": "mmlu_nutrition", |
| "task_alias": "nutrition", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_philosophy": { |
| "task": "mmlu_philosophy", |
| "task_alias": "philosophy", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_prehistory": { |
| "task": "mmlu_prehistory", |
| "task_alias": "prehistory", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_professional_accounting": { |
| "task": "mmlu_professional_accounting", |
| "task_alias": "professional_accounting", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_professional_law": { |
| "task": "mmlu_professional_law", |
| "task_alias": "professional_law", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_professional_medicine": { |
| "task": "mmlu_professional_medicine", |
| "task_alias": "professional_medicine", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_professional_psychology": { |
| "task": "mmlu_professional_psychology", |
| "task_alias": "professional_psychology", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_public_relations": { |
| "task": "mmlu_public_relations", |
| "task_alias": "public_relations", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_security_studies": { |
| "task": "mmlu_security_studies", |
| "task_alias": "security_studies", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_sociology": { |
| "task": "mmlu_sociology", |
| "task_alias": "sociology", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_us_foreign_policy": { |
| "task": "mmlu_us_foreign_policy", |
| "task_alias": "us_foreign_policy", |
| "tag": "mmlu_social_sciences_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_virology": { |
| "task": "mmlu_virology", |
| "task_alias": "virology", |
| "tag": "mmlu_other_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "mmlu_world_religions": { |
| "task": "mmlu_world_religions", |
| "task_alias": "world_religions", |
| "tag": "mmlu_humanities_tasks", |
| "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": 0, |
| "metric_list": [ |
| { |
| "metric": "acc", |
| "aggregation": "mean", |
| "higher_is_better": true |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "piqa": { |
| "task": "piqa", |
| "dataset_path": "piqa", |
| "dataset_kwargs": { |
| "trust_remote_code": true |
| }, |
| "training_split": "train", |
| "validation_split": "validation", |
| "doc_to_text": "Question: {{goal}}\nAnswer:", |
| "doc_to_target": "label", |
| "doc_to_choice": "{{[sol1, sol2]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "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": "goal", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "sciq": { |
| "task": "sciq", |
| "dataset_path": "sciq", |
| "training_split": "train", |
| "validation_split": "validation", |
| "test_split": "test", |
| "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:", |
| "doc_to_target": 3, |
| "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "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": "{{support}} {{question}}", |
| "metadata": { |
| "version": 1.0 |
| } |
| }, |
| "wikitext": { |
| "task": "wikitext", |
| "dataset_path": "EleutherAI/wikitext_document_level", |
| "dataset_name": "wikitext-2-raw-v1", |
| "dataset_kwargs": { |
| "trust_remote_code": true |
| }, |
| "training_split": "train", |
| "validation_split": "validation", |
| "test_split": "test", |
| "doc_to_text": "", |
| "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n", |
| "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n", |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "word_perplexity" |
| }, |
| { |
| "metric": "byte_perplexity" |
| }, |
| { |
| "metric": "bits_per_byte" |
| } |
| ], |
| "output_type": "loglikelihood_rolling", |
| "repeats": 1, |
| "should_decontaminate": true, |
| "doc_to_decontamination_query": "{{page}}", |
| "metadata": { |
| "version": 2.0 |
| } |
| }, |
| "winogrande": { |
| "task": "winogrande", |
| "dataset_path": "winogrande", |
| "dataset_name": "winogrande_xl", |
| "dataset_kwargs": { |
| "trust_remote_code": true |
| }, |
| "training_split": "train", |
| "validation_split": "validation", |
| "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": 0, |
| "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 |
| } |
| }, |
| "wsc": { |
| "task": "wsc", |
| "tag": [ |
| "super-glue-lm-eval-v1" |
| ], |
| "dataset_path": "super_glue", |
| "dataset_name": "wsc.fixed", |
| "training_split": "train", |
| "validation_split": "validation", |
| "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n", |
| "doc_to_target": "label", |
| "doc_to_choice": [ |
| "no", |
| "yes" |
| ], |
| "description": "", |
| "target_delimiter": " ", |
| "fewshot_delimiter": "\n\n", |
| "num_fewshot": 0, |
| "metric_list": [ |
| { |
| "metric": "acc" |
| } |
| ], |
| "output_type": "multiple_choice", |
| "repeats": 1, |
| "should_decontaminate": false, |
| "metadata": { |
| "version": 1.0 |
| } |
| } |
| }, |
| "versions": { |
| "arc_challenge": 1.0, |
| "arc_easy": 1.0, |
| "blimp": 2.0, |
| "blimp_adjunct_island": 1.0, |
| "blimp_anaphor_gender_agreement": 1.0, |
| "blimp_anaphor_number_agreement": 1.0, |
| "blimp_animate_subject_passive": 1.0, |
| "blimp_animate_subject_trans": 1.0, |
| "blimp_causative": 1.0, |
| "blimp_complex_NP_island": 1.0, |
| "blimp_coordinate_structure_constraint_complex_left_branch": 1.0, |
| "blimp_coordinate_structure_constraint_object_extraction": 1.0, |
| "blimp_determiner_noun_agreement_1": 1.0, |
| "blimp_determiner_noun_agreement_2": 1.0, |
| "blimp_determiner_noun_agreement_irregular_1": 1.0, |
| "blimp_determiner_noun_agreement_irregular_2": 1.0, |
| "blimp_determiner_noun_agreement_with_adj_2": 1.0, |
| "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0, |
| "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0, |
| "blimp_determiner_noun_agreement_with_adjective_1": 1.0, |
| "blimp_distractor_agreement_relational_noun": 1.0, |
| "blimp_distractor_agreement_relative_clause": 1.0, |
| "blimp_drop_argument": 1.0, |
| "blimp_ellipsis_n_bar_1": 1.0, |
| "blimp_ellipsis_n_bar_2": 1.0, |
| "blimp_existential_there_object_raising": 1.0, |
| "blimp_existential_there_quantifiers_1": 1.0, |
| "blimp_existential_there_quantifiers_2": 1.0, |
| "blimp_existential_there_subject_raising": 1.0, |
| "blimp_expletive_it_object_raising": 1.0, |
| "blimp_inchoative": 1.0, |
| "blimp_intransitive": 1.0, |
| "blimp_irregular_past_participle_adjectives": 1.0, |
| "blimp_irregular_past_participle_verbs": 1.0, |
| "blimp_irregular_plural_subject_verb_agreement_1": 1.0, |
| "blimp_irregular_plural_subject_verb_agreement_2": 1.0, |
| "blimp_left_branch_island_echo_question": 1.0, |
| "blimp_left_branch_island_simple_question": 1.0, |
| "blimp_matrix_question_npi_licensor_present": 1.0, |
| "blimp_npi_present_1": 1.0, |
| "blimp_npi_present_2": 1.0, |
| "blimp_only_npi_licensor_present": 1.0, |
| "blimp_only_npi_scope": 1.0, |
| "blimp_passive_1": 1.0, |
| "blimp_passive_2": 1.0, |
| "blimp_principle_A_c_command": 1.0, |
| "blimp_principle_A_case_1": 1.0, |
| "blimp_principle_A_case_2": 1.0, |
| "blimp_principle_A_domain_1": 1.0, |
| "blimp_principle_A_domain_2": 1.0, |
| "blimp_principle_A_domain_3": 1.0, |
| "blimp_principle_A_reconstruction": 1.0, |
| "blimp_regular_plural_subject_verb_agreement_1": 1.0, |
| "blimp_regular_plural_subject_verb_agreement_2": 1.0, |
| "blimp_sentential_negation_npi_licensor_present": 1.0, |
| "blimp_sentential_negation_npi_scope": 1.0, |
| "blimp_sentential_subject_island": 1.0, |
| "blimp_superlative_quantifiers_1": 1.0, |
| "blimp_superlative_quantifiers_2": 1.0, |
| "blimp_tough_vs_raising_1": 1.0, |
| "blimp_tough_vs_raising_2": 1.0, |
| "blimp_transitive": 1.0, |
| "blimp_wh_island": 1.0, |
| "blimp_wh_questions_object_gap": 1.0, |
| "blimp_wh_questions_subject_gap": 1.0, |
| "blimp_wh_questions_subject_gap_long_distance": 1.0, |
| "blimp_wh_vs_that_no_gap": 1.0, |
| "blimp_wh_vs_that_no_gap_long_distance": 1.0, |
| "blimp_wh_vs_that_with_gap": 1.0, |
| "blimp_wh_vs_that_with_gap_long_distance": 1.0, |
| "lambada_openai": 1.0, |
| "logiqa": 1.0, |
| "mmlu": 2, |
| "mmlu_abstract_algebra": 1.0, |
| "mmlu_anatomy": 1.0, |
| "mmlu_astronomy": 1.0, |
| "mmlu_business_ethics": 1.0, |
| "mmlu_clinical_knowledge": 1.0, |
| "mmlu_college_biology": 1.0, |
| "mmlu_college_chemistry": 1.0, |
| "mmlu_college_computer_science": 1.0, |
| "mmlu_college_mathematics": 1.0, |
| "mmlu_college_medicine": 1.0, |
| "mmlu_college_physics": 1.0, |
| "mmlu_computer_security": 1.0, |
| "mmlu_conceptual_physics": 1.0, |
| "mmlu_econometrics": 1.0, |
| "mmlu_electrical_engineering": 1.0, |
| "mmlu_elementary_mathematics": 1.0, |
| "mmlu_formal_logic": 1.0, |
| "mmlu_global_facts": 1.0, |
| "mmlu_high_school_biology": 1.0, |
| "mmlu_high_school_chemistry": 1.0, |
| "mmlu_high_school_computer_science": 1.0, |
| "mmlu_high_school_european_history": 1.0, |
| "mmlu_high_school_geography": 1.0, |
| "mmlu_high_school_government_and_politics": 1.0, |
| "mmlu_high_school_macroeconomics": 1.0, |
| "mmlu_high_school_mathematics": 1.0, |
| "mmlu_high_school_microeconomics": 1.0, |
| "mmlu_high_school_physics": 1.0, |
| "mmlu_high_school_psychology": 1.0, |
| "mmlu_high_school_statistics": 1.0, |
| "mmlu_high_school_us_history": 1.0, |
| "mmlu_high_school_world_history": 1.0, |
| "mmlu_human_aging": 1.0, |
| "mmlu_human_sexuality": 1.0, |
| "mmlu_humanities": 2, |
| "mmlu_international_law": 1.0, |
| "mmlu_jurisprudence": 1.0, |
| "mmlu_logical_fallacies": 1.0, |
| "mmlu_machine_learning": 1.0, |
| "mmlu_management": 1.0, |
| "mmlu_marketing": 1.0, |
| "mmlu_medical_genetics": 1.0, |
| "mmlu_miscellaneous": 1.0, |
| "mmlu_moral_disputes": 1.0, |
| "mmlu_moral_scenarios": 1.0, |
| "mmlu_nutrition": 1.0, |
| "mmlu_other": 2, |
| "mmlu_philosophy": 1.0, |
| "mmlu_prehistory": 1.0, |
| "mmlu_professional_accounting": 1.0, |
| "mmlu_professional_law": 1.0, |
| "mmlu_professional_medicine": 1.0, |
| "mmlu_professional_psychology": 1.0, |
| "mmlu_public_relations": 1.0, |
| "mmlu_security_studies": 1.0, |
| "mmlu_social_sciences": 2, |
| "mmlu_sociology": 1.0, |
| "mmlu_stem": 2, |
| "mmlu_us_foreign_policy": 1.0, |
| "mmlu_virology": 1.0, |
| "mmlu_world_religions": 1.0, |
| "piqa": 1.0, |
| "sciq": 1.0, |
| "wikitext": 2.0, |
| "winogrande": 1.0, |
| "wsc": 1.0 |
| }, |
| "n-shot": { |
| "arc_challenge": 0, |
| "arc_easy": 0, |
| "blimp_adjunct_island": 0, |
| "blimp_anaphor_gender_agreement": 0, |
| "blimp_anaphor_number_agreement": 0, |
| "blimp_animate_subject_passive": 0, |
| "blimp_animate_subject_trans": 0, |
| "blimp_causative": 0, |
| "blimp_complex_NP_island": 0, |
| "blimp_coordinate_structure_constraint_complex_left_branch": 0, |
| "blimp_coordinate_structure_constraint_object_extraction": 0, |
| "blimp_determiner_noun_agreement_1": 0, |
| "blimp_determiner_noun_agreement_2": 0, |
| "blimp_determiner_noun_agreement_irregular_1": 0, |
| "blimp_determiner_noun_agreement_irregular_2": 0, |
| "blimp_determiner_noun_agreement_with_adj_2": 0, |
| "blimp_determiner_noun_agreement_with_adj_irregular_1": 0, |
| "blimp_determiner_noun_agreement_with_adj_irregular_2": 0, |
| "blimp_determiner_noun_agreement_with_adjective_1": 0, |
| "blimp_distractor_agreement_relational_noun": 0, |
| "blimp_distractor_agreement_relative_clause": 0, |
| "blimp_drop_argument": 0, |
| "blimp_ellipsis_n_bar_1": 0, |
| "blimp_ellipsis_n_bar_2": 0, |
| "blimp_existential_there_object_raising": 0, |
| "blimp_existential_there_quantifiers_1": 0, |
| "blimp_existential_there_quantifiers_2": 0, |
| "blimp_existential_there_subject_raising": 0, |
| "blimp_expletive_it_object_raising": 0, |
| "blimp_inchoative": 0, |
| "blimp_intransitive": 0, |
| "blimp_irregular_past_participle_adjectives": 0, |
| "blimp_irregular_past_participle_verbs": 0, |
| "blimp_irregular_plural_subject_verb_agreement_1": 0, |
| "blimp_irregular_plural_subject_verb_agreement_2": 0, |
| "blimp_left_branch_island_echo_question": 0, |
| "blimp_left_branch_island_simple_question": 0, |
| "blimp_matrix_question_npi_licensor_present": 0, |
| "blimp_npi_present_1": 0, |
| "blimp_npi_present_2": 0, |
| "blimp_only_npi_licensor_present": 0, |
| "blimp_only_npi_scope": 0, |
| "blimp_passive_1": 0, |
| "blimp_passive_2": 0, |
| "blimp_principle_A_c_command": 0, |
| "blimp_principle_A_case_1": 0, |
| "blimp_principle_A_case_2": 0, |
| "blimp_principle_A_domain_1": 0, |
| "blimp_principle_A_domain_2": 0, |
| "blimp_principle_A_domain_3": 0, |
| "blimp_principle_A_reconstruction": 0, |
| "blimp_regular_plural_subject_verb_agreement_1": 0, |
| "blimp_regular_plural_subject_verb_agreement_2": 0, |
| "blimp_sentential_negation_npi_licensor_present": 0, |
| "blimp_sentential_negation_npi_scope": 0, |
| "blimp_sentential_subject_island": 0, |
| "blimp_superlative_quantifiers_1": 0, |
| "blimp_superlative_quantifiers_2": 0, |
| "blimp_tough_vs_raising_1": 0, |
| "blimp_tough_vs_raising_2": 0, |
| "blimp_transitive": 0, |
| "blimp_wh_island": 0, |
| "blimp_wh_questions_object_gap": 0, |
| "blimp_wh_questions_subject_gap": 0, |
| "blimp_wh_questions_subject_gap_long_distance": 0, |
| "blimp_wh_vs_that_no_gap": 0, |
| "blimp_wh_vs_that_no_gap_long_distance": 0, |
| "blimp_wh_vs_that_with_gap": 0, |
| "blimp_wh_vs_that_with_gap_long_distance": 0, |
| "lambada_openai": 0, |
| "logiqa": 0, |
| "mmlu_abstract_algebra": 0, |
| "mmlu_anatomy": 0, |
| "mmlu_astronomy": 0, |
| "mmlu_business_ethics": 0, |
| "mmlu_clinical_knowledge": 0, |
| "mmlu_college_biology": 0, |
| "mmlu_college_chemistry": 0, |
| "mmlu_college_computer_science": 0, |
| "mmlu_college_mathematics": 0, |
| "mmlu_college_medicine": 0, |
| "mmlu_college_physics": 0, |
| "mmlu_computer_security": 0, |
| "mmlu_conceptual_physics": 0, |
| "mmlu_econometrics": 0, |
| "mmlu_electrical_engineering": 0, |
| "mmlu_elementary_mathematics": 0, |
| "mmlu_formal_logic": 0, |
| "mmlu_global_facts": 0, |
| "mmlu_high_school_biology": 0, |
| "mmlu_high_school_chemistry": 0, |
| "mmlu_high_school_computer_science": 0, |
| "mmlu_high_school_european_history": 0, |
| "mmlu_high_school_geography": 0, |
| "mmlu_high_school_government_and_politics": 0, |
| "mmlu_high_school_macroeconomics": 0, |
| "mmlu_high_school_mathematics": 0, |
| "mmlu_high_school_microeconomics": 0, |
| "mmlu_high_school_physics": 0, |
| "mmlu_high_school_psychology": 0, |
| "mmlu_high_school_statistics": 0, |
| "mmlu_high_school_us_history": 0, |
| "mmlu_high_school_world_history": 0, |
| "mmlu_human_aging": 0, |
| "mmlu_human_sexuality": 0, |
| "mmlu_international_law": 0, |
| "mmlu_jurisprudence": 0, |
| "mmlu_logical_fallacies": 0, |
| "mmlu_machine_learning": 0, |
| "mmlu_management": 0, |
| "mmlu_marketing": 0, |
| "mmlu_medical_genetics": 0, |
| "mmlu_miscellaneous": 0, |
| "mmlu_moral_disputes": 0, |
| "mmlu_moral_scenarios": 0, |
| "mmlu_nutrition": 0, |
| "mmlu_philosophy": 0, |
| "mmlu_prehistory": 0, |
| "mmlu_professional_accounting": 0, |
| "mmlu_professional_law": 0, |
| "mmlu_professional_medicine": 0, |
| "mmlu_professional_psychology": 0, |
| "mmlu_public_relations": 0, |
| "mmlu_security_studies": 0, |
| "mmlu_sociology": 0, |
| "mmlu_us_foreign_policy": 0, |
| "mmlu_virology": 0, |
| "mmlu_world_religions": 0, |
| "piqa": 0, |
| "sciq": 0, |
| "wikitext": 0, |
| "winogrande": 0, |
| "wsc": 0 |
| }, |
| "higher_is_better": { |
| "arc_challenge": { |
| "acc": true, |
| "acc_norm": true |
| }, |
| "arc_easy": { |
| "acc": true, |
| "acc_norm": true |
| }, |
| "blimp": { |
| "acc": true |
| }, |
| "blimp_adjunct_island": { |
| "acc": true |
| }, |
| "blimp_anaphor_gender_agreement": { |
| "acc": true |
| }, |
| "blimp_anaphor_number_agreement": { |
| "acc": true |
| }, |
| "blimp_animate_subject_passive": { |
| "acc": true |
| }, |
| "blimp_animate_subject_trans": { |
| "acc": true |
| }, |
| "blimp_causative": { |
| "acc": true |
| }, |
| "blimp_complex_NP_island": { |
| "acc": true |
| }, |
| "blimp_coordinate_structure_constraint_complex_left_branch": { |
| "acc": true |
| }, |
| "blimp_coordinate_structure_constraint_object_extraction": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_1": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_2": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_irregular_1": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_irregular_2": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_with_adj_2": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_with_adj_irregular_1": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_with_adj_irregular_2": { |
| "acc": true |
| }, |
| "blimp_determiner_noun_agreement_with_adjective_1": { |
| "acc": true |
| }, |
| "blimp_distractor_agreement_relational_noun": { |
| "acc": true |
| }, |
| "blimp_distractor_agreement_relative_clause": { |
| "acc": true |
| }, |
| "blimp_drop_argument": { |
| "acc": true |
| }, |
| "blimp_ellipsis_n_bar_1": { |
| "acc": true |
| }, |
| "blimp_ellipsis_n_bar_2": { |
| "acc": true |
| }, |
| "blimp_existential_there_object_raising": { |
| "acc": true |
| }, |
| "blimp_existential_there_quantifiers_1": { |
| "acc": true |
| }, |
| "blimp_existential_there_quantifiers_2": { |
| "acc": true |
| }, |
| "blimp_existential_there_subject_raising": { |
| "acc": true |
| }, |
| "blimp_expletive_it_object_raising": { |
| "acc": true |
| }, |
| "blimp_inchoative": { |
| "acc": true |
| }, |
| "blimp_intransitive": { |
| "acc": true |
| }, |
| "blimp_irregular_past_participle_adjectives": { |
| "acc": true |
| }, |
| "blimp_irregular_past_participle_verbs": { |
| "acc": true |
| }, |
| "blimp_irregular_plural_subject_verb_agreement_1": { |
| "acc": true |
| }, |
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| "effective": 1000 |
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| "effective": 1172 |
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| "effective": 2376 |
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| "model_args": "pretrained=EleutherAI/pythia-70m,revision=step256,dtype=float,trust_remote_code=True", |
| "model_num_parameters": 70426624, |
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| "model_name_sanitized": "EleutherAI__pythia-70m", |
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| "chat_template": null, |
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