|
{ |
|
"results": { |
|
"arc_challenge": { |
|
"alias": "arc_challenge", |
|
"acc,none": 0.2158703071672355, |
|
"acc_stderr,none": 0.012022975360030668, |
|
"acc_norm,none": 0.24573378839590443, |
|
"acc_norm_stderr,none": 0.012581033453730114 |
|
}, |
|
"arc_easy": { |
|
"alias": "arc_easy", |
|
"acc,none": 0.2727272727272727, |
|
"acc_stderr,none": 0.00913863072636423, |
|
"acc_norm,none": 0.2521043771043771, |
|
"acc_norm_stderr,none": 0.008910024163218178 |
|
}, |
|
"blimp": { |
|
"acc,none": 0.5266119402985074, |
|
"acc_stderr,none": 0.0018730484493487852, |
|
"alias": "blimp" |
|
}, |
|
"blimp_adjunct_island": { |
|
"alias": " - blimp_adjunct_island", |
|
"acc,none": 0.534, |
|
"acc_stderr,none": 0.015782683329937625 |
|
}, |
|
"blimp_anaphor_gender_agreement": { |
|
"alias": " - blimp_anaphor_gender_agreement", |
|
"acc,none": 0.614, |
|
"acc_stderr,none": 0.015402637476784374 |
|
}, |
|
"blimp_anaphor_number_agreement": { |
|
"alias": " - blimp_anaphor_number_agreement", |
|
"acc,none": 0.563, |
|
"acc_stderr,none": 0.015693223928730373 |
|
}, |
|
"blimp_animate_subject_passive": { |
|
"alias": " - blimp_animate_subject_passive", |
|
"acc,none": 0.606, |
|
"acc_stderr,none": 0.015459721957493377 |
|
}, |
|
"blimp_animate_subject_trans": { |
|
"alias": " - blimp_animate_subject_trans", |
|
"acc,none": 0.802, |
|
"acc_stderr,none": 0.0126077339341753 |
|
}, |
|
"blimp_causative": { |
|
"alias": " - blimp_causative", |
|
"acc,none": 0.396, |
|
"acc_stderr,none": 0.015473313265859408 |
|
}, |
|
"blimp_complex_NP_island": { |
|
"alias": " - blimp_complex_NP_island", |
|
"acc,none": 0.472, |
|
"acc_stderr,none": 0.015794475789511476 |
|
}, |
|
"blimp_coordinate_structure_constraint_complex_left_branch": { |
|
"alias": " - blimp_coordinate_structure_constraint_complex_left_branch", |
|
"acc,none": 0.525, |
|
"acc_stderr,none": 0.01579951342999601 |
|
}, |
|
"blimp_coordinate_structure_constraint_object_extraction": { |
|
"alias": " - blimp_coordinate_structure_constraint_object_extraction", |
|
"acc,none": 0.63, |
|
"acc_stderr,none": 0.015275252316519362 |
|
}, |
|
"blimp_determiner_noun_agreement_1": { |
|
"alias": " - blimp_determiner_noun_agreement_1", |
|
"acc,none": 0.511, |
|
"acc_stderr,none": 0.015815471195292686 |
|
}, |
|
"blimp_determiner_noun_agreement_2": { |
|
"alias": " - blimp_determiner_noun_agreement_2", |
|
"acc,none": 0.516, |
|
"acc_stderr,none": 0.015811198373114878 |
|
}, |
|
"blimp_determiner_noun_agreement_irregular_1": { |
|
"alias": " - blimp_determiner_noun_agreement_irregular_1", |
|
"acc,none": 0.492, |
|
"acc_stderr,none": 0.015817274929209008 |
|
}, |
|
"blimp_determiner_noun_agreement_irregular_2": { |
|
"alias": " - blimp_determiner_noun_agreement_irregular_2", |
|
"acc,none": 0.488, |
|
"acc_stderr,none": 0.015814743314581818 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adj_2": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adj_2", |
|
"acc,none": 0.51, |
|
"acc_stderr,none": 0.015816135752773207 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adj_irregular_1": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_1", |
|
"acc,none": 0.49, |
|
"acc_stderr,none": 0.015816135752773207 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adj_irregular_2": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_2", |
|
"acc,none": 0.496, |
|
"acc_stderr,none": 0.015818793703510886 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adjective_1": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adjective_1", |
|
"acc,none": 0.511, |
|
"acc_stderr,none": 0.015815471195292686 |
|
}, |
|
"blimp_distractor_agreement_relational_noun": { |
|
"alias": " - blimp_distractor_agreement_relational_noun", |
|
"acc,none": 0.511, |
|
"acc_stderr,none": 0.015815471195292682 |
|
}, |
|
"blimp_distractor_agreement_relative_clause": { |
|
"alias": " - blimp_distractor_agreement_relative_clause", |
|
"acc,none": 0.497, |
|
"acc_stderr,none": 0.015819015179246724 |
|
}, |
|
"blimp_drop_argument": { |
|
"alias": " - blimp_drop_argument", |
|
"acc,none": 0.663, |
|
"acc_stderr,none": 0.014955087918653607 |
|
}, |
|
"blimp_ellipsis_n_bar_1": { |
|
"alias": " - blimp_ellipsis_n_bar_1", |
|
"acc,none": 0.494, |
|
"acc_stderr,none": 0.015818160898606715 |
|
}, |
|
"blimp_ellipsis_n_bar_2": { |
|
"alias": " - blimp_ellipsis_n_bar_2", |
|
"acc,none": 0.326, |
|
"acc_stderr,none": 0.01483050720454104 |
|
}, |
|
"blimp_existential_there_object_raising": { |
|
"alias": " - blimp_existential_there_object_raising", |
|
"acc,none": 0.612, |
|
"acc_stderr,none": 0.015417317979911077 |
|
}, |
|
"blimp_existential_there_quantifiers_1": { |
|
"alias": " - blimp_existential_there_quantifiers_1", |
|
"acc,none": 0.909, |
|
"acc_stderr,none": 0.00909954953840023 |
|
}, |
|
"blimp_existential_there_quantifiers_2": { |
|
"alias": " - blimp_existential_there_quantifiers_2", |
|
"acc,none": 0.615, |
|
"acc_stderr,none": 0.01539519444541081 |
|
}, |
|
"blimp_existential_there_subject_raising": { |
|
"alias": " - blimp_existential_there_subject_raising", |
|
"acc,none": 0.533, |
|
"acc_stderr,none": 0.01578480789113878 |
|
}, |
|
"blimp_expletive_it_object_raising": { |
|
"alias": " - blimp_expletive_it_object_raising", |
|
"acc,none": 0.569, |
|
"acc_stderr,none": 0.015667944488173494 |
|
}, |
|
"blimp_inchoative": { |
|
"alias": " - blimp_inchoative", |
|
"acc,none": 0.389, |
|
"acc_stderr,none": 0.015424555647308488 |
|
}, |
|
"blimp_intransitive": { |
|
"alias": " - blimp_intransitive", |
|
"acc,none": 0.557, |
|
"acc_stderr,none": 0.015716169953204105 |
|
}, |
|
"blimp_irregular_past_participle_adjectives": { |
|
"alias": " - blimp_irregular_past_participle_adjectives", |
|
"acc,none": 0.293, |
|
"acc_stderr,none": 0.014399942998441273 |
|
}, |
|
"blimp_irregular_past_participle_verbs": { |
|
"alias": " - blimp_irregular_past_participle_verbs", |
|
"acc,none": 0.463, |
|
"acc_stderr,none": 0.015775927227262423 |
|
}, |
|
"blimp_irregular_plural_subject_verb_agreement_1": { |
|
"alias": " - blimp_irregular_plural_subject_verb_agreement_1", |
|
"acc,none": 0.493, |
|
"acc_stderr,none": 0.01581774956184357 |
|
}, |
|
"blimp_irregular_plural_subject_verb_agreement_2": { |
|
"alias": " - blimp_irregular_plural_subject_verb_agreement_2", |
|
"acc,none": 0.526, |
|
"acc_stderr,none": 0.015797897758042745 |
|
}, |
|
"blimp_left_branch_island_echo_question": { |
|
"alias": " - blimp_left_branch_island_echo_question", |
|
"acc,none": 0.596, |
|
"acc_stderr,none": 0.015524980677122581 |
|
}, |
|
"blimp_left_branch_island_simple_question": { |
|
"alias": " - blimp_left_branch_island_simple_question", |
|
"acc,none": 0.51, |
|
"acc_stderr,none": 0.01581613575277321 |
|
}, |
|
"blimp_matrix_question_npi_licensor_present": { |
|
"alias": " - blimp_matrix_question_npi_licensor_present", |
|
"acc,none": 0.339, |
|
"acc_stderr,none": 0.014976758771620347 |
|
}, |
|
"blimp_npi_present_1": { |
|
"alias": " - blimp_npi_present_1", |
|
"acc,none": 0.406, |
|
"acc_stderr,none": 0.015537226438634602 |
|
}, |
|
"blimp_npi_present_2": { |
|
"alias": " - blimp_npi_present_2", |
|
"acc,none": 0.341, |
|
"acc_stderr,none": 0.014998131348402714 |
|
}, |
|
"blimp_only_npi_licensor_present": { |
|
"alias": " - blimp_only_npi_licensor_present", |
|
"acc,none": 0.377, |
|
"acc_stderr,none": 0.015333170125779855 |
|
}, |
|
"blimp_only_npi_scope": { |
|
"alias": " - blimp_only_npi_scope", |
|
"acc,none": 0.599, |
|
"acc_stderr,none": 0.015506109745498322 |
|
}, |
|
"blimp_passive_1": { |
|
"alias": " - blimp_passive_1", |
|
"acc,none": 0.664, |
|
"acc_stderr,none": 0.014944140233795023 |
|
}, |
|
"blimp_passive_2": { |
|
"alias": " - blimp_passive_2", |
|
"acc,none": 0.602, |
|
"acc_stderr,none": 0.01548663410285892 |
|
}, |
|
"blimp_principle_A_c_command": { |
|
"alias": " - blimp_principle_A_c_command", |
|
"acc,none": 0.317, |
|
"acc_stderr,none": 0.014721675438880234 |
|
}, |
|
"blimp_principle_A_case_1": { |
|
"alias": " - blimp_principle_A_case_1", |
|
"acc,none": 0.844, |
|
"acc_stderr,none": 0.011480235006122365 |
|
}, |
|
"blimp_principle_A_case_2": { |
|
"alias": " - blimp_principle_A_case_2", |
|
"acc,none": 0.5, |
|
"acc_stderr,none": 0.015819299929208316 |
|
}, |
|
"blimp_principle_A_domain_1": { |
|
"alias": " - blimp_principle_A_domain_1", |
|
"acc,none": 0.53, |
|
"acc_stderr,none": 0.015790799515836763 |
|
}, |
|
"blimp_principle_A_domain_2": { |
|
"alias": " - blimp_principle_A_domain_2", |
|
"acc,none": 0.512, |
|
"acc_stderr,none": 0.015814743314581818 |
|
}, |
|
"blimp_principle_A_domain_3": { |
|
"alias": " - blimp_principle_A_domain_3", |
|
"acc,none": 0.509, |
|
"acc_stderr,none": 0.015816736995005392 |
|
}, |
|
"blimp_principle_A_reconstruction": { |
|
"alias": " - blimp_principle_A_reconstruction", |
|
"acc,none": 0.448, |
|
"acc_stderr,none": 0.015733516566347833 |
|
}, |
|
"blimp_regular_plural_subject_verb_agreement_1": { |
|
"alias": " - blimp_regular_plural_subject_verb_agreement_1", |
|
"acc,none": 0.389, |
|
"acc_stderr,none": 0.01542455564730849 |
|
}, |
|
"blimp_regular_plural_subject_verb_agreement_2": { |
|
"alias": " - blimp_regular_plural_subject_verb_agreement_2", |
|
"acc,none": 0.513, |
|
"acc_stderr,none": 0.015813952101896622 |
|
}, |
|
"blimp_sentential_negation_npi_licensor_present": { |
|
"alias": " - blimp_sentential_negation_npi_licensor_present", |
|
"acc,none": 0.644, |
|
"acc_stderr,none": 0.015149042659306623 |
|
}, |
|
"blimp_sentential_negation_npi_scope": { |
|
"alias": " - blimp_sentential_negation_npi_scope", |
|
"acc,none": 0.725, |
|
"acc_stderr,none": 0.014127086556490528 |
|
}, |
|
"blimp_sentential_subject_island": { |
|
"alias": " - blimp_sentential_subject_island", |
|
"acc,none": 0.46, |
|
"acc_stderr,none": 0.01576859691439438 |
|
}, |
|
"blimp_superlative_quantifiers_1": { |
|
"alias": " - blimp_superlative_quantifiers_1", |
|
"acc,none": 0.777, |
|
"acc_stderr,none": 0.013169830843425668 |
|
}, |
|
"blimp_superlative_quantifiers_2": { |
|
"alias": " - blimp_superlative_quantifiers_2", |
|
"acc,none": 0.62, |
|
"acc_stderr,none": 0.015356947477797585 |
|
}, |
|
"blimp_tough_vs_raising_1": { |
|
"alias": " - blimp_tough_vs_raising_1", |
|
"acc,none": 0.413, |
|
"acc_stderr,none": 0.01557798682993653 |
|
}, |
|
"blimp_tough_vs_raising_2": { |
|
"alias": " - blimp_tough_vs_raising_2", |
|
"acc,none": 0.616, |
|
"acc_stderr,none": 0.01538768276189707 |
|
}, |
|
"blimp_transitive": { |
|
"alias": " - blimp_transitive", |
|
"acc,none": 0.518, |
|
"acc_stderr,none": 0.015809045699406728 |
|
}, |
|
"blimp_wh_island": { |
|
"alias": " - blimp_wh_island", |
|
"acc,none": 0.611, |
|
"acc_stderr,none": 0.015424555647308495 |
|
}, |
|
"blimp_wh_questions_object_gap": { |
|
"alias": " - blimp_wh_questions_object_gap", |
|
"acc,none": 0.483, |
|
"acc_stderr,none": 0.015810153729833434 |
|
}, |
|
"blimp_wh_questions_subject_gap": { |
|
"alias": " - blimp_wh_questions_subject_gap", |
|
"acc,none": 0.439, |
|
"acc_stderr,none": 0.015701131345400774 |
|
}, |
|
"blimp_wh_questions_subject_gap_long_distance": { |
|
"alias": " - blimp_wh_questions_subject_gap_long_distance", |
|
"acc,none": 0.406, |
|
"acc_stderr,none": 0.015537226438634602 |
|
}, |
|
"blimp_wh_vs_that_no_gap": { |
|
"alias": " - blimp_wh_vs_that_no_gap", |
|
"acc,none": 0.373, |
|
"acc_stderr,none": 0.015300493622922809 |
|
}, |
|
"blimp_wh_vs_that_no_gap_long_distance": { |
|
"alias": " - blimp_wh_vs_that_no_gap_long_distance", |
|
"acc,none": 0.418, |
|
"acc_stderr,none": 0.01560511196754195 |
|
}, |
|
"blimp_wh_vs_that_with_gap": { |
|
"alias": " - blimp_wh_vs_that_with_gap", |
|
"acc,none": 0.61, |
|
"acc_stderr,none": 0.01543172505386661 |
|
}, |
|
"blimp_wh_vs_that_with_gap_long_distance": { |
|
"alias": " - blimp_wh_vs_that_with_gap_long_distance", |
|
"acc,none": 0.568, |
|
"acc_stderr,none": 0.015672320237336206 |
|
}, |
|
"lambada_openai": { |
|
"alias": "lambada_openai", |
|
"perplexity,none": 3681922.383502935, |
|
"perplexity_stderr,none": 360512.4372341794, |
|
"acc,none": 0.0, |
|
"acc_stderr,none": 0.0 |
|
}, |
|
"logiqa": { |
|
"alias": "logiqa", |
|
"acc,none": 0.22580645161290322, |
|
"acc_stderr,none": 0.016399713788445066, |
|
"acc_norm,none": 0.2457757296466974, |
|
"acc_norm_stderr,none": 0.016887410894296923 |
|
}, |
|
"mmlu": { |
|
"acc,none": 0.2460475715710013, |
|
"acc_stderr,none": 0.0036316292061756832, |
|
"alias": "mmlu" |
|
}, |
|
"mmlu_humanities": { |
|
"acc,none": 0.24484590860786398, |
|
"acc_stderr,none": 0.0062705558065704135, |
|
"alias": " - humanities" |
|
}, |
|
"mmlu_formal_logic": { |
|
"alias": " - formal_logic", |
|
"acc,none": 0.2698412698412698, |
|
"acc_stderr,none": 0.039701582732351734 |
|
}, |
|
"mmlu_high_school_european_history": { |
|
"alias": " - high_school_european_history", |
|
"acc,none": 0.26666666666666666, |
|
"acc_stderr,none": 0.03453131801885414 |
|
}, |
|
"mmlu_high_school_us_history": { |
|
"alias": " - high_school_us_history", |
|
"acc,none": 0.23039215686274508, |
|
"acc_stderr,none": 0.029554292605695066 |
|
}, |
|
"mmlu_high_school_world_history": { |
|
"alias": " - high_school_world_history", |
|
"acc,none": 0.24472573839662448, |
|
"acc_stderr,none": 0.027985699387036423 |
|
}, |
|
"mmlu_international_law": { |
|
"alias": " - international_law", |
|
"acc,none": 0.2892561983471074, |
|
"acc_stderr,none": 0.04139112727635463 |
|
}, |
|
"mmlu_jurisprudence": { |
|
"alias": " - jurisprudence", |
|
"acc,none": 0.2777777777777778, |
|
"acc_stderr,none": 0.04330043749650742 |
|
}, |
|
"mmlu_logical_fallacies": { |
|
"alias": " - logical_fallacies", |
|
"acc,none": 0.24539877300613497, |
|
"acc_stderr,none": 0.03380939813943354 |
|
}, |
|
"mmlu_moral_disputes": { |
|
"alias": " - moral_disputes", |
|
"acc,none": 0.26878612716763006, |
|
"acc_stderr,none": 0.023868003262500118 |
|
}, |
|
"mmlu_moral_scenarios": { |
|
"alias": " - moral_scenarios", |
|
"acc,none": 0.2435754189944134, |
|
"acc_stderr,none": 0.01435591196476786 |
|
}, |
|
"mmlu_philosophy": { |
|
"alias": " - philosophy", |
|
"acc,none": 0.2861736334405145, |
|
"acc_stderr,none": 0.02567025924218895 |
|
}, |
|
"mmlu_prehistory": { |
|
"alias": " - prehistory", |
|
"acc,none": 0.24382716049382716, |
|
"acc_stderr,none": 0.023891879541959607 |
|
}, |
|
"mmlu_professional_law": { |
|
"alias": " - professional_law", |
|
"acc,none": 0.22490221642764016, |
|
"acc_stderr,none": 0.010663604709948288 |
|
}, |
|
"mmlu_world_religions": { |
|
"alias": " - world_religions", |
|
"acc,none": 0.23391812865497075, |
|
"acc_stderr,none": 0.03246721765117825 |
|
}, |
|
"mmlu_other": { |
|
"acc,none": 0.25523012552301255, |
|
"acc_stderr,none": 0.007796215834368254, |
|
"alias": " - other" |
|
}, |
|
"mmlu_business_ethics": { |
|
"alias": " - business_ethics", |
|
"acc,none": 0.23, |
|
"acc_stderr,none": 0.04229525846816505 |
|
}, |
|
"mmlu_clinical_knowledge": { |
|
"alias": " - clinical_knowledge", |
|
"acc,none": 0.17735849056603772, |
|
"acc_stderr,none": 0.023508739218846934 |
|
}, |
|
"mmlu_college_medicine": { |
|
"alias": " - college_medicine", |
|
"acc,none": 0.2138728323699422, |
|
"acc_stderr,none": 0.031265112061730424 |
|
}, |
|
"mmlu_global_facts": { |
|
"alias": " - global_facts", |
|
"acc,none": 0.27, |
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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}, |
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|
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}, |
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|
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|
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|
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}, |
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|
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|
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|
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|
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|
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}, |
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"wikitext": { |
|
"alias": "wikitext", |
|
"word_perplexity,none": 323422.4990049516, |
|
"word_perplexity_stderr,none": "N/A", |
|
"byte_perplexity,none": 10.723944917267163, |
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"byte_perplexity_stderr,none": "N/A", |
|
"bits_per_byte,none": 3.422763809045428, |
|
"bits_per_byte_stderr,none": "N/A" |
|
}, |
|
"winogrande": { |
|
"alias": "winogrande", |
|
"acc,none": 0.4988161010260458, |
|
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|
}, |
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|
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|
"acc,none": 0.6153846153846154, |
|
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|
} |
|
}, |
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"groups": { |
|
"blimp": { |
|
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|
"acc_stderr,none": 0.0018730484493487852, |
|
"alias": "blimp" |
|
}, |
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"mmlu": { |
|
"acc,none": 0.2460475715710013, |
|
"acc_stderr,none": 0.0036316292061756832, |
|
"alias": "mmlu" |
|
}, |
|
"mmlu_humanities": { |
|
"acc,none": 0.24484590860786398, |
|
"acc_stderr,none": 0.0062705558065704135, |
|
"alias": " - humanities" |
|
}, |
|
"mmlu_other": { |
|
"acc,none": 0.25523012552301255, |
|
"acc_stderr,none": 0.007796215834368254, |
|
"alias": " - other" |
|
}, |
|
"mmlu_social_sciences": { |
|
"acc,none": 0.23561910952226195, |
|
"acc_stderr,none": 0.007646817597937775, |
|
"alias": " - social sciences" |
|
}, |
|
"mmlu_stem": { |
|
"acc,none": 0.24896923564858864, |
|
"acc_stderr,none": 0.007702076690998317, |
|
"alias": " - stem" |
|
} |
|
}, |
|
"group_subtasks": { |
|
"arc_easy": [], |
|
"arc_challenge": [], |
|
"blimp": [ |
|
"blimp_adjunct_island", |
|
"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": [ |
|
"mmlu_stem", |
|
"mmlu_other", |
|
"mmlu_social_sciences", |
|
"mmlu_humanities" |
|
], |
|
"piqa": [], |
|
"sciq": [], |
|
"wikitext": [], |
|
"winogrande": [], |
|
"wsc": [] |
|
}, |
|
"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", |
|
"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": "Question: {{question}}\nAnswer:", |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
}, |
|
"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)}}", |
|
"doc_to_choice": "{{choices.text}}", |
|
"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": "Question: {{question}}\nAnswer:", |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
}, |
|
"blimp_adjunct_island": { |
|
"task": "blimp_adjunct_island", |
|
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"doc_to_decontamination_query": "{{text}}", |
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"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, |
|
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