|
{ |
|
"results": { |
|
"arc_challenge": { |
|
"alias": "arc_challenge", |
|
"acc,none": 0.20819112627986347, |
|
"acc_stderr,none": 0.011864866118448069, |
|
"acc_norm,none": 0.2431740614334471, |
|
"acc_norm_stderr,none": 0.012536554144587089 |
|
}, |
|
"arc_easy": { |
|
"alias": "arc_easy", |
|
"acc,none": 0.2689393939393939, |
|
"acc_stderr,none": 0.009098548093009185, |
|
"acc_norm,none": 0.26515151515151514, |
|
"acc_norm_stderr,none": 0.009057621139172613 |
|
}, |
|
"blimp": { |
|
"acc,none": 0.5312985074626866, |
|
"acc_stderr,none": 0.0017764584780696397, |
|
"alias": "blimp" |
|
}, |
|
"blimp_adjunct_island": { |
|
"alias": " - blimp_adjunct_island", |
|
"acc,none": 0.457, |
|
"acc_stderr,none": 0.015760691590136388 |
|
}, |
|
"blimp_anaphor_gender_agreement": { |
|
"alias": " - blimp_anaphor_gender_agreement", |
|
"acc,none": 0.249, |
|
"acc_stderr,none": 0.013681600278702306 |
|
}, |
|
"blimp_anaphor_number_agreement": { |
|
"alias": " - blimp_anaphor_number_agreement", |
|
"acc,none": 0.485, |
|
"acc_stderr,none": 0.015812179641814895 |
|
}, |
|
"blimp_animate_subject_passive": { |
|
"alias": " - blimp_animate_subject_passive", |
|
"acc,none": 0.644, |
|
"acc_stderr,none": 0.015149042659306621 |
|
}, |
|
"blimp_animate_subject_trans": { |
|
"alias": " - blimp_animate_subject_trans", |
|
"acc,none": 0.806, |
|
"acc_stderr,none": 0.012510816141264366 |
|
}, |
|
"blimp_causative": { |
|
"alias": " - blimp_causative", |
|
"acc,none": 0.36, |
|
"acc_stderr,none": 0.015186527932040124 |
|
}, |
|
"blimp_complex_NP_island": { |
|
"alias": " - blimp_complex_NP_island", |
|
"acc,none": 0.471, |
|
"acc_stderr,none": 0.0157926694516289 |
|
}, |
|
"blimp_coordinate_structure_constraint_complex_left_branch": { |
|
"alias": " - blimp_coordinate_structure_constraint_complex_left_branch", |
|
"acc,none": 0.392, |
|
"acc_stderr,none": 0.015445859463771297 |
|
}, |
|
"blimp_coordinate_structure_constraint_object_extraction": { |
|
"alias": " - blimp_coordinate_structure_constraint_object_extraction", |
|
"acc,none": 0.565, |
|
"acc_stderr,none": 0.0156850572527172 |
|
}, |
|
"blimp_determiner_noun_agreement_1": { |
|
"alias": " - blimp_determiner_noun_agreement_1", |
|
"acc,none": 0.516, |
|
"acc_stderr,none": 0.01581119837311488 |
|
}, |
|
"blimp_determiner_noun_agreement_2": { |
|
"alias": " - blimp_determiner_noun_agreement_2", |
|
"acc,none": 0.505, |
|
"acc_stderr,none": 0.015818508944436656 |
|
}, |
|
"blimp_determiner_noun_agreement_irregular_1": { |
|
"alias": " - blimp_determiner_noun_agreement_irregular_1", |
|
"acc,none": 0.52, |
|
"acc_stderr,none": 0.015806639423035167 |
|
}, |
|
"blimp_determiner_noun_agreement_irregular_2": { |
|
"alias": " - blimp_determiner_noun_agreement_irregular_2", |
|
"acc,none": 0.535, |
|
"acc_stderr,none": 0.015780495050030156 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adj_2": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adj_2", |
|
"acc,none": 0.474, |
|
"acc_stderr,none": 0.015797897758042752 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adj_irregular_1": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_1", |
|
"acc,none": 0.532, |
|
"acc_stderr,none": 0.015786868759359005 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adj_irregular_2": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_2", |
|
"acc,none": 0.545, |
|
"acc_stderr,none": 0.01575510149834709 |
|
}, |
|
"blimp_determiner_noun_agreement_with_adjective_1": { |
|
"alias": " - blimp_determiner_noun_agreement_with_adjective_1", |
|
"acc,none": 0.476, |
|
"acc_stderr,none": 0.015801065586651758 |
|
}, |
|
"blimp_distractor_agreement_relational_noun": { |
|
"alias": " - blimp_distractor_agreement_relational_noun", |
|
"acc,none": 0.475, |
|
"acc_stderr,none": 0.01579951342999602 |
|
}, |
|
"blimp_distractor_agreement_relative_clause": { |
|
"alias": " - blimp_distractor_agreement_relative_clause", |
|
"acc,none": 0.507, |
|
"acc_stderr,none": 0.015817749561843578 |
|
}, |
|
"blimp_drop_argument": { |
|
"alias": " - blimp_drop_argument", |
|
"acc,none": 0.722, |
|
"acc_stderr,none": 0.014174516461485239 |
|
}, |
|
"blimp_ellipsis_n_bar_1": { |
|
"alias": " - blimp_ellipsis_n_bar_1", |
|
"acc,none": 0.449, |
|
"acc_stderr,none": 0.01573679276875201 |
|
}, |
|
"blimp_ellipsis_n_bar_2": { |
|
"alias": " - blimp_ellipsis_n_bar_2", |
|
"acc,none": 0.285, |
|
"acc_stderr,none": 0.014282120955200477 |
|
}, |
|
"blimp_existential_there_object_raising": { |
|
"alias": " - blimp_existential_there_object_raising", |
|
"acc,none": 0.673, |
|
"acc_stderr,none": 0.014842213153411249 |
|
}, |
|
"blimp_existential_there_quantifiers_1": { |
|
"alias": " - blimp_existential_there_quantifiers_1", |
|
"acc,none": 0.518, |
|
"acc_stderr,none": 0.015809045699406728 |
|
}, |
|
"blimp_existential_there_quantifiers_2": { |
|
"alias": " - blimp_existential_there_quantifiers_2", |
|
"acc,none": 0.862, |
|
"acc_stderr,none": 0.010912152632504389 |
|
}, |
|
"blimp_existential_there_subject_raising": { |
|
"alias": " - blimp_existential_there_subject_raising", |
|
"acc,none": 0.565, |
|
"acc_stderr,none": 0.0156850572527172 |
|
}, |
|
"blimp_expletive_it_object_raising": { |
|
"alias": " - blimp_expletive_it_object_raising", |
|
"acc,none": 0.595, |
|
"acc_stderr,none": 0.01553113699045304 |
|
}, |
|
"blimp_inchoative": { |
|
"alias": " - blimp_inchoative", |
|
"acc,none": 0.415, |
|
"acc_stderr,none": 0.015589035185604628 |
|
}, |
|
"blimp_intransitive": { |
|
"alias": " - blimp_intransitive", |
|
"acc,none": 0.616, |
|
"acc_stderr,none": 0.01538768276189707 |
|
}, |
|
"blimp_irregular_past_participle_adjectives": { |
|
"alias": " - blimp_irregular_past_participle_adjectives", |
|
"acc,none": 0.513, |
|
"acc_stderr,none": 0.01581395210189663 |
|
}, |
|
"blimp_irregular_past_participle_verbs": { |
|
"alias": " - blimp_irregular_past_participle_verbs", |
|
"acc,none": 0.459, |
|
"acc_stderr,none": 0.015766025737882154 |
|
}, |
|
"blimp_irregular_plural_subject_verb_agreement_1": { |
|
"alias": " - blimp_irregular_plural_subject_verb_agreement_1", |
|
"acc,none": 0.508, |
|
"acc_stderr,none": 0.01581727492920901 |
|
}, |
|
"blimp_irregular_plural_subject_verb_agreement_2": { |
|
"alias": " - blimp_irregular_plural_subject_verb_agreement_2", |
|
"acc,none": 0.548, |
|
"acc_stderr,none": 0.01574623586588068 |
|
}, |
|
"blimp_left_branch_island_echo_question": { |
|
"alias": " - blimp_left_branch_island_echo_question", |
|
"acc,none": 0.659, |
|
"acc_stderr,none": 0.014998131348402713 |
|
}, |
|
"blimp_left_branch_island_simple_question": { |
|
"alias": " - blimp_left_branch_island_simple_question", |
|
"acc,none": 0.544, |
|
"acc_stderr,none": 0.015757928553979162 |
|
}, |
|
"blimp_matrix_question_npi_licensor_present": { |
|
"alias": " - blimp_matrix_question_npi_licensor_present", |
|
"acc,none": 0.014, |
|
"acc_stderr,none": 0.003717232548256584 |
|
}, |
|
"blimp_npi_present_1": { |
|
"alias": " - blimp_npi_present_1", |
|
"acc,none": 0.931, |
|
"acc_stderr,none": 0.008018934050315155 |
|
}, |
|
"blimp_npi_present_2": { |
|
"alias": " - blimp_npi_present_2", |
|
"acc,none": 0.91, |
|
"acc_stderr,none": 0.009054390204866435 |
|
}, |
|
"blimp_only_npi_licensor_present": { |
|
"alias": " - blimp_only_npi_licensor_present", |
|
"acc,none": 0.878, |
|
"acc_stderr,none": 0.010354864712936703 |
|
}, |
|
"blimp_only_npi_scope": { |
|
"alias": " - blimp_only_npi_scope", |
|
"acc,none": 0.855, |
|
"acc_stderr,none": 0.011139977517890125 |
|
}, |
|
"blimp_passive_1": { |
|
"alias": " - blimp_passive_1", |
|
"acc,none": 0.633, |
|
"acc_stderr,none": 0.015249378464171744 |
|
}, |
|
"blimp_passive_2": { |
|
"alias": " - blimp_passive_2", |
|
"acc,none": 0.595, |
|
"acc_stderr,none": 0.015531136990453047 |
|
}, |
|
"blimp_principle_A_c_command": { |
|
"alias": " - blimp_principle_A_c_command", |
|
"acc,none": 0.347, |
|
"acc_stderr,none": 0.015060472031706624 |
|
}, |
|
"blimp_principle_A_case_1": { |
|
"alias": " - blimp_principle_A_case_1", |
|
"acc,none": 0.841, |
|
"acc_stderr,none": 0.011569479368271306 |
|
}, |
|
"blimp_principle_A_case_2": { |
|
"alias": " - blimp_principle_A_case_2", |
|
"acc,none": 0.419, |
|
"acc_stderr,none": 0.015610338967577802 |
|
}, |
|
"blimp_principle_A_domain_1": { |
|
"alias": " - blimp_principle_A_domain_1", |
|
"acc,none": 0.935, |
|
"acc_stderr,none": 0.0077997330618319975 |
|
}, |
|
"blimp_principle_A_domain_2": { |
|
"alias": " - blimp_principle_A_domain_2", |
|
"acc,none": 0.634, |
|
"acc_stderr,none": 0.015240612726405752 |
|
}, |
|
"blimp_principle_A_domain_3": { |
|
"alias": " - blimp_principle_A_domain_3", |
|
"acc,none": 0.513, |
|
"acc_stderr,none": 0.01581395210189663 |
|
}, |
|
"blimp_principle_A_reconstruction": { |
|
"alias": " - blimp_principle_A_reconstruction", |
|
"acc,none": 0.38, |
|
"acc_stderr,none": 0.015356947477797585 |
|
}, |
|
"blimp_regular_plural_subject_verb_agreement_1": { |
|
"alias": " - blimp_regular_plural_subject_verb_agreement_1", |
|
"acc,none": 0.416, |
|
"acc_stderr,none": 0.015594460144140601 |
|
}, |
|
"blimp_regular_plural_subject_verb_agreement_2": { |
|
"alias": " - blimp_regular_plural_subject_verb_agreement_2", |
|
"acc,none": 0.503, |
|
"acc_stderr,none": 0.015819015179246724 |
|
}, |
|
"blimp_sentential_negation_npi_licensor_present": { |
|
"alias": " - blimp_sentential_negation_npi_licensor_present", |
|
"acc,none": 1.0, |
|
"acc_stderr,none": 0.0 |
|
}, |
|
"blimp_sentential_negation_npi_scope": { |
|
"alias": " - blimp_sentential_negation_npi_scope", |
|
"acc,none": 0.586, |
|
"acc_stderr,none": 0.015583544104177522 |
|
}, |
|
"blimp_sentential_subject_island": { |
|
"alias": " - blimp_sentential_subject_island", |
|
"acc,none": 0.447, |
|
"acc_stderr,none": 0.015730176046009056 |
|
}, |
|
"blimp_superlative_quantifiers_1": { |
|
"alias": " - blimp_superlative_quantifiers_1", |
|
"acc,none": 0.006, |
|
"acc_stderr,none": 0.0024433521993298224 |
|
}, |
|
"blimp_superlative_quantifiers_2": { |
|
"alias": " - blimp_superlative_quantifiers_2", |
|
"acc,none": 0.107, |
|
"acc_stderr,none": 0.009779910359847167 |
|
}, |
|
"blimp_tough_vs_raising_1": { |
|
"alias": " - blimp_tough_vs_raising_1", |
|
"acc,none": 0.393, |
|
"acc_stderr,none": 0.015452824654081496 |
|
}, |
|
"blimp_tough_vs_raising_2": { |
|
"alias": " - blimp_tough_vs_raising_2", |
|
"acc,none": 0.649, |
|
"acc_stderr,none": 0.015100563798316405 |
|
}, |
|
"blimp_transitive": { |
|
"alias": " - blimp_transitive", |
|
"acc,none": 0.534, |
|
"acc_stderr,none": 0.015782683329937618 |
|
}, |
|
"blimp_wh_island": { |
|
"alias": " - blimp_wh_island", |
|
"acc,none": 0.487, |
|
"acc_stderr,none": 0.015813952101896626 |
|
}, |
|
"blimp_wh_questions_object_gap": { |
|
"alias": " - blimp_wh_questions_object_gap", |
|
"acc,none": 0.381, |
|
"acc_stderr,none": 0.015364734787007436 |
|
}, |
|
"blimp_wh_questions_subject_gap": { |
|
"alias": " - blimp_wh_questions_subject_gap", |
|
"acc,none": 0.278, |
|
"acc_stderr,none": 0.014174516461485246 |
|
}, |
|
"blimp_wh_questions_subject_gap_long_distance": { |
|
"alias": " - blimp_wh_questions_subject_gap_long_distance", |
|
"acc,none": 0.404, |
|
"acc_stderr,none": 0.015524980677122583 |
|
}, |
|
"blimp_wh_vs_that_no_gap": { |
|
"alias": " - blimp_wh_vs_that_no_gap", |
|
"acc,none": 0.588, |
|
"acc_stderr,none": 0.015572363292015102 |
|
}, |
|
"blimp_wh_vs_that_no_gap_long_distance": { |
|
"alias": " - blimp_wh_vs_that_no_gap_long_distance", |
|
"acc,none": 0.594, |
|
"acc_stderr,none": 0.015537226438634604 |
|
}, |
|
"blimp_wh_vs_that_with_gap": { |
|
"alias": " - blimp_wh_vs_that_with_gap", |
|
"acc,none": 0.47, |
|
"acc_stderr,none": 0.015790799515836763 |
|
}, |
|
"blimp_wh_vs_that_with_gap_long_distance": { |
|
"alias": " - blimp_wh_vs_that_with_gap_long_distance", |
|
"acc,none": 0.424, |
|
"acc_stderr,none": 0.015635487471405186 |
|
}, |
|
"lambada_openai": { |
|
"alias": "lambada_openai", |
|
"perplexity,none": 2347939.752880559, |
|
"perplexity_stderr,none": 209053.22406932144, |
|
"acc,none": 0.0, |
|
"acc_stderr,none": 0.0 |
|
}, |
|
"logiqa": { |
|
"alias": "logiqa", |
|
"acc,none": 0.20890937019969277, |
|
"acc_stderr,none": 0.015945399396423917, |
|
"acc_norm,none": 0.24270353302611367, |
|
"acc_norm_stderr,none": 0.016815676206479526 |
|
}, |
|
"mmlu": { |
|
"acc,none": 0.2689075630252101, |
|
"acc_stderr,none": 0.0037016236891939144, |
|
"alias": "mmlu" |
|
}, |
|
"mmlu_humanities": { |
|
"acc,none": 0.24165781083953242, |
|
"acc_stderr,none": 0.006229085729404717, |
|
"alias": " - humanities" |
|
}, |
|
"mmlu_formal_logic": { |
|
"alias": " - formal_logic", |
|
"acc,none": 0.36507936507936506, |
|
"acc_stderr,none": 0.04306241259127153 |
|
}, |
|
"mmlu_high_school_european_history": { |
|
"alias": " - high_school_european_history", |
|
"acc,none": 0.2545454545454545, |
|
"acc_stderr,none": 0.03401506715249039 |
|
}, |
|
"mmlu_high_school_us_history": { |
|
"alias": " - high_school_us_history", |
|
"acc,none": 0.2549019607843137, |
|
"acc_stderr,none": 0.030587591351604246 |
|
}, |
|
"mmlu_high_school_world_history": { |
|
"alias": " - high_school_world_history", |
|
"acc,none": 0.20253164556962025, |
|
"acc_stderr,none": 0.026160568246601464 |
|
}, |
|
"mmlu_international_law": { |
|
"alias": " - international_law", |
|
"acc,none": 0.14049586776859505, |
|
"acc_stderr,none": 0.031722334260021585 |
|
}, |
|
"mmlu_jurisprudence": { |
|
"alias": " - jurisprudence", |
|
"acc,none": 0.21296296296296297, |
|
"acc_stderr,none": 0.03957835471980981 |
|
}, |
|
"mmlu_logical_fallacies": { |
|
"alias": " - logical_fallacies", |
|
"acc,none": 0.2331288343558282, |
|
"acc_stderr,none": 0.0332201579577674 |
|
}, |
|
"mmlu_moral_disputes": { |
|
"alias": " - moral_disputes", |
|
"acc,none": 0.2138728323699422, |
|
"acc_stderr,none": 0.022075709251757177 |
|
}, |
|
"mmlu_moral_scenarios": { |
|
"alias": " - moral_scenarios", |
|
"acc,none": 0.27262569832402234, |
|
"acc_stderr,none": 0.014893391735249603 |
|
}, |
|
"mmlu_philosophy": { |
|
"alias": " - philosophy", |
|
"acc,none": 0.24115755627009647, |
|
"acc_stderr,none": 0.024296594034763426 |
|
}, |
|
"mmlu_prehistory": { |
|
"alias": " - prehistory", |
|
"acc,none": 0.22530864197530864, |
|
"acc_stderr,none": 0.023246202647819746 |
|
}, |
|
"mmlu_professional_law": { |
|
"alias": " - professional_law", |
|
"acc,none": 0.24445893089960888, |
|
"acc_stderr,none": 0.010976425013113897 |
|
}, |
|
"mmlu_world_religions": { |
|
"alias": " - world_religions", |
|
"acc,none": 0.17543859649122806, |
|
"acc_stderr,none": 0.029170885500727686 |
|
}, |
|
"mmlu_other": { |
|
"acc,none": 0.2513678789829417, |
|
"acc_stderr,none": 0.007644350095427473, |
|
"alias": " - other" |
|
}, |
|
"mmlu_business_ethics": { |
|
"alias": " - business_ethics", |
|
"acc,none": 0.21, |
|
"acc_stderr,none": 0.040936018074033256 |
|
}, |
|
"mmlu_clinical_knowledge": { |
|
"alias": " - clinical_knowledge", |
|
"acc,none": 0.2981132075471698, |
|
"acc_stderr,none": 0.028152837942493875 |
|
}, |
|
"mmlu_college_medicine": { |
|
"alias": " - college_medicine", |
|
"acc,none": 0.3352601156069364, |
|
"acc_stderr,none": 0.03599586301247078 |
|
}, |
|
"mmlu_global_facts": { |
|
"alias": " - global_facts", |
|
"acc,none": 0.18, |
|
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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", |
|
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"word_perplexity_stderr,none": "N/A", |
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|
"bits_per_byte,none": 2.7911816633957947, |
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"bits_per_byte_stderr,none": "N/A" |
|
}, |
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|
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|
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|
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|
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|
} |
|
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"groups": { |
|
"blimp": { |
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|
"alias": "blimp" |
|
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"acc_stderr,none": 0.0037016236891939144, |
|
"alias": "mmlu" |
|
}, |
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"mmlu_humanities": { |
|
"acc,none": 0.24165781083953242, |
|
"acc_stderr,none": 0.006229085729404717, |
|
"alias": " - humanities" |
|
}, |
|
"mmlu_other": { |
|
"acc,none": 0.2513678789829417, |
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"acc_stderr,none": 0.007644350095427473, |
|
"alias": " - other" |
|
}, |
|
"mmlu_social_sciences": { |
|
"acc,none": 0.31069223269418267, |
|
"acc_stderr,none": 0.008278554546998305, |
|
"alias": " - social sciences" |
|
}, |
|
"mmlu_stem": { |
|
"acc,none": 0.2860767522993974, |
|
"acc_stderr,none": 0.007959894447428693, |
|
"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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