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{
"results": {
"polish": {
"acc,none": 0.4721071717287744,
"acc_stderr,none": 0.010755498956589112,
"acc_norm,none": 0.4566671808932055,
"acc_norm_stderr,none": 0.0068765892337264035,
"exact_match,score-first": 0.5154242863020202,
"exact_match_stderr,score-first": 0.16365606748645156,
"alias": "polish"
},
"belebele_pol_Latn": {
"acc,none": 0.30333333333333334,
"acc_stderr,none": 0.015331785641933972,
"acc_norm,none": 0.30333333333333334,
"acc_norm_stderr,none": 0.015331785641933972,
"alias": " - belebele_pol_Latn"
},
"polemo2_in": {
"exact_match,score-first": 0.6426592797783933,
"exact_match_stderr,score-first": 0.01784695026310191,
"alias": " - polemo2_in"
},
"polemo2_in_multiple_choice": {
"acc,none": 0.2880886426592798,
"acc_stderr,none": 0.016865856350741566,
"acc_norm,none": 0.23822714681440443,
"acc_norm_stderr,none": 0.01586502417719433,
"alias": " - polemo2_in_multiple_choice"
},
"polemo2_out": {
"exact_match,score-first": 0.6174089068825911,
"exact_match_stderr,score-first": 0.021889226400747818,
"alias": " - polemo2_out"
},
"polemo2_out_multiple_choice": {
"acc,none": 0.02631578947368421,
"acc_stderr,none": 0.007209311746493937,
"acc_norm,none": 0.2854251012145749,
"acc_norm_stderr,none": 0.02033979167488537,
"alias": " - polemo2_out_multiple_choice"
},
"polish_8tags_multiple_choice": {
"acc,none": 0.620768526989936,
"acc_stderr,none": 0.007338826630914385,
"acc_norm,none": 0.5681610247026533,
"acc_norm_stderr,none": 0.00749214603961998,
"alias": " - polish_8tags_multiple_choice"
},
"polish_8tags_regex": {
"exact_match,score-first": 0.4714089661482159,
"exact_match_stderr,score-first": 0.007550373089263302,
"alias": " - polish_8tags_regex"
},
"polish_belebele_regex": {
"exact_match,score-first": 0.3622222222222222,
"exact_match_stderr,score-first": 0.016030327346260632,
"alias": " - polish_belebele_regex"
},
"polish_dyk_multiple_choice": {
"acc,none": 0.3673469387755102,
"acc_stderr,none": 0.015035728051630332,
"acc_norm,none": 0.3673469387755102,
"acc_norm_stderr,none": 0.015035728051630332,
"alias": " - polish_dyk_multiple_choice"
},
"polish_dyk_regex": {
"exact_match,score-first": 0.1749271137026239,
"exact_match_stderr,score-first": 0.011848903583973948,
"alias": " - polish_dyk_regex"
},
"polish_ppc_multiple_choice": {
"acc,none": 0.475,
"acc_stderr,none": 0.015799513429996016,
"acc_norm,none": 0.475,
"acc_norm_stderr,none": 0.015799513429996016,
"alias": " - polish_ppc_multiple_choice"
},
"polish_ppc_regex": {
"exact_match,score-first": 0.0,
"exact_match_stderr,score-first": 0.0,
"alias": " - polish_ppc_regex"
},
"polish_psc_multiple_choice": {
"acc,none": 0.6948051948051948,
"acc_stderr,none": 0.014031763148103638,
"acc_norm,none": 0.6948051948051948,
"acc_norm_stderr,none": 0.014031763148103638,
"alias": " - polish_psc_multiple_choice"
},
"polish_psc_regex": {
"exact_match,score-first": 0.6929499072356216,
"exact_match_stderr,score-first": 0.014055544850266423,
"alias": " - polish_psc_regex"
}
},
"groups": {
"polish": {
"acc,none": 0.4721071717287744,
"acc_stderr,none": 0.010755498956589112,
"acc_norm,none": 0.4566671808932055,
"acc_norm_stderr,none": 0.0068765892337264035,
"exact_match,score-first": 0.5154242863020202,
"exact_match_stderr,score-first": 0.16365606748645156,
"alias": "polish"
}
},
"configs": {
"belebele_pol_Latn": {
"task": "belebele_pol_Latn",
"group": "belebele",
"dataset_path": "facebook/belebele",
"test_split": "pol_Latn",
"fewshot_split": "pol_Latn",
"doc_to_text": "P: {{flores_passage}}\nQ: {{question.strip()}}\nA: {{mc_answer1}}\nB: {{mc_answer2}}\nC: {{mc_answer3}}\nD: {{mc_answer4}}\nAnswer:",
"doc_to_target": "{{['1', '2', '3', '4'].index(correct_answer_num)}}",
"doc_to_choice": [
"A",
"B",
"C",
"D"
],
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "first_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}}",
"metadata": {
"version": 0.0
}
},
"polemo2_in": {
"task": "polemo2_in",
"group": [
"polemo2"
],
"dataset_path": "allegro/klej-polemo2-in",
"training_split": "train",
"validation_split": "validation",
"test_split": "test",
"doc_to_text": "Opinia: \"{{sentence}}\"\nOkreśl sentyment podanej opinii. Możliwe odpowiedzi:\nA - Neutralny\nB - Negatywny\nC - Pozytywny\nD - Niejednoznaczny\nPrawidłowa odpowiedź:",
"doc_to_target": "{{{'__label__meta_zero': 'A', '__label__meta_minus_m': 'B', '__label__meta_plus_m': 'C', '__label__meta_amb': 'D'}.get(target)}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
".",
","
],
"do_sample": false,
"temperature": 0.0,
"max_gen_toks": 50
},
"repeats": 1,
"filter_list": [
{
"name": "score-first",
"filter": [
{
"function": "regex",
"regex_pattern": "(\\b[ABCD]\\b)"
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence}}",
"metadata": {
"version": 1.0
}
},
"polemo2_in_multiple_choice": {
"task": "polemo2_in_multiple_choice",
"group": [
"polemo2_mc"
],
"dataset_path": "allegro/klej-polemo2-in",
"training_split": "train",
"validation_split": "validation",
"test_split": "test",
"doc_to_text": "Opinia: \"{{sentence}}\"\nOkreśl sentyment podanej opinii: Neutralny, Negatywny, Pozytywny, Niejednoznaczny.\nSentyment:",
"doc_to_target": "{{['__label__meta_zero', '__label__meta_minus_m', '__label__meta_plus_m', '__label__meta_amb'].index(target)}}",
"doc_to_choice": [
"Neutralny",
"Negatywny",
"Pozytywny",
"Niejednoznaczny"
],
"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": "{{sentence}}"
},
"polemo2_out": {
"task": "polemo2_out",
"group": [
"polemo2"
],
"dataset_path": "allegro/klej-polemo2-out",
"training_split": "train",
"validation_split": "validation",
"test_split": "test",
"doc_to_text": "Opinia: \"{{sentence}}\"\nOkreśl sentyment podanej opinii. Możliwe odpowiedzi:\nA - Neutralny\nB - Negatywny\nC - Pozytywny\nD - Niejednoznaczny\nPrawidłowa odpowiedź:",
"doc_to_target": "{{{'__label__meta_zero': 'A', '__label__meta_minus_m': 'B', '__label__meta_plus_m': 'C', '__label__meta_amb': 'D'}.get(target)}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
".",
","
],
"do_sample": false,
"temperature": 0.0,
"max_gen_toks": 50
},
"repeats": 1,
"filter_list": [
{
"name": "score-first",
"filter": [
{
"function": "regex",
"regex_pattern": "(\\b[ABCD]\\b)"
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence}}",
"metadata": {
"version": 1.0
}
},
"polemo2_out_multiple_choice": {
"task": "polemo2_out_multiple_choice",
"group": [
"polemo2_mc"
],
"dataset_path": "allegro/klej-polemo2-out",
"training_split": "train",
"validation_split": "validation",
"test_split": "test",
"doc_to_text": "Opinia: \"{{sentence}}\"\nOkreśl sentyment podanej opinii: Neutralny, Negatywny, Pozytywny, Niejednoznaczny.\nSentyment:",
"doc_to_target": "{{['__label__meta_zero', '__label__meta_minus_m', '__label__meta_plus_m', '__label__meta_amb'].index(target)}}",
"doc_to_choice": [
"Neutralny",
"Negatywny",
"Pozytywny",
"Niejednoznaczny"
],
"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": "{{sentence}}"
},
"polish_8tags_multiple_choice": {
"task": "polish_8tags_multiple_choice",
"dataset_path": "djstrong/8tags",
"training_split": "train",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Tytuł: \"{{sentence}}\"\nDo podanego tytułu przyporządkuj jedną najlepiej pasującą kategorię z podanych: Film, Historia, Jedzenie, Medycyna, Motoryzacja, Praca, Sport, Technologie.\nKategoria:",
"doc_to_target": "{{label|int}}",
"doc_to_choice": [
"Film",
"Historia",
"Jedzenie",
"Medycyna",
"Motoryzacja",
"Praca",
"Sport",
"Technologie"
],
"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": "{{sentence}}"
},
"polish_8tags_regex": {
"task": "polish_8tags_regex",
"dataset_path": "sdadas/8tags",
"training_split": "train",
"validation_split": "validation",
"test_split": "test",
"doc_to_text": "Tytuł: \"{{sentence}}\"\nPytanie: jaka kategoria najlepiej pasuje do podanego tytułu?\nMożliwe odpowiedzi:\nA - film\nB - historia\nC - jedzenie\nD - medycyna\nE - motoryzacja\nF - praca\nG - sport\nH - technologie\nPrawidłowa odpowiedź:",
"doc_to_target": "{{{0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E', 5: 'F', 6: 'G', 7: 'H'}.get(label)}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
".",
","
],
"do_sample": false,
"temperature": 0.0,
"max_gen_toks": 50
},
"repeats": 1,
"filter_list": [
{
"name": "score-first",
"filter": [
{
"function": "regex",
"regex_pattern": "(\\b[ABCDEFGH]\\b)"
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence}}"
},
"polish_belebele_regex": {
"task": "polish_belebele_regex",
"dataset_path": "facebook/belebele",
"test_split": "pol_Latn",
"doc_to_text": "Fragment: \"{{flores_passage}}\"\nPytanie: \"{{question}}\"\nMożliwe odpowiedzi:\nA - {{mc_answer1}}\nB - {{mc_answer2}}\nC - {{mc_answer3}}\nD - {{mc_answer4}}\nPrawidłowa odpowiedź:",
"doc_to_target": "{{{0: 'A', 1: 'B', 2: 'C', 3: 'D'}.get(correct_answer_num|int - 1)}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
".",
","
],
"do_sample": false,
"temperature": 0.0,
"max_gen_toks": 50
},
"repeats": 1,
"filter_list": [
{
"name": "score-first",
"filter": [
{
"function": "regex",
"regex_pattern": "(\\b[ABCD]\\b)"
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "{{flores_passage}} {{question}} {{mc_answer1}} {{mc_answer2}} {{mc_answer3}} {{mc_answer4}}"
},
"polish_dyk_multiple_choice": {
"task": "polish_dyk_multiple_choice",
"dataset_path": "allegro/klej-dyk",
"training_split": "train",
"test_split": "test",
"doc_to_text": "Pytanie: \"{{question}}\"\nSugerowana odpowiedź: \"{{answer}}\"\nPytanie: Czy sugerowana odpowiedź na zadane pytanie jest poprawna?\nOdpowiedz krótko \"Tak\" lub \"Nie\". Prawidłowa odpowiedź:",
"doc_to_target": "{{target|int}}",
"doc_to_choice": [
"Nie",
"Tak"
],
"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}} {{answer}}"
},
"polish_dyk_regex": {
"task": "polish_dyk_regex",
"dataset_path": "allegro/klej-dyk",
"training_split": "train",
"test_split": "test",
"doc_to_text": "Pytanie: \"{{question}}\"\nSugerowana odpowiedź: \"{{answer}}\"\nCzy sugerowana odpowiedź na zadane pytanie jest poprawna? Możliwe opcje:\nA - brakuje sugerowanej odpowiedzi\nB - nie, sugerowana odpowiedź nie jest poprawna\nC - tak, sugerowana odpowiedź jest poprawna\nD - brakuje pytania\nPrawidłowa opcja:",
"doc_to_target": "{{{0: 'A', 1: 'B', 2: 'C', 3: 'D'}.get(target|int + 1)}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
".",
","
],
"do_sample": false,
"temperature": 0.0,
"max_gen_toks": 50
},
"repeats": 1,
"filter_list": [
{
"name": "score-first",
"filter": [
{
"function": "regex",
"regex_pattern": "(\\b[ABCD]\\b)"
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "{{question}} {{answer}}"
},
"polish_ppc_multiple_choice": {
"task": "polish_ppc_multiple_choice",
"dataset_path": "djstrong/ppc",
"training_split": "train",
"validation_split": "validation",
"test_split": "test",
"doc_to_text": "Zdanie A: \"{{sentence_A}}\"\nZdanie B: \"{{sentence_B}}\"\nPytanie: jaka jest zależność między zdaniami A i B? Możliwe odpowiedzi:\nA - znaczą dokładnie to samo\nB - mają podobne znaczenie\nC - mają różne znaczenie\nPrawidłowa odpowiedź:",
"doc_to_target": "{{label|int - 1}}",
"doc_to_choice": [
"A",
"B",
"C"
],
"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": "{{sentence_A}} {{sentence_B}}"
},
"polish_ppc_regex": {
"task": "polish_ppc_regex",
"dataset_path": "sdadas/ppc",
"training_split": "train",
"validation_split": "validation",
"test_split": "test",
"doc_to_text": "Zdanie A: \"{{sentence_A}}\"\nZdanie B: \"{{sentence_B}}\"\nPytanie: jaka jest zależność między zdaniami A i B? Możliwe odpowiedzi:\nA - wszystkie odpowiedzi poprawne\nB - znaczą dokładnie to samo\nC - mają podobne znaczenie\nD - mają różne znaczenie\nPrawidłowa odpowiedź:",
"doc_to_target": "{{{0: 'A', 1: 'B', 2: 'C', 3: 'D'}.get(label|int)}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
".",
","
],
"do_sample": false,
"temperature": 0.0,
"max_gen_toks": 50
},
"repeats": 1,
"filter_list": [
{
"name": "score-first",
"filter": [
{
"function": "regex",
"regex_pattern": "(\\b[ABCD]\\b)"
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_A}} {{sentence_B}}"
},
"polish_psc_multiple_choice": {
"task": "polish_psc_multiple_choice",
"dataset_path": "allegro/klej-psc",
"training_split": "train",
"test_split": "test",
"doc_to_text": "Tekst: \"{{extract_text}}\"\nPodsumowanie: \"{{summary_text}}\"\nPytanie: Czy podsumowanie dla podanego tekstu jest poprawne?\nOdpowiedz krótko \"Tak\" lub \"Nie\". Prawidłowa odpowiedź:",
"doc_to_target": "{{label|int}}",
"doc_to_choice": [
"Nie",
"Tak"
],
"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": "{{extract_text}} {{summary_text}}"
},
"polish_psc_regex": {
"task": "polish_psc_regex",
"dataset_path": "allegro/klej-psc",
"training_split": "train",
"test_split": "test",
"doc_to_text": "Fragment 1: \"{{extract_text}}\"\nFragment 2: \"{{summary_text}}\"\nPytanie: jaka jest zależność między fragmentami 1 i 2?\nMożliwe odpowiedzi:\nA - wszystkie odpowiedzi poprawne\nB - dotyczą tego samego artykułu\nC - dotyczą różnych artykułów\nD - brak poprawnej odpowiedzi\nPrawidłowa odpowiedź:",
"doc_to_target": "{{{0: 'A', 1: 'B', 2: 'C', 3: 'D'}.get(label|int + 1)}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
".",
","
],
"do_sample": false,
"temperature": 0.0,
"max_gen_toks": 50
},
"repeats": 1,
"filter_list": [
{
"name": "score-first",
"filter": [
{
"function": "regex",
"regex_pattern": "(\\b[ABCD]\\b)"
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": true,
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