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{
"results": {
"assin2_rte": {
"f1_macro,all": 0.4377495864867047,
"acc,all": 0.5502450980392157,
"alias": "assin2_rte"
},
"assin2_sts": {
"pearson,all": 0.04519453586348976,
"mse,all": 1.3953676470588234,
"alias": "assin2_sts"
},
"bluex": {
"acc,all": 0.2545201668984701,
"acc,exam_id__USP_2019": 0.2,
"acc,exam_id__USP_2022": 0.22448979591836735,
"acc,exam_id__USP_2023": 0.29545454545454547,
"acc,exam_id__UNICAMP_2018": 0.2037037037037037,
"acc,exam_id__UNICAMP_2019": 0.26,
"acc,exam_id__USP_2020": 0.26785714285714285,
"acc,exam_id__UNICAMP_2020": 0.3090909090909091,
"acc,exam_id__UNICAMP_2023": 0.27906976744186046,
"acc,exam_id__USP_2021": 0.19230769230769232,
"acc,exam_id__UNICAMP_2022": 0.3076923076923077,
"acc,exam_id__UNICAMP_2024": 0.3333333333333333,
"acc,exam_id__USP_2018": 0.18518518518518517,
"acc,exam_id__UNICAMP_2021_2": 0.29411764705882354,
"acc,exam_id__UNICAMP_2021_1": 0.32608695652173914,
"acc,exam_id__USP_2024": 0.14634146341463414,
"alias": "bluex"
},
"enem_challenge": {
"alias": "enem",
"acc,all": 0.20293911826452066,
"acc,exam_id__2013": 0.16666666666666666,
"acc,exam_id__2016_2": 0.1951219512195122,
"acc,exam_id__2016": 0.15702479338842976,
"acc,exam_id__2011": 0.20512820512820512,
"acc,exam_id__2017": 0.22413793103448276,
"acc,exam_id__2023": 0.2074074074074074,
"acc,exam_id__2014": 0.26605504587155965,
"acc,exam_id__2012": 0.15517241379310345,
"acc,exam_id__2009": 0.23478260869565218,
"acc,exam_id__2015": 0.25210084033613445,
"acc,exam_id__2022": 0.18796992481203006,
"acc,exam_id__2010": 0.18803418803418803
},
"faquad_nli": {
"f1_macro,all": 0.3399609444345819,
"acc,all": 0.34,
"alias": "faquad_nli"
},
"hatebr_offensive": {
"alias": "hatebr_offensive_binary",
"f1_macro,all": 0.3349186726374015,
"acc,all": 0.5007142857142857
},
"oab_exams": {
"acc,all": 0.2674259681093394,
"acc,exam_id__2016-20a": 0.25,
"acc,exam_id__2012-06": 0.25,
"acc,exam_id__2015-18": 0.2,
"acc,exam_id__2014-14": 0.3125,
"acc,exam_id__2012-07": 0.325,
"acc,exam_id__2015-16": 0.2125,
"acc,exam_id__2011-05": 0.25,
"acc,exam_id__2012-06a": 0.25,
"acc,exam_id__2017-23": 0.225,
"acc,exam_id__2016-19": 0.24358974358974358,
"acc,exam_id__2017-24": 0.275,
"acc,exam_id__2016-20": 0.2375,
"acc,exam_id__2017-22": 0.25,
"acc,exam_id__2013-12": 0.2875,
"acc,exam_id__2010-02": 0.25,
"acc,exam_id__2011-03": 0.25252525252525254,
"acc,exam_id__2012-08": 0.325,
"acc,exam_id__2013-10": 0.3125,
"acc,exam_id__2016-21": 0.3,
"acc,exam_id__2014-15": 0.32051282051282054,
"acc,exam_id__2018-25": 0.275,
"acc,exam_id__2014-13": 0.25,
"acc,exam_id__2010-01": 0.23529411764705882,
"acc,exam_id__2015-17": 0.24358974358974358,
"acc,exam_id__2013-11": 0.325,
"acc,exam_id__2011-04": 0.2625,
"acc,exam_id__2012-09": 0.3116883116883117,
"alias": "oab_exams"
},
"portuguese_hate_speech": {
"alias": "portuguese_hate_speech_binary",
"f1_macro,all": 0.22986425339366515,
"acc,all": 0.2984723854289072
},
"tweetsentbr": {
"f1_macro,all": 0.18133818528465914,
"acc,all": 0.30646766169154227,
"alias": "tweetsentbr"
}
},
"configs": {
"assin2_rte": {
"task": "assin2_rte",
"group": [
"pt_benchmark",
"assin2"
],
"dataset_path": "assin2",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? Sim ou Não?\nResposta:",
"doc_to_target": "{{['Não', 'Sim'][entailment_judgment]}}",
"description": "Abaixo estão pares de premissa e hipótese. Para cada par, indique se a hipótese pode ser inferida a partir da premissa, responda apenas com \"Sim\" ou \"Não\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
1,
3251,
2,
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3256,
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3262,
3263,
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3266,
3267,
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3268,
3269,
21,
3270,
3271,
22,
3272,
3273,
23,
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24,
25,
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],
"id_column": "sentence_pair_id"
}
},
"num_fewshot": 15,
"metric_list": [
{
"metric": "f1_macro",
"aggregation": "f1_macro",
"higher_is_better": true
},
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "find_similar_label",
"labels": [
"Sim",
"Não"
]
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": false,
"metadata": {
"version": 1.1
}
},
"assin2_sts": {
"task": "assin2_sts",
"group": [
"pt_benchmark",
"assin2"
],
"dataset_path": "assin2",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: Quão similares são as duas frases? Dê uma pontuação entre 1,0 a 5,0.\nResposta:",
"doc_to_target": "<function assin2_float_to_pt_str at 0x7fb393d55120>",
"description": "Abaixo estão pares de frases que você deve avaliar o grau de similaridade. Dê uma pontuação entre 1,0 e 5,0, sendo 1,0 pouco similar e 5,0 muito similar.\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
1,
3251,
2,
3252,
3,
4,
5,
6,
3253,
7,
3254,
3255,
3256,
8,
9,
10,
3257,
11,
3258,
12,
13,
14,
15,
3259,
3260,
3261,
3262,
3263,
16,
17,
3264,
18,
3265,
3266,
3267,
19,
20,
3268,
3269,
21,
3270,
3271,
22,
3272,
3273,
23,
3274,
24,
25,
3275
],
"id_column": "sentence_pair_id"
}
},
"num_fewshot": 15,
"metric_list": [
{
"metric": "pearson",
"aggregation": "pearsonr",
"higher_is_better": true
},
{
"metric": "mse",
"aggregation": "mean_squared_error",
"higher_is_better": false
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "number_filter",
"type": "float",
"range_min": 1.0,
"range_max": 5.0,
"on_outside_range": "clip",
"fallback": 5.0
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": false,
"metadata": {
"version": 1.1
}
},
"bluex": {
"task": "bluex",
"group": [
"pt_benchmark",
"vestibular"
],
"dataset_path": "eduagarcia-temp/BLUEX_without_images",
"test_split": "train",
"fewshot_split": "train",
"doc_to_text": "<function enem_doc_to_text at 0x7fb393d54ae0>",
"doc_to_target": "{{answerKey}}",
"description": "As perguntas a seguir são questões de múltipla escolha de provas de vestibular de universidades brasileiras, selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\", \"D\" ou \"E\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
"USP_2018_3",
"UNICAMP_2018_2",
"USP_2018_35",
"UNICAMP_2018_16",
"USP_2018_89"
],
"id_column": "id",
"exclude_from_task": true
}
},
"num_fewshot": 3,
"metric_list": [
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "normalize_spaces"
},
{
"function": "remove_accents"
},
{
"function": "find_choices",
"choices": [
"A",
"B",
"C",
"D",
"E"
],
"regex_patterns": [
"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
"\\b([ABCDE])\\.",
"\\b([ABCDE]) ?[.):-]",
"\\b([ABCDE])$",
"\\b([ABCDE])\\b"
]
},
{
"function": "take_first"
}
],
"group_by": {
"column": "exam_id"
}
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fb393d54d60>",
"metadata": {
"version": 1.1
}
},
"enem_challenge": {
"task": "enem_challenge",
"task_alias": "enem",
"group": [
"pt_benchmark",
"vestibular"
],
"dataset_path": "eduagarcia/enem_challenge",
"test_split": "train",
"fewshot_split": "train",
"doc_to_text": "<function enem_doc_to_text at 0x7fb393d55300>",
"doc_to_target": "{{answerKey}}",
"description": "As perguntas a seguir são questões de múltipla escolha do Exame Nacional do Ensino Médio (ENEM), selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\", \"D\" ou \"E\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
"2022_21",
"2022_88",
"2022_143"
],
"id_column": "id",
"exclude_from_task": true
}
},
"num_fewshot": 3,
"metric_list": [
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "normalize_spaces"
},
{
"function": "remove_accents"
},
{
"function": "find_choices",
"choices": [
"A",
"B",
"C",
"D",
"E"
],
"regex_patterns": [
"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
"\\b([ABCDE])\\.",
"\\b([ABCDE]) ?[.):-]",
"\\b([ABCDE])$",
"\\b([ABCDE])\\b"
]
},
{
"function": "take_first"
}
],
"group_by": {
"column": "exam_id"
}
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fb393d55580>",
"metadata": {
"version": 1.1
}
},
"faquad_nli": {
"task": "faquad_nli",
"group": [
"pt_benchmark"
],
"dataset_path": "ruanchaves/faquad-nli",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Pergunta: {{question}}\nResposta: {{answer}}\nA resposta dada satisfaz à pergunta? Sim ou Não?",
"doc_to_target": "{{['Não', 'Sim'][label]}}",
"description": "Abaixo estão pares de pergunta e resposta. Para cada par, você deve julgar se a resposta responde à pergunta de maneira satisfatória e aparenta estar correta. Escreva apenas \"Sim\" ou \"Não\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "first_n",
"sampler_config": {
"fewshot_indices": [
1893,
949,
663,
105,
1169,
2910,
2227,
2813,
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1312,
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522,
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323,
236,
1263,
1562,
2519,
1049,
432,
1167,
1394,
2022,
2551,
2194,
2187,
2282,
2816,
108,
301,
1185,
1315,
1420,
2436,
2322,
766
]
}
},
"num_fewshot": 15,
"metric_list": [
{
"metric": "f1_macro",
"aggregation": "f1_macro",
"higher_is_better": true
},
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "find_similar_label",
"labels": [
"Sim",
"Não"
]
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": false,
"metadata": {
"version": 1.1
}
},
"hatebr_offensive": {
"task": "hatebr_offensive",
"task_alias": "hatebr_offensive_binary",
"group": [
"pt_benchmark"
],
"dataset_path": "eduagarcia/portuguese_benchmark",
"dataset_name": "HateBR_offensive_binary",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Texto: {{sentence}}\nPergunta: O texto é ofensivo?\nResposta:",
"doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
"description": "Abaixo contém o texto de comentários de usuários do Instagram em português, sua tarefa é classificar se o texto é ofensivo ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
48,
44,
36,
20,
3511,
88,
3555,
16,
56,
3535,
60,
40,
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4,
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3575,
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24,
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52,
72,
8,
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3515,
3519,
3531,
28,
32,
0,
12,
3583
],
"id_column": "idx"
}
},
"num_fewshot": 25,
"metric_list": [
{
"metric": "f1_macro",
"aggregation": "f1_macro",
"higher_is_better": true
},
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "find_similar_label",
"labels": [
"Sim",
"Não"
]
},
{
"function": "take_first"
}
]
}
],
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"oab_exams": {
"task": "oab_exams",
"group": [
"legal_benchmark",
"pt_benchmark"
],
"dataset_path": "eduagarcia/oab_exams",
"test_split": "train",
"fewshot_split": "train",
"doc_to_text": "<function doc_to_text at 0x7fb393d544a0>",
"doc_to_target": "{{answerKey}}",
"description": "As perguntas a seguir são questões de múltipla escolha do Exame de Ordem da Ordem dos Advogados do Brasil (OAB), selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\" ou \"D\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
"2010-01_1",
"2010-01_11",
"2010-01_13",
"2010-01_23",
"2010-01_26",
"2010-01_28",
"2010-01_38",
"2010-01_48",
"2010-01_58",
"2010-01_68",
"2010-01_76",
"2010-01_83",
"2010-01_85",
"2010-01_91",
"2010-01_99"
],
"id_column": "id",
"exclude_from_task": true
}
},
"num_fewshot": 3,
"metric_list": [
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "normalize_spaces"
},
{
"function": "remove_accents"
},
{
"function": "find_choices",
"choices": [
"A",
"B",
"C",
"D"
],
"regex_patterns": [
"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
"\\b([ABCD])\\.",
"\\b([ABCD]) ?[.):-]",
"\\b([ABCD])$",
"\\b([ABCD])\\b"
]
},
{
"function": "take_first"
}
],
"group_by": {
"column": "exam_id"
}
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "<function doc_to_text at 0x7fb393d54720>",
"metadata": {
"version": 1.5
}
},
"portuguese_hate_speech": {
"task": "portuguese_hate_speech",
"task_alias": "portuguese_hate_speech_binary",
"group": [
"pt_benchmark"
],
"dataset_path": "eduagarcia/portuguese_benchmark",
"dataset_name": "Portuguese_Hate_Speech_binary",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
"doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
"description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
52,
50,
39,
28,
3,
105,
22,
25,
60,
11,
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41,
9,
4,
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42,
7,
20,
76,
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