|
{ |
|
"results": { |
|
"assin2_rte": { |
|
"f1_macro,all": 0.9221381866393468, |
|
"acc,all": 0.9223856209150327, |
|
"alias": "assin2_rte" |
|
}, |
|
"assin2_sts": { |
|
"pearson,all": 0.8036205393734592, |
|
"mse,all": 0.4840232966283583, |
|
"alias": "assin2_sts" |
|
}, |
|
"bluex": { |
|
"acc,all": 0.6133518776077886, |
|
"acc,exam_id__USP_2018": 0.5740740740740741, |
|
"acc,exam_id__USP_2024": 0.6585365853658537, |
|
"acc,exam_id__UNICAMP_2021_2": 0.5882352941176471, |
|
"acc,exam_id__UNICAMP_2022": 0.6666666666666666, |
|
"acc,exam_id__UNICAMP_2019": 0.66, |
|
"acc,exam_id__USP_2023": 0.7272727272727273, |
|
"acc,exam_id__UNICAMP_2021_1": 0.5869565217391305, |
|
"acc,exam_id__UNICAMP_2018": 0.5370370370370371, |
|
"acc,exam_id__USP_2020": 0.5357142857142857, |
|
"acc,exam_id__USP_2019": 0.675, |
|
"acc,exam_id__USP_2021": 0.7115384615384616, |
|
"acc,exam_id__USP_2022": 0.5102040816326531, |
|
"acc,exam_id__UNICAMP_2023": 0.6046511627906976, |
|
"acc,exam_id__UNICAMP_2024": 0.5777777777777777, |
|
"acc,exam_id__UNICAMP_2020": 0.6363636363636364, |
|
"alias": "bluex" |
|
}, |
|
"enem_challenge": { |
|
"alias": "enem", |
|
"acc,all": 0.7501749475157453, |
|
"acc,exam_id__2022": 0.6992481203007519, |
|
"acc,exam_id__2016": 0.7107438016528925, |
|
"acc,exam_id__2017": 0.75, |
|
"acc,exam_id__2023": 0.7777777777777778, |
|
"acc,exam_id__2011": 0.7948717948717948, |
|
"acc,exam_id__2015": 0.7058823529411765, |
|
"acc,exam_id__2012": 0.75, |
|
"acc,exam_id__2010": 0.7435897435897436, |
|
"acc,exam_id__2009": 0.808695652173913, |
|
"acc,exam_id__2013": 0.7407407407407407, |
|
"acc,exam_id__2016_2": 0.7642276422764228, |
|
"acc,exam_id__2014": 0.7614678899082569 |
|
}, |
|
"faquad_nli": { |
|
"f1_macro,all": 0.8168992136555427, |
|
"acc,all": 0.8553846153846154, |
|
"alias": "faquad_nli" |
|
}, |
|
"hatebr_offensive": { |
|
"alias": "hatebr_offensive_binary", |
|
"f1_macro,all": 0.8860083727003879, |
|
"acc,all": 0.8864285714285715 |
|
}, |
|
"oab_exams": { |
|
"acc,all": 0.5143507972665148, |
|
"acc,exam_id__2011-04": 0.45, |
|
"acc,exam_id__2016-19": 0.5128205128205128, |
|
"acc,exam_id__2017-24": 0.5125, |
|
"acc,exam_id__2011-03": 0.40404040404040403, |
|
"acc,exam_id__2018-25": 0.4375, |
|
"acc,exam_id__2013-12": 0.5875, |
|
"acc,exam_id__2016-21": 0.4375, |
|
"acc,exam_id__2015-16": 0.4875, |
|
"acc,exam_id__2010-02": 0.54, |
|
"acc,exam_id__2016-20": 0.5875, |
|
"acc,exam_id__2012-06": 0.5125, |
|
"acc,exam_id__2015-18": 0.5, |
|
"acc,exam_id__2014-14": 0.55, |
|
"acc,exam_id__2014-13": 0.5125, |
|
"acc,exam_id__2012-07": 0.4875, |
|
"acc,exam_id__2012-08": 0.5375, |
|
"acc,exam_id__2011-05": 0.575, |
|
"acc,exam_id__2013-10": 0.5375, |
|
"acc,exam_id__2010-01": 0.4, |
|
"acc,exam_id__2012-09": 0.45454545454545453, |
|
"acc,exam_id__2015-17": 0.6666666666666666, |
|
"acc,exam_id__2016-20a": 0.4375, |
|
"acc,exam_id__2017-22": 0.575, |
|
"acc,exam_id__2013-11": 0.55, |
|
"acc,exam_id__2014-15": 0.6923076923076923, |
|
"acc,exam_id__2012-06a": 0.4875, |
|
"acc,exam_id__2017-23": 0.4875, |
|
"alias": "oab_exams" |
|
}, |
|
"portuguese_hate_speech": { |
|
"alias": "portuguese_hate_speech_binary", |
|
"f1_macro,all": 0.6598220108981507, |
|
"acc,all": 0.6650998824911868 |
|
}, |
|
"tweetsentbr": { |
|
"f1_macro,all": 0.7338301593814277, |
|
"acc,all": 0.7611940298507462, |
|
"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, |
|
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": "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 0x7f59bb4562a0>", |
|
"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 0x7f59bb455c60>", |
|
"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 0x7f59bb455ee0>", |
|
"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 0x7f59bb456480>", |
|
"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 0x7f59bb456700>", |
|
"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, |
|
974, |
|
558, |
|
1503, |
|
1958, |
|
2918, |
|
601, |
|
1560, |
|
984, |
|
2388, |
|
995, |
|
2233, |
|
1982, |
|
165, |
|
2788, |
|
1312, |
|
2285, |
|
522, |
|
1113, |
|
1670, |
|
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, |
|
3527, |
|
4, |
|
76, |
|
3579, |
|
3523, |
|
3551, |
|
68, |
|
3503, |
|
84, |
|
3539, |
|
64, |
|
3599, |
|
80, |
|
3563, |
|
3559, |
|
3543, |
|
3547, |
|
3587, |
|
3595, |
|
3575, |
|
3567, |
|
3591, |
|
24, |
|
96, |
|
92, |
|
3507, |
|
52, |
|
72, |
|
8, |
|
3571, |
|
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 0x7f59bb455620>", |
|
"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 0x7f59bb4558a0>", |
|
"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, |
|
66, |
|
41, |
|
9, |
|
4, |
|
91, |
|
42, |
|
7, |
|
20, |
|
76, |
|
1, |
|
104, |
|
13, |
|
67, |
|
54, |
|
97, |
|
27, |
|
24, |
|
14, |
|
16, |
|
48, |
|
53, |
|
40, |
|
34, |
|
49, |
|
32, |
|
119, |
|
114, |
|
2, |
|
58, |
|
83, |
|
18, |
|
36, |
|
5, |
|
6, |
|
10, |
|
35, |
|
38, |
|
0, |
|
21, |
|
46 |
|
], |
|
"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 |
|
} |
|
}, |
|
"tweetsentbr": { |
|
"task": "tweetsentbr", |
|
"group": [ |
|
"pt_benchmark" |
|
], |
|
"dataset_path": "eduagarcia/tweetsentbr_fewshot", |
|
"test_split": "test", |
|
"fewshot_split": "train", |
|
"doc_to_text": "Texto: {{sentence}}\nPergunta: O sentimento do texto é Positivo, Neutro ou Negativo?\nResposta:", |
|
"doc_to_target": "{{'Positivo' if label == 'Positive' else ('Negativo' if label == 'Negative' else 'Neutro')}}", |
|
"description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o sentimento do texto é Positivo, Neutro ou Negativo. Responda apenas com uma das opções.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"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": [ |
|
"Positivo", |
|
"Neutro", |
|
"Negativo" |
|
] |
|
}, |
|
{ |
|
"function": "take_first" |
|
} |
|
] |
|
} |
|
], |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
} |
|
}, |
|
"versions": { |
|
"assin2_rte": 1.1, |
|
"assin2_sts": 1.1, |
|
"bluex": 1.1, |
|
"enem_challenge": 1.1, |
|
"faquad_nli": 1.1, |
|
"hatebr_offensive": 1.0, |
|
"oab_exams": 1.5, |
|
"portuguese_hate_speech": 1.0, |
|
"tweetsentbr": 1.0 |
|
}, |
|
"n-shot": { |
|
"assin2_rte": 15, |
|
"assin2_sts": 15, |
|
"bluex": 3, |
|
"enem_challenge": 3, |
|
"faquad_nli": 15, |
|
"hatebr_offensive": 25, |
|
"oab_exams": 3, |
|
"portuguese_hate_speech": 25, |
|
"tweetsentbr": 25 |
|
}, |
|
"model_meta": { |
|
"truncated": 0, |
|
"non_truncated": 14150, |
|
"padded": 0, |
|
"non_padded": 14150, |
|
"fewshots_truncated": 0, |
|
"has_chat_template": true, |
|
"chat_type": "system_user_assistant", |
|
"n_gpus": 1, |
|
"accelerate_num_process": null, |
|
"model_sha": "ba96502c2b3d43cd6f416aa6dd12d820554167ba", |
|
"model_dtype": "torch.bfloat16", |
|
"model_memory_footprint": 66098194432, |
|
"model_num_parameters": 32512218112, |
|
"model_is_loaded_in_4bit": null, |
|
"model_is_loaded_in_8bit": null, |
|
"model_is_quantized": null, |
|
"model_device": "cuda:0", |
|
"batch_size": 2, |
|
"max_length": 2560, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32 |
|
}, |
|
"task_model_meta": { |
|
"assin2_rte": { |
|
"sample_size": 2448, |
|
"truncated": 0, |
|
"non_truncated": 2448, |
|
"padded": 0, |
|
"non_padded": 2448, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1307.2818627450981, |
|
"min_seq_length": 1288, |
|
"max_seq_length": 1369, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 15.0, |
|
"mean_effective_fewshot_size": 15.0 |
|
}, |
|
"assin2_sts": { |
|
"sample_size": 2448, |
|
"truncated": 0, |
|
"non_truncated": 2448, |
|
"padded": 0, |
|
"non_padded": 2448, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1498.2818627450981, |
|
"min_seq_length": 1479, |
|
"max_seq_length": 1560, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 15.0, |
|
"mean_effective_fewshot_size": 15.0 |
|
}, |
|
"bluex": { |
|
"sample_size": 719, |
|
"truncated": 0, |
|
"non_truncated": 719, |
|
"padded": 0, |
|
"non_padded": 719, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1495.2378303198886, |
|
"min_seq_length": 1175, |
|
"max_seq_length": 2146, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 3.0, |
|
"mean_effective_fewshot_size": 3.0 |
|
}, |
|
"enem_challenge": { |
|
"sample_size": 1429, |
|
"truncated": 0, |
|
"non_truncated": 1429, |
|
"padded": 0, |
|
"non_padded": 1429, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1415.7809657102869, |
|
"min_seq_length": 1185, |
|
"max_seq_length": 2376, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 3.0, |
|
"mean_effective_fewshot_size": 3.0 |
|
}, |
|
"faquad_nli": { |
|
"sample_size": 650, |
|
"truncated": 0, |
|
"non_truncated": 650, |
|
"padded": 0, |
|
"non_padded": 650, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1438.6876923076923, |
|
"min_seq_length": 1394, |
|
"max_seq_length": 1534, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 15.0, |
|
"mean_effective_fewshot_size": 15.0 |
|
}, |
|
"hatebr_offensive": { |
|
"sample_size": 1400, |
|
"truncated": 0, |
|
"non_truncated": 1400, |
|
"padded": 0, |
|
"non_padded": 1400, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1245.6992857142857, |
|
"min_seq_length": 1227, |
|
"max_seq_length": 1466, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 25.0, |
|
"mean_effective_fewshot_size": 25.0 |
|
}, |
|
"oab_exams": { |
|
"sample_size": 2195, |
|
"truncated": 0, |
|
"non_truncated": 2195, |
|
"padded": 0, |
|
"non_padded": 2195, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1203.888382687927, |
|
"min_seq_length": 974, |
|
"max_seq_length": 1617, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 3.0, |
|
"mean_effective_fewshot_size": 3.0 |
|
}, |
|
"portuguese_hate_speech": { |
|
"sample_size": 851, |
|
"truncated": 0, |
|
"non_truncated": 851, |
|
"padded": 0, |
|
"non_padded": 851, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1688.62044653349, |
|
"min_seq_length": 1658, |
|
"max_seq_length": 1722, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 25.0, |
|
"mean_effective_fewshot_size": 25.0 |
|
}, |
|
"tweetsentbr": { |
|
"sample_size": 2010, |
|
"truncated": 0, |
|
"non_truncated": 2010, |
|
"padded": 0, |
|
"non_padded": 2010, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1539.0567164179104, |
|
"min_seq_length": 1521, |
|
"max_seq_length": 1587, |
|
"max_ctx_length": 2528, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 25.0, |
|
"mean_effective_fewshot_size": 25.0 |
|
} |
|
}, |
|
"config": { |
|
"model": "huggingface", |
|
"model_args": "pretrained=OpenBuddy/openbuddy-qwen1.5-32b-v21.2-32k,dtype=bfloat16,device=cuda:0,revision=main,trust_remote_code=True,starting_max_length=2560", |
|
"batch_size": "auto", |
|
"batch_sizes": [], |
|
"device": null, |
|
"use_cache": null, |
|
"limit": [ |
|
null, |
|
null, |
|
null, |
|
null, |
|
null, |
|
null, |
|
null, |
|
null, |
|
null |
|
], |
|
"bootstrap_iters": 0, |
|
"gen_kwargs": null |
|
}, |
|
"git_hash": "f2a0116" |
|
} |