|
{ |
|
"results": { |
|
"assin2_rte": { |
|
"f1_macro,all": 0.3333333333333333, |
|
"acc,all": 0.5, |
|
"alias": "assin2_rte" |
|
}, |
|
"assin2_sts": { |
|
"pearson,all": 0.008251040372066512, |
|
"mse,all": 2.529979575163398, |
|
"alias": "assin2_sts" |
|
}, |
|
"bluex": { |
|
"acc,all": 0.18776077885952713, |
|
"acc,exam_id__USP_2018": 0.1111111111111111, |
|
"acc,exam_id__USP_2024": 0.12195121951219512, |
|
"acc,exam_id__USP_2021": 0.19230769230769232, |
|
"acc,exam_id__UNICAMP_2021_1": 0.2826086956521739, |
|
"acc,exam_id__USP_2020": 0.19642857142857142, |
|
"acc,exam_id__USP_2022": 0.1836734693877551, |
|
"acc,exam_id__UNICAMP_2022": 0.23076923076923078, |
|
"acc,exam_id__UNICAMP_2020": 0.14545454545454545, |
|
"acc,exam_id__USP_2023": 0.11363636363636363, |
|
"acc,exam_id__USP_2019": 0.25, |
|
"acc,exam_id__UNICAMP_2023": 0.32558139534883723, |
|
"acc,exam_id__UNICAMP_2024": 0.17777777777777778, |
|
"acc,exam_id__UNICAMP_2021_2": 0.13725490196078433, |
|
"acc,exam_id__UNICAMP_2019": 0.16, |
|
"acc,exam_id__UNICAMP_2018": 0.2222222222222222, |
|
"alias": "bluex" |
|
}, |
|
"enem_challenge": { |
|
"alias": "enem", |
|
"acc,all": 0.20573827851644508, |
|
"acc,exam_id__2023": 0.22962962962962963, |
|
"acc,exam_id__2009": 0.16521739130434782, |
|
"acc,exam_id__2013": 0.23148148148148148, |
|
"acc,exam_id__2011": 0.17094017094017094, |
|
"acc,exam_id__2014": 0.22018348623853212, |
|
"acc,exam_id__2016_2": 0.2032520325203252, |
|
"acc,exam_id__2022": 0.17293233082706766, |
|
"acc,exam_id__2017": 0.23275862068965517, |
|
"acc,exam_id__2016": 0.17355371900826447, |
|
"acc,exam_id__2015": 0.16806722689075632, |
|
"acc,exam_id__2012": 0.2672413793103448, |
|
"acc,exam_id__2010": 0.23931623931623933 |
|
}, |
|
"faquad_nli": { |
|
"f1_macro,all": 0.4396551724137931, |
|
"acc,all": 0.7846153846153846, |
|
"alias": "faquad_nli" |
|
}, |
|
"oab_exams": { |
|
"acc,all": 0.24145785876993167, |
|
"acc,exam_id__2010-01": 0.24705882352941178, |
|
"acc,exam_id__2017-24": 0.2375, |
|
"acc,exam_id__2016-21": 0.1875, |
|
"acc,exam_id__2016-19": 0.2692307692307692, |
|
"acc,exam_id__2013-12": 0.25, |
|
"acc,exam_id__2015-17": 0.32051282051282054, |
|
"acc,exam_id__2012-09": 0.2597402597402597, |
|
"acc,exam_id__2014-14": 0.175, |
|
"acc,exam_id__2013-10": 0.275, |
|
"acc,exam_id__2012-06a": 0.2875, |
|
"acc,exam_id__2016-20a": 0.25, |
|
"acc,exam_id__2018-25": 0.2, |
|
"acc,exam_id__2011-04": 0.2, |
|
"acc,exam_id__2011-05": 0.2875, |
|
"acc,exam_id__2017-22": 0.275, |
|
"acc,exam_id__2014-13": 0.275, |
|
"acc,exam_id__2012-08": 0.15, |
|
"acc,exam_id__2013-11": 0.2375, |
|
"acc,exam_id__2011-03": 0.24242424242424243, |
|
"acc,exam_id__2012-07": 0.25, |
|
"acc,exam_id__2015-16": 0.225, |
|
"acc,exam_id__2014-15": 0.19230769230769232, |
|
"acc,exam_id__2010-02": 0.28, |
|
"acc,exam_id__2016-20": 0.2375, |
|
"acc,exam_id__2017-23": 0.3, |
|
"acc,exam_id__2012-06": 0.225, |
|
"acc,exam_id__2015-18": 0.175, |
|
"alias": "oab_exams" |
|
}, |
|
"sparrow_emotion-2021-cortiz-por": { |
|
"alias": "emotion-2021-cortiz-por", |
|
"f1_macro,all": 0.01696284559524297, |
|
"acc,all": 0.056 |
|
}, |
|
"sparrow_hate-2019-fortuna-por": { |
|
"alias": "hate-2019-fortuna-por", |
|
"f1_macro,all": 0.5175257215183529, |
|
"acc,all": 0.538 |
|
}, |
|
"sparrow_sentiment-2016-mozetic-por": { |
|
"alias": "sentiment-2016-mozetic-por", |
|
"f1_macro,all": 0.14550406020994255, |
|
"acc,all": 0.158 |
|
}, |
|
"sparrow_sentiment-2018-brum-por": { |
|
"alias": "sentiment-2018-brum-por", |
|
"f1_macro,all": 0.2744510495706668, |
|
"acc,all": 0.352 |
|
} |
|
}, |
|
"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?\nResposta:", |
|
"doc_to_target": "{{['Não', 'Sim'][entailment_judgment]}}", |
|
"description": "Abaixo contém pares de premissa e hipótese, para cada par você deve julgar 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": 1.0 |
|
} |
|
}, |
|
"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: Qual o grau de similaridade entre as duas frases de 1,0 a 5,0?\nResposta:", |
|
"doc_to_target": "<function assin2_float_to_pt_str at 0x7fe12fa9d800>", |
|
"description": "Abaixo contém pares de frases, para cada par você deve julgar o grau de similaridade de 1,0 a 5,0, responda apenas com o número.\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": 1.0 |
|
} |
|
}, |
|
"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 0x7fe12fa9d1c0>", |
|
"doc_to_target": "{{answerKey}}", |
|
"description": "As perguntas a seguir são questões de multipla escolha de provas de vestibular de Universidades Brasileiras, reponda 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])$", |
|
"\\b([ABCDE])\\b" |
|
] |
|
}, |
|
{ |
|
"function": "take_first" |
|
} |
|
], |
|
"group_by": { |
|
"column": "exam_id" |
|
} |
|
} |
|
], |
|
"should_decontaminate": true, |
|
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fe12fa9d440>", |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
}, |
|
"enem_challenge": { |
|
"task": "enem_challenge", |
|
"task_alias": "enem", |
|
"group": [ |
|
"pt_benchmark", |
|
"vestibular" |
|
], |
|
"dataset_path": "eduagarcia/enem_challenge", |
|
"test_split": "train", |
|
"fewshot_split": "train", |
|
"doc_to_text": "<function enem_doc_to_text at 0x7fe12fa9d9e0>", |
|
"doc_to_target": "{{answerKey}}", |
|
"description": "As perguntas a seguir são questões de multipla escolha do Exame Nacional do Ensino Médio (ENEM), reponda apenas com as letras A, B, C, D ou E.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "id_sampler", |
|
"sampler_config": { |
|
"id_list": [ |
|
"2022_21", |
|
"2022_88", |
|
"2022_143" |
|
], |
|
"id_column": "id", |
|
"exclude_from_task": true |
|
} |
|
}, |
|
"num_fewshot": 3, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "acc", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "generate_until", |
|
"generation_kwargs": { |
|
"max_gen_toks": 32, |
|
"do_sample": false, |
|
"temperature": 0.0, |
|
"top_k": null, |
|
"top_p": null, |
|
"until": [ |
|
"\n\n" |
|
] |
|
}, |
|
"repeats": 1, |
|
"filter_list": [ |
|
{ |
|
"name": "all", |
|
"filter": [ |
|
{ |
|
"function": "normalize_spaces" |
|
}, |
|
{ |
|
"function": "remove_accents" |
|
}, |
|
{ |
|
"function": "find_choices", |
|
"choices": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D", |
|
"E" |
|
], |
|
"regex_patterns": [ |
|
"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta[Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b", |
|
"\\b([ABCDE])\\.", |
|
"\\b([ABCDE]) ?[.):-]", |
|
"\\b([ABCDE])$", |
|
"\\b([ABCDE])\\b" |
|
] |
|
}, |
|
{ |
|
"function": "take_first" |
|
} |
|
], |
|
"group_by": { |
|
"column": "exam_id" |
|
} |
|
} |
|
], |
|
"should_decontaminate": true, |
|
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fe12fa9dc60>", |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
}, |
|
"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 satisfaz a pergunta? Sim ou Não?", |
|
"doc_to_target": "{{['Não', 'Sim'][label]}}", |
|
"description": "Abaixo contém pares de pergunta e reposta, para cada par você deve julgar resposta responde a 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": 1.0 |
|
} |
|
}, |
|
"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 0x7fe12fa9cb80>", |
|
"doc_to_target": "{{answerKey}}", |
|
"description": "As perguntas a seguir são questões de multipla escolha do Exame de Ordem da Ordem dos Advogados do Brasil (OAB), reponda 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 0x7fe12fa9ce00>", |
|
"metadata": { |
|
"version": 1.4 |
|
} |
|
}, |
|
"sparrow_emotion-2021-cortiz-por": { |
|
"task": "sparrow_emotion-2021-cortiz-por", |
|
"task_alias": "emotion-2021-cortiz-por", |
|
"group": [ |
|
"pt_benchmark", |
|
"sparrow" |
|
], |
|
"dataset_path": "UBC-NLP/sparrow", |
|
"dataset_name": "emotion-2021-cortiz-por", |
|
"test_split": "validation", |
|
"fewshot_split": "train", |
|
"doc_to_text": "Texto: {{content}}\nPergunta: Qual a principal emoção apresentada no texto?\nResposta:", |
|
"doc_to_target": "<function sparrow_emotion_por_trans_label at 0x7fe12fa9d080>", |
|
"description": "Abaixo contém o conteúdo de tweets de usuarios do Twitter em português, sua tarefa é extrair qual a principal emoção dos textos. Responda com apenas uma das seguintes opções:\n Admiração, Diversão, Raiva, Aborrecimento, Aprovação, Compaixão, Confusão, Curiosidade, Desejo, Decepção, Desaprovação, Nojo, Vergonha, Inveja, Entusiasmo, Medo, Gratidão, Luto, Alegria, Saudade, Amor, Nervosismo, Otimismo, Orgulho, Alívio, Remorso, Tristeza ou Surpresa.\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": [ |
|
"Admiração", |
|
"Diversão", |
|
"Raiva", |
|
"Aborrecimento", |
|
"Aprovação", |
|
"Compaixão", |
|
"Confusão", |
|
"Curiosidade", |
|
"Desejo", |
|
"Decepção", |
|
"Desaprovação", |
|
"Nojo", |
|
" Vergonha", |
|
"Inveja", |
|
"Entusiasmo", |
|
"Medo", |
|
"Gratidão", |
|
"Luto", |
|
"Alegria", |
|
"Saudade", |
|
"Amor", |
|
"Nervosismo", |
|
"Otimismo", |
|
"Orgulho", |
|
"Alívio", |
|
"Remorso", |
|
"Tristeza", |
|
"Surpresa" |
|
] |
|
}, |
|
{ |
|
"function": "take_first" |
|
} |
|
] |
|
} |
|
], |
|
"should_decontaminate": false, |
|
"limit": 500, |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
}, |
|
"sparrow_hate-2019-fortuna-por": { |
|
"task": "sparrow_hate-2019-fortuna-por", |
|
"task_alias": "hate-2019-fortuna-por", |
|
"group": [ |
|
"pt_benchmark", |
|
"sparrow" |
|
], |
|
"dataset_path": "UBC-NLP/sparrow", |
|
"dataset_name": "hate-2019-fortuna-por", |
|
"test_split": "validation", |
|
"fewshot_split": "train", |
|
"doc_to_text": "Texto: {{content}}\nPergunta: O texto contém discurso de ódio?\nResposta:", |
|
"doc_to_target": "{{'Sim' if label == 'Hate' else 'Não'}}", |
|
"description": "Abaixo contém o conteúdo de tweets de usuarios do Twitter em português, sua tarefa é classificar se o texto contem discurso de ódio our não. Responda apenas com Sim ou Não.\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": [ |
|
"Sim", |
|
"Não" |
|
] |
|
}, |
|
{ |
|
"function": "take_first" |
|
} |
|
] |
|
} |
|
], |
|
"should_decontaminate": false, |
|
"limit": 500, |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
}, |
|
"sparrow_sentiment-2016-mozetic-por": { |
|
"task": "sparrow_sentiment-2016-mozetic-por", |
|
"task_alias": "sentiment-2016-mozetic-por", |
|
"group": [ |
|
"pt_benchmark", |
|
"sparrow" |
|
], |
|
"dataset_path": "UBC-NLP/sparrow", |
|
"dataset_name": "sentiment-2016-mozetic-por", |
|
"test_split": "validation", |
|
"fewshot_split": "train", |
|
"doc_to_text": "Texto: {{content}}\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 conteúdo de tweets de usuarios 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, |
|
"limit": 500, |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
}, |
|
"sparrow_sentiment-2018-brum-por": { |
|
"task": "sparrow_sentiment-2018-brum-por", |
|
"task_alias": "sentiment-2018-brum-por", |
|
"group": [ |
|
"pt_benchmark", |
|
"sparrow" |
|
], |
|
"dataset_path": "UBC-NLP/sparrow", |
|
"dataset_name": "sentiment-2018-brum-por", |
|
"test_split": "validation", |
|
"fewshot_split": "train", |
|
"doc_to_text": "Texto: {{content}}\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 conteúdo de tweets de usuarios 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, |
|
"limit": 500, |
|
"metadata": { |
|
"version": 1.0 |
|
} |
|
} |
|
}, |
|
"versions": { |
|
"assin2_rte": 1.0, |
|
"assin2_sts": 1.0, |
|
"bluex": 1.0, |
|
"enem_challenge": 1.0, |
|
"faquad_nli": 1.0, |
|
"oab_exams": 1.4, |
|
"sparrow_emotion-2021-cortiz-por": 1.0, |
|
"sparrow_hate-2019-fortuna-por": 1.0, |
|
"sparrow_sentiment-2016-mozetic-por": 1.0, |
|
"sparrow_sentiment-2018-brum-por": 1.0 |
|
}, |
|
"n-shot": { |
|
"assin2_rte": 15, |
|
"assin2_sts": 15, |
|
"bluex": 3, |
|
"enem_challenge": 3, |
|
"faquad_nli": 15, |
|
"oab_exams": 3, |
|
"sparrow_emotion-2021-cortiz-por": 25, |
|
"sparrow_hate-2019-fortuna-por": 25, |
|
"sparrow_sentiment-2016-mozetic-por": 25, |
|
"sparrow_sentiment-2018-brum-por": 25 |
|
}, |
|
"model_meta": { |
|
"truncated": 0, |
|
"non_truncated": 11889, |
|
"padded": 0, |
|
"non_padded": 11889, |
|
"fewshots_truncated": 0, |
|
"has_chat_template": false, |
|
"chat_type": null, |
|
"n_gpus": 1, |
|
"accelerate_num_process": null, |
|
"model_sha": "1d43a3b40d7d708d8084d07dfae0c4e9fd95c04f", |
|
"model_dtype": "torch.float16", |
|
"model_memory_footprint": 16014337056, |
|
"model_num_parameters": 7868755968, |
|
"model_is_loaded_in_4bit": false, |
|
"model_is_loaded_in_8bit": false, |
|
"model_is_quantized": null, |
|
"model_device": "cuda:1", |
|
"batch_size": 8, |
|
"max_length": 4096, |
|
"max_ctx_length": 4064, |
|
"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": 1259.0061274509803, |
|
"min_seq_length": 1236, |
|
"max_seq_length": 1325, |
|
"max_ctx_length": 4064, |
|
"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": 1392.0061274509803, |
|
"min_seq_length": 1369, |
|
"max_seq_length": 1458, |
|
"max_ctx_length": 4064, |
|
"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": 1324.076495132128, |
|
"min_seq_length": 953, |
|
"max_seq_length": 2108, |
|
"max_ctx_length": 4064, |
|
"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": 1542.0517844646606, |
|
"min_seq_length": 1291, |
|
"max_seq_length": 2503, |
|
"max_ctx_length": 4064, |
|
"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": 1540.8153846153846, |
|
"min_seq_length": 1487, |
|
"max_seq_length": 1650, |
|
"max_ctx_length": 4064, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 15.0, |
|
"mean_effective_fewshot_size": 15.0 |
|
}, |
|
"oab_exams": { |
|
"sample_size": 2195, |
|
"truncated": 0, |
|
"non_truncated": 2195, |
|
"padded": 0, |
|
"non_padded": 2195, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1324.5503416856493, |
|
"min_seq_length": 1061, |
|
"max_seq_length": 1789, |
|
"max_ctx_length": 4064, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 3.0, |
|
"mean_effective_fewshot_size": 3.0 |
|
}, |
|
"sparrow_emotion-2021-cortiz-por": { |
|
"sample_size": 500, |
|
"truncated": 0, |
|
"non_truncated": 500, |
|
"padded": 0, |
|
"non_padded": 500, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1744.524, |
|
"min_seq_length": 1723, |
|
"max_seq_length": 1777, |
|
"max_ctx_length": 4064, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 25.0, |
|
"mean_effective_fewshot_size": 25.0 |
|
}, |
|
"sparrow_hate-2019-fortuna-por": { |
|
"sample_size": 500, |
|
"truncated": 0, |
|
"non_truncated": 500, |
|
"padded": 0, |
|
"non_padded": 500, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1716.684, |
|
"min_seq_length": 1693, |
|
"max_seq_length": 1754, |
|
"max_ctx_length": 4064, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 25.0, |
|
"mean_effective_fewshot_size": 25.0 |
|
}, |
|
"sparrow_sentiment-2016-mozetic-por": { |
|
"sample_size": 500, |
|
"truncated": 0, |
|
"non_truncated": 500, |
|
"padded": 0, |
|
"non_padded": 500, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1425.294, |
|
"min_seq_length": 1408, |
|
"max_seq_length": 1461, |
|
"max_ctx_length": 4064, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 25.0, |
|
"mean_effective_fewshot_size": 25.0 |
|
}, |
|
"sparrow_sentiment-2018-brum-por": { |
|
"sample_size": 500, |
|
"truncated": 0, |
|
"non_truncated": 500, |
|
"padded": 0, |
|
"non_padded": 500, |
|
"fewshots_truncated": 0, |
|
"mean_seq_length": 1577.602, |
|
"min_seq_length": 1560, |
|
"max_seq_length": 1607, |
|
"max_ctx_length": 4064, |
|
"max_gen_toks": 32, |
|
"mean_original_fewshots_size": 25.0, |
|
"mean_effective_fewshot_size": 25.0 |
|
} |
|
}, |
|
"config": { |
|
"model": "huggingface", |
|
"model_args": "pretrained=stabilityai/stablelm-base-alpha-7b,dtype=float16,device=cuda:1,revision=main,trust_remote_code=True,starting_max_length=4096", |
|
"batch_size": "auto", |
|
"batch_sizes": [], |
|
"device": null, |
|
"use_cache": null, |
|
"limit": [ |
|
null, |
|
null, |
|
null, |
|
null, |
|
null, |
|
null, |
|
500.0, |
|
500.0, |
|
500.0, |
|
500.0 |
|
], |
|
"bootstrap_iters": 0, |
|
"gen_kwargs": null |
|
}, |
|
"git_hash": "15f86b5" |
|
} |