llm_pt_leaderboard_raw_results
/
HuggingFaceTB
/cosmo-1b
/raw_2024-02-26T18-03-06.542808
/results.json
{ | |
"results": { | |
"assin2_rte": { | |
"f1_macro,all": 0.5526600270022243, | |
"acc,all": 0.553921568627451, | |
"alias": "assin2_rte" | |
}, | |
"assin2_sts": { | |
"pearson,all": 0.07330211383402985, | |
"mse,all": 2.5634150326797394, | |
"alias": "assin2_sts" | |
}, | |
"bluex": { | |
"acc,all": 0.20723226703755215, | |
"acc,exam_id__USP_2024": 0.14634146341463414, | |
"acc,exam_id__USP_2020": 0.21428571428571427, | |
"acc,exam_id__USP_2018": 0.16666666666666666, | |
"acc,exam_id__UNICAMP_2018": 0.24074074074074073, | |
"acc,exam_id__UNICAMP_2021_1": 0.30434782608695654, | |
"acc,exam_id__USP_2023": 0.11363636363636363, | |
"acc,exam_id__UNICAMP_2022": 0.23076923076923078, | |
"acc,exam_id__UNICAMP_2019": 0.18, | |
"acc,exam_id__UNICAMP_2024": 0.28888888888888886, | |
"acc,exam_id__UNICAMP_2021_2": 0.13725490196078433, | |
"acc,exam_id__UNICAMP_2020": 0.18181818181818182, | |
"acc,exam_id__USP_2022": 0.16326530612244897, | |
"acc,exam_id__USP_2021": 0.15384615384615385, | |
"acc,exam_id__UNICAMP_2023": 0.3488372093023256, | |
"acc,exam_id__USP_2019": 0.275, | |
"alias": "bluex" | |
}, | |
"enem_challenge": { | |
"alias": "enem", | |
"acc,all": 0.20783764870538837, | |
"acc,exam_id__2011": 0.26495726495726496, | |
"acc,exam_id__2016": 0.19834710743801653, | |
"acc,exam_id__2012": 0.23275862068965517, | |
"acc,exam_id__2015": 0.18487394957983194, | |
"acc,exam_id__2010": 0.13675213675213677, | |
"acc,exam_id__2023": 0.25925925925925924, | |
"acc,exam_id__2017": 0.19827586206896552, | |
"acc,exam_id__2013": 0.17592592592592593, | |
"acc,exam_id__2014": 0.2018348623853211, | |
"acc,exam_id__2009": 0.23478260869565218, | |
"acc,exam_id__2016_2": 0.21951219512195122, | |
"acc,exam_id__2022": 0.18045112781954886 | |
}, | |
"faquad_nli": { | |
"f1_macro,all": 0.4396551724137931, | |
"acc,all": 0.7846153846153846, | |
"alias": "faquad_nli" | |
}, | |
"hatebr_offensive": { | |
"alias": "hatebr_offensive_binary", | |
"f1_macro,all": 0.3411338879766024, | |
"acc,all": 0.5007142857142857 | |
}, | |
"oab_exams": { | |
"acc,all": 0.23234624145785876, | |
"acc,exam_id__2012-07": 0.15, | |
"acc,exam_id__2012-09": 0.23376623376623376, | |
"acc,exam_id__2015-16": 0.225, | |
"acc,exam_id__2011-03": 0.24242424242424243, | |
"acc,exam_id__2010-02": 0.25, | |
"acc,exam_id__2012-08": 0.225, | |
"acc,exam_id__2012-06a": 0.25, | |
"acc,exam_id__2014-15": 0.21794871794871795, | |
"acc,exam_id__2017-22": 0.25, | |
"acc,exam_id__2016-19": 0.20512820512820512, | |
"acc,exam_id__2010-01": 0.25882352941176473, | |
"acc,exam_id__2016-20a": 0.3125, | |
"acc,exam_id__2014-14": 0.25, | |
"acc,exam_id__2014-13": 0.2375, | |
"acc,exam_id__2016-20": 0.225, | |
"acc,exam_id__2015-17": 0.24358974358974358, | |
"acc,exam_id__2011-05": 0.2375, | |
"acc,exam_id__2013-11": 0.175, | |
"acc,exam_id__2012-06": 0.2375, | |
"acc,exam_id__2013-12": 0.175, | |
"acc,exam_id__2011-04": 0.275, | |
"acc,exam_id__2013-10": 0.2125, | |
"acc,exam_id__2017-24": 0.225, | |
"acc,exam_id__2016-21": 0.2125, | |
"acc,exam_id__2017-23": 0.2125, | |
"acc,exam_id__2015-18": 0.2375, | |
"acc,exam_id__2018-25": 0.2875, | |
"alias": "oab_exams" | |
}, | |
"portuguese_hate_speech": { | |
"alias": "portuguese_hate_speech_binary", | |
"f1_macro,all": 0.24442150902068246, | |
"acc,all": 0.30552291421856637 | |
}, | |
"tweetsentbr": { | |
"f1_macro,all": 0.2534405090147715, | |
"acc,all": 0.32587064676616917, | |
"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 0x7f3c5e349120>", | |
"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 0x7f3c5e348ae0>", | |
"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 0x7f3c5e348d60>", | |
"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 0x7f3c5e349300>", | |
"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 0x7f3c5e349580>", | |
"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 0x7f3c5e3484a0>", | |
"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 0x7f3c5e348720>", | |
"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-temp/tweetsentbr", | |
"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": "id_sampler", | |
"sampler_config": { | |
"id_list": [ | |
"862006098672459776", | |
"861612241703063552", | |
"861833257087848448", | |
"861283345476571138", | |
"861283000335695873", | |
"862139461274152962", | |
"862139468702265344", | |
"862006107702734848", | |
"862004354458537984", | |
"861833322925883392", | |
"861603063190171648", | |
"862139462716989440", | |
"862005877355810818", | |
"861751885862244353", | |
"862045180261695489", | |
"862004252499226630", | |
"862023970828292097", | |
"862041752127107074", | |
"862034961863503872", | |
"861293756548608001", | |
"861993527575695360", | |
"862003099355021315", | |
"862002404086206467", | |
"861282989602463744", | |
"862139454399668229", | |
"862139463769743361", | |
"862054906689138688", | |
"862139446535360513", | |
"861997363744911361", | |
"862057988898648065", | |
"861329080083521536", | |
"861286289034838016", | |
"861833050526806017", | |
"861300658565255169", | |
"861989003821813760", | |
"861682750398631938", | |
"861283275716907008", | |
"861283402523267072", | |
"861873108147466240", | |
"862139462138171392", | |
"861284090271715333", | |
"862139446149427201", | |
"861629109331525633", | |
"861721698609098753", | |
"862139453124612096", | |
"861283339482914816", | |
"861282466291748867", | |
"862055346759749632", | |
"862003019860389891", | |
"862140698346344449", | |
"862084376280092672", | |
"862003058708017152", | |
"862000677345787904", | |
"862029129310502913", | |
"862005822376882178", | |
"861969836297134085", | |
"861302955361927168", | |
"862064949451005953", | |
"861282589541355520", | |
"862005476858486784", | |
"862004684411850757", | |
"862139471101349890", | |
"862139467146170368", | |
"862139475098558465", | |
"862140706550403072", | |
"861282777001537536", | |
"862003184147079169", | |
"861283410656059394", | |
"861283417857691649", | |
"861888778922856448", | |
"861655860812099585", | |
"861834248063504384", | |
"862005210935382017", | |
"861282716930760704", | |
"861287082433622022" | |
], | |
"id_column": "id" | |
} | |
}, | |
"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": 85, | |
"non_truncated": 14065, | |
"padded": 0, | |
"non_padded": 14150, | |
"fewshots_truncated": 102, | |
"has_chat_template": false, | |
"chat_type": null, | |
"n_gpus": 1, | |
"accelerate_num_process": null, | |
"model_sha": "0d5e341cfe835dffc81b6186f9715c094889f8ce", | |
"model_dtype": "torch.float16", | |
"model_memory_footprint": 3517130752, | |
"model_num_parameters": 1741785088, | |
"model_is_loaded_in_4bit": null, | |
"model_is_loaded_in_8bit": null, | |
"model_is_quantized": null, | |
"model_device": "cuda:0", | |
"batch_size": 64, | |
"max_length": 2048, | |
"max_ctx_length": 2016, | |
"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": 1369.7455065359477, | |
"min_seq_length": 1346, | |
"max_seq_length": 1436, | |
"max_ctx_length": 2016, | |
"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": 1593.7455065359477, | |
"min_seq_length": 1570, | |
"max_seq_length": 1660, | |
"max_ctx_length": 2016, | |
"max_gen_toks": 32, | |
"mean_original_fewshots_size": 15.0, | |
"mean_effective_fewshot_size": 15.0 | |
}, | |
"bluex": { | |
"sample_size": 719, | |
"truncated": 59, | |
"non_truncated": 660, | |
"padded": 0, | |
"non_padded": 719, | |
"fewshots_truncated": 74, | |
"mean_seq_length": 1719.9262865090404, | |
"min_seq_length": 1343, | |
"max_seq_length": 2520, | |
"max_ctx_length": 2016, | |
"max_gen_toks": 32, | |
"mean_original_fewshots_size": 3.0, | |
"mean_effective_fewshot_size": 2.8970792767732965 | |
}, | |
"enem_challenge": { | |
"sample_size": 1429, | |
"truncated": 26, | |
"non_truncated": 1403, | |
"padded": 0, | |
"non_padded": 1429, | |
"fewshots_truncated": 28, | |
"mean_seq_length": 1620.039188243527, | |
"min_seq_length": 1354, | |
"max_seq_length": 2618, | |
"max_ctx_length": 2016, | |
"max_gen_toks": 32, | |
"mean_original_fewshots_size": 3.0, | |
"mean_effective_fewshot_size": 2.980405878236529 | |
}, | |
"faquad_nli": { | |
"sample_size": 650, | |
"truncated": 0, | |
"non_truncated": 650, | |
"padded": 0, | |
"non_padded": 650, | |
"fewshots_truncated": 0, | |
"mean_seq_length": 1594.9876923076922, | |
"min_seq_length": 1539, | |
"max_seq_length": 1715, | |
"max_ctx_length": 2016, | |
"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": 1305.3878571428572, | |
"min_seq_length": 1282, | |
"max_seq_length": 1556, | |
"max_ctx_length": 2016, | |
"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": 1365.764464692483, | |
"min_seq_length": 1099, | |
"max_seq_length": 1868, | |
"max_ctx_length": 2016, | |
"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": 1806.3360752056403, | |
"min_seq_length": 1771, | |
"max_seq_length": 1845, | |
"max_ctx_length": 2016, | |
"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": 1552.2492537313433, | |
"min_seq_length": 1531, | |
"max_seq_length": 1647, | |
"max_ctx_length": 2016, | |
"max_gen_toks": 32, | |
"mean_original_fewshots_size": 25.0, | |
"mean_effective_fewshot_size": 25.0 | |
} | |
}, | |
"config": { | |
"model": "huggingface", | |
"model_args": "pretrained=HuggingFaceTB/cosmo-1b,dtype=float16,device=cuda:0,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, | |
null, | |
null, | |
null | |
], | |
"bootstrap_iters": 0, | |
"gen_kwargs": null | |
}, | |
"git_hash": "804df15" | |
} |