| { | |
| "results": { | |
| "assin2_rte": { | |
| "f1_macro,all": 0.4883903675731297, | |
| "acc,all": 0.5506535947712419, | |
| "alias": "assin2_rte" | |
| }, | |
| "assin2_sts": { | |
| "pearson,all": 0.3755961900599195, | |
| "mse,all": 1.5730269607843137, | |
| "alias": "assin2_sts" | |
| }, | |
| "bluex": { | |
| "acc,all": 0.29207232267037553, | |
| "acc,exam_id__UNICAMP_2020": 0.3090909090909091, | |
| "acc,exam_id__UNICAMP_2021_2": 0.4117647058823529, | |
| "acc,exam_id__USP_2018": 0.2222222222222222, | |
| "acc,exam_id__UNICAMP_2023": 0.32558139534883723, | |
| "acc,exam_id__USP_2024": 0.2926829268292683, | |
| "acc,exam_id__UNICAMP_2021_1": 0.1956521739130435, | |
| "acc,exam_id__USP_2020": 0.25, | |
| "acc,exam_id__USP_2019": 0.3, | |
| "acc,exam_id__USP_2023": 0.13636363636363635, | |
| "acc,exam_id__UNICAMP_2019": 0.34, | |
| "acc,exam_id__USP_2022": 0.14285714285714285, | |
| "acc,exam_id__UNICAMP_2024": 0.4222222222222222, | |
| "acc,exam_id__USP_2021": 0.28846153846153844, | |
| "acc,exam_id__UNICAMP_2022": 0.38461538461538464, | |
| "acc,exam_id__UNICAMP_2018": 0.37037037037037035, | |
| "alias": "bluex" | |
| }, | |
| "enem_challenge": { | |
| "alias": "enem", | |
| "acc,all": 0.21623512946116166, | |
| "acc,exam_id__2023": 0.21481481481481482, | |
| "acc,exam_id__2010": 0.23076923076923078, | |
| "acc,exam_id__2016_2": 0.21951219512195122, | |
| "acc,exam_id__2011": 0.23076923076923078, | |
| "acc,exam_id__2022": 0.21804511278195488, | |
| "acc,exam_id__2015": 0.20168067226890757, | |
| "acc,exam_id__2013": 0.23148148148148148, | |
| "acc,exam_id__2014": 0.21100917431192662, | |
| "acc,exam_id__2009": 0.14782608695652175, | |
| "acc,exam_id__2016": 0.23140495867768596, | |
| "acc,exam_id__2012": 0.25862068965517243, | |
| "acc,exam_id__2017": 0.19827586206896552 | |
| }, | |
| "faquad_nli": { | |
| "f1_macro,all": 0.4396551724137931, | |
| "acc,all": 0.7846153846153846, | |
| "alias": "faquad_nli" | |
| }, | |
| "hatebr_offensive": { | |
| "alias": "hatebr_offensive_binary", | |
| "f1_macro,all": 0.8499559054089365, | |
| "acc,all": 0.85 | |
| }, | |
| "oab_exams": { | |
| "acc,all": 0.2715261958997722, | |
| "acc,exam_id__2016-20": 0.3625, | |
| "acc,exam_id__2015-17": 0.21794871794871795, | |
| "acc,exam_id__2014-13": 0.2125, | |
| "acc,exam_id__2018-25": 0.2625, | |
| "acc,exam_id__2017-22": 0.2375, | |
| "acc,exam_id__2014-14": 0.2375, | |
| "acc,exam_id__2013-11": 0.325, | |
| "acc,exam_id__2015-18": 0.3, | |
| "acc,exam_id__2011-05": 0.3375, | |
| "acc,exam_id__2012-08": 0.225, | |
| "acc,exam_id__2012-06a": 0.3125, | |
| "acc,exam_id__2017-24": 0.2625, | |
| "acc,exam_id__2012-07": 0.325, | |
| "acc,exam_id__2016-20a": 0.2125, | |
| "acc,exam_id__2016-21": 0.25, | |
| "acc,exam_id__2016-19": 0.38461538461538464, | |
| "acc,exam_id__2010-01": 0.27058823529411763, | |
| "acc,exam_id__2011-04": 0.275, | |
| "acc,exam_id__2012-06": 0.2375, | |
| "acc,exam_id__2017-23": 0.3, | |
| "acc,exam_id__2012-09": 0.2597402597402597, | |
| "acc,exam_id__2013-12": 0.275, | |
| "acc,exam_id__2013-10": 0.2375, | |
| "acc,exam_id__2011-03": 0.21212121212121213, | |
| "acc,exam_id__2015-16": 0.3, | |
| "acc,exam_id__2010-02": 0.3, | |
| "acc,exam_id__2014-15": 0.20512820512820512, | |
| "alias": "oab_exams" | |
| }, | |
| "portuguese_hate_speech": { | |
| "alias": "portuguese_hate_speech_binary", | |
| "f1_macro,all": 0.6742912511607251, | |
| "acc,all": 0.7215041128084606 | |
| }, | |
| "tweetsentbr": { | |
| "f1_macro,all": 0.4037922571146918, | |
| "acc,all": 0.6228855721393035, | |
| "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": [ | |
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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 0x7f8e52c3d8a0>", | |
| "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, | |
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| 5, | |
| 6, | |
| 3253, | |
| 7, | |
| 3254, | |
| 3255, | |
| 3256, | |
| 8, | |
| 9, | |
| 10, | |
| 3257, | |
| 11, | |
| 3258, | |
| 12, | |
| 13, | |
| 14, | |
| 15, | |
| 3259, | |
| 3260, | |
| 3261, | |
| 3262, | |
| 3263, | |
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| 24, | |
| 25, | |
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| ], | |
| "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 0x7f8e52c3d260>", | |
| "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 0x7f8e52c3d4e0>", | |
| "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 0x7f8e52c3da80>", | |
| "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 0x7f8e52c3dd00>", | |
| "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, | |
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| 663, | |
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| 2227, | |
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| 974, | |
| 558, | |
| 1503, | |
| 1958, | |
| 2918, | |
| 601, | |
| 1560, | |
| 984, | |
| 2388, | |
| 995, | |
| 2233, | |
| 1982, | |
| 165, | |
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| 1312, | |
| 2285, | |
| 522, | |
| 1113, | |
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| 2022, | |
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| ] | |
| } | |
| }, | |
| "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": { | |
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