{ "results": { "assin2_rte": { "f1_macro,all": 0.3333333333333333, "acc,all": 0.5, "alias": "assin2_rte" }, "assin2_sts": { "pearson,all": 0.07703722378109175, "mse,all": 2.5286274509803923, "alias": "assin2_sts" }, "bluex": { "acc,all": 0.2614742698191933, "acc,exam_id__USP_2021": 0.23076923076923078, "acc,exam_id__UNICAMP_2018": 0.2777777777777778, "acc,exam_id__UNICAMP_2021_1": 0.32608695652173914, "acc,exam_id__UNICAMP_2022": 0.3076923076923077, "acc,exam_id__USP_2020": 0.30357142857142855, "acc,exam_id__UNICAMP_2021_2": 0.29411764705882354, "acc,exam_id__UNICAMP_2023": 0.4883720930232558, "acc,exam_id__UNICAMP_2020": 0.18181818181818182, "acc,exam_id__UNICAMP_2019": 0.2, "acc,exam_id__USP_2019": 0.325, "acc,exam_id__USP_2022": 0.24489795918367346, "acc,exam_id__USP_2024": 0.14634146341463414, "acc,exam_id__USP_2023": 0.18181818181818182, "acc,exam_id__USP_2018": 0.18518518518518517, "acc,exam_id__UNICAMP_2024": 0.26666666666666666, "alias": "bluex" }, "enem_challenge": { "alias": "enem", "acc,all": 0.2365290412876137, "acc,exam_id__2016": 0.23140495867768596, "acc,exam_id__2015": 0.19327731092436976, "acc,exam_id__2017": 0.2413793103448276, "acc,exam_id__2010": 0.1794871794871795, "acc,exam_id__2023": 0.25925925925925924, "acc,exam_id__2013": 0.2222222222222222, "acc,exam_id__2009": 0.2782608695652174, "acc,exam_id__2022": 0.24812030075187969, "acc,exam_id__2014": 0.1926605504587156, "acc,exam_id__2016_2": 0.22764227642276422, "acc,exam_id__2011": 0.2222222222222222, "acc,exam_id__2012": 0.33620689655172414 }, "faquad_nli": { "f1_macro,all": 0.5548892542799111, "acc,all": 0.7276923076923076, "alias": "faquad_nli" }, "oab_exams": { "acc,all": 0.2742596810933941, "acc,exam_id__2012-08": 0.2875, "acc,exam_id__2013-10": 0.2125, "acc,exam_id__2012-06a": 0.2, "acc,exam_id__2012-06": 0.2875, "acc,exam_id__2015-17": 0.3333333333333333, "acc,exam_id__2016-21": 0.3, "acc,exam_id__2011-03": 0.2727272727272727, "acc,exam_id__2017-23": 0.325, "acc,exam_id__2012-09": 0.15584415584415584, "acc,exam_id__2013-11": 0.3, "acc,exam_id__2017-24": 0.2875, "acc,exam_id__2011-04": 0.3125, "acc,exam_id__2014-15": 0.3333333333333333, "acc,exam_id__2013-12": 0.2, "acc,exam_id__2010-02": 0.34, "acc,exam_id__2016-20": 0.2375, "acc,exam_id__2017-22": 0.3, "acc,exam_id__2015-18": 0.275, "acc,exam_id__2010-01": 0.27058823529411763, "acc,exam_id__2018-25": 0.3, "acc,exam_id__2014-14": 0.2375, "acc,exam_id__2014-13": 0.275, "acc,exam_id__2012-07": 0.25, "acc,exam_id__2016-19": 0.3076923076923077, "acc,exam_id__2016-20a": 0.25, "acc,exam_id__2015-16": 0.2625, "acc,exam_id__2011-05": 0.275, "alias": "oab_exams" }, "sparrow_emotion-2021-cortiz-por": { "alias": "emotion-2021-cortiz-por", "f1_macro,all": 0.08365150307457563, "acc,all": 0.142 }, "sparrow_hate-2019-fortuna-por": { "alias": "hate-2019-fortuna-por", "f1_macro,all": 0.5377762837213211, "acc,all": 0.538 }, "sparrow_sentiment-2016-mozetic-por": { "alias": "sentiment-2016-mozetic-por", "f1_macro,all": 0.42328641755398966, "acc,all": 0.638 }, "sparrow_sentiment-2018-brum-por": { "alias": "sentiment-2018-brum-por", "f1_macro,all": 0.32817916935199615, "acc,all": 0.372 } }, "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": "", "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": "", "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])$", "\\b([ABCDE])\\b" ] }, { "function": "take_first" } ], "group_by": { "column": "exam_id" } } ], "should_decontaminate": true, "doc_to_decontamination_query": "", "metadata": { "version": 1.0 } }, "enem_challenge": { "task": "enem_challenge", "task_alias": "enem", "group": [ "pt_benchmark", "vestibular" ], "dataset_path": "eduagarcia/enem_challenge", "test_split": "train", "fewshot_split": "train", "doc_to_text": "", "doc_to_target": "{{answerKey}}", "description": "As perguntas a seguir são questões de multipla escolha do Exame Nacional do Ensino Médio (ENEM), reponda apenas com as letras A, B, C, D ou E.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "id_sampler", "sampler_config": { "id_list": [ "2022_21", "2022_88", "2022_143" ], "id_column": "id", "exclude_from_task": true } }, "num_fewshot": 3, "metric_list": [ { "metric": "acc", "aggregation": "acc", "higher_is_better": true } ], "output_type": "generate_until", "generation_kwargs": { "max_gen_toks": 32, "do_sample": false, "temperature": 0.0, "top_k": null, "top_p": null, "until": [ "\n\n" ] }, "repeats": 1, "filter_list": [ { "name": "all", "filter": [ { "function": "normalize_spaces" }, { "function": "remove_accents" }, { "function": "find_choices", "choices": [ "A", "B", "C", "D", "E" ], "regex_patterns": [ "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta[Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b", "\\b([ABCDE])\\.", "\\b([ABCDE]) ?[.):-]", "\\b([ABCDE])$", "\\b([ABCDE])\\b" ] }, { "function": "take_first" } ], "group_by": { "column": "exam_id" } } ], "should_decontaminate": true, "doc_to_decontamination_query": "", "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": "", "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": "", "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": "", "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": 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": [ "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": 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, "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": 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": [ "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. 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