{ "results": { "assin2_rte": { "f1_macro,all": 0.6307200282684031, "acc,all": 0.670751633986928, "alias": "assin2_rte" }, "assin2_sts": { "pearson,all": 0.5853055022861218, "mse,all": 1.5015236928104576, "alias": "assin2_sts" }, "bluex": { "acc,all": 0.5702364394993046, "acc,exam_id__UNICAMP_2022": 0.6410256410256411, "acc,exam_id__UNICAMP_2019": 0.62, "acc,exam_id__UNICAMP_2023": 0.6511627906976745, "acc,exam_id__UNICAMP_2018": 0.5185185185185185, "acc,exam_id__UNICAMP_2020": 0.5818181818181818, "acc,exam_id__USP_2024": 0.6829268292682927, "acc,exam_id__UNICAMP_2021_2": 0.5294117647058824, "acc,exam_id__USP_2022": 0.5918367346938775, "acc,exam_id__USP_2019": 0.475, "acc,exam_id__USP_2021": 0.5576923076923077, "acc,exam_id__USP_2023": 0.6363636363636364, "acc,exam_id__UNICAMP_2021_1": 0.5869565217391305, "acc,exam_id__UNICAMP_2024": 0.5555555555555556, "acc,exam_id__USP_2020": 0.5714285714285714, "acc,exam_id__USP_2018": 0.4074074074074074, "alias": "bluex" }, "enem_challenge": { "alias": "enem", "acc,all": 0.6627011896431071, "acc,exam_id__2015": 0.680672268907563, "acc,exam_id__2012": 0.6810344827586207, "acc,exam_id__2017": 0.6810344827586207, "acc,exam_id__2009": 0.6521739130434783, "acc,exam_id__2023": 0.6148148148148148, "acc,exam_id__2016_2": 0.6585365853658537, "acc,exam_id__2010": 0.6410256410256411, "acc,exam_id__2014": 0.6788990825688074, "acc,exam_id__2013": 0.6574074074074074, "acc,exam_id__2022": 0.6541353383458647, "acc,exam_id__2011": 0.7094017094017094, "acc,exam_id__2016": 0.6528925619834711 }, "faquad_nli": { "f1_macro,all": 0.4396551724137931, "acc,all": 0.7846153846153846, "alias": "faquad_nli" }, "oab_exams": { "acc,all": 0.47289293849658315, "acc,exam_id__2012-06a": 0.4875, "acc,exam_id__2015-17": 0.5384615384615384, "acc,exam_id__2012-06": 0.4625, "acc,exam_id__2014-15": 0.5641025641025641, "acc,exam_id__2016-20": 0.5, "acc,exam_id__2013-10": 0.4375, "acc,exam_id__2012-07": 0.4625, "acc,exam_id__2011-03": 0.5151515151515151, "acc,exam_id__2011-05": 0.475, "acc,exam_id__2016-19": 0.47435897435897434, "acc,exam_id__2017-23": 0.475, "acc,exam_id__2017-22": 0.525, "acc,exam_id__2018-25": 0.4125, "acc,exam_id__2014-13": 0.375, "acc,exam_id__2017-24": 0.45, "acc,exam_id__2010-01": 0.3764705882352941, "acc,exam_id__2014-14": 0.475, "acc,exam_id__2011-04": 0.4375, "acc,exam_id__2013-12": 0.525, "acc,exam_id__2015-16": 0.475, "acc,exam_id__2016-21": 0.4625, "acc,exam_id__2013-11": 0.5375, "acc,exam_id__2012-08": 0.5, "acc,exam_id__2016-20a": 0.3625, "acc,exam_id__2012-09": 0.37662337662337664, "acc,exam_id__2010-02": 0.54, "acc,exam_id__2015-18": 0.525, "alias": "oab_exams" }, "sparrow_emotion-2021-cortiz-por": { "alias": "emotion-2021-cortiz-por", "f1_macro,all": 0.08636098823540275, "acc,all": 0.154 }, "sparrow_hate-2019-fortuna-por": { "alias": "hate-2019-fortuna-por", "f1_macro,all": 0.4173441734417344, "acc,all": 0.656 }, "sparrow_sentiment-2016-mozetic-por": { "alias": "sentiment-2016-mozetic-por", "f1_macro,all": 0.4332192120249312, "acc,all": 0.64 }, "sparrow_sentiment-2018-brum-por": { "alias": "sentiment-2018-brum-por", "f1_macro,all": 0.3507029531559711, "acc,all": 0.404 } }, "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": 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": "977747da7d30fc0c59d6a8778abbb7967c32bad5", "model_dtype": "torch.bfloat16", "model_memory_footprint": 29081303040, "model_num_parameters": 14498703360, "model_is_loaded_in_4bit": false, "model_is_loaded_in_8bit": false, "model_is_quantized": null, "model_device": "cuda:0", "batch_size": 4, "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": 1438.0081699346406, "min_seq_length": 1411, "max_seq_length": 1520, "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": 1490.0081699346406, "min_seq_length": 1463, "max_seq_length": 1572, "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": 1498.164116828929, "min_seq_length": 1054, "max_seq_length": 2456, "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": 1843.518544436669, "min_seq_length": 1518, "max_seq_length": 3121, "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": 1895.2184615384615, "min_seq_length": 1829, "max_seq_length": 2052, "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": 1656.2997722095672, "min_seq_length": 1326, "max_seq_length": 2280, "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": 1974.364, "min_seq_length": 1948, "max_seq_length": 2013, "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": 1973.182, "min_seq_length": 1945, "max_seq_length": 2012, "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": 1788.404, "min_seq_length": 1768, "max_seq_length": 1828, "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": 1967.69, "min_seq_length": 1947, "max_seq_length": 2009, "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=OrionStarAI/Orion-14B-Base,dtype=bfloat16,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, 500.0, 500.0, 500.0, 500.0 ], "bootstrap_iters": 0, "gen_kwargs": null }, "git_hash": "15f86b5" }