| { | |
| "results": { | |
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| "f1_macro,all": 0.6950181531654831, | |
| "acc,all": 0.7181372549019608, | |
| "alias": "assin2_rte" | |
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| "assin2_sts": { | |
| "pearson,all": 0.5337084187331966, | |
| "mse,all": 1.683774509803922, | |
| "alias": "assin2_sts" | |
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| "bluex": { | |
| "acc,all": 0.6244784422809457, | |
| "acc,exam_id__UNICAMP_2019": 0.6, | |
| "acc,exam_id__UNICAMP_2023": 0.6046511627906976, | |
| "acc,exam_id__UNICAMP_2021_1": 0.6304347826086957, | |
| "acc,exam_id__UNICAMP_2021_2": 0.5686274509803921, | |
| "acc,exam_id__USP_2021": 0.6346153846153846, | |
| "acc,exam_id__UNICAMP_2024": 0.6444444444444445, | |
| "acc,exam_id__UNICAMP_2020": 0.5636363636363636, | |
| "acc,exam_id__USP_2023": 0.75, | |
| "acc,exam_id__USP_2024": 0.8048780487804879, | |
| "acc,exam_id__UNICAMP_2018": 0.5370370370370371, | |
| "acc,exam_id__USP_2019": 0.6, | |
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| "enem_challenge": { | |
| "alias": "enem", | |
| "acc,all": 0.7333799860041987, | |
| "acc,exam_id__2011": 0.7948717948717948, | |
| "acc,exam_id__2013": 0.6944444444444444, | |
| "acc,exam_id__2017": 0.7068965517241379, | |
| "acc,exam_id__2009": 0.7130434782608696, | |
| "acc,exam_id__2012": 0.7586206896551724, | |
| "acc,exam_id__2010": 0.7521367521367521, | |
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| "acc,exam_id__2016": 0.7107438016528925, | |
| "acc,exam_id__2022": 0.6992481203007519, | |
| "acc,exam_id__2015": 0.773109243697479, | |
| "acc,exam_id__2014": 0.7247706422018348, | |
| "acc,exam_id__2016_2": 0.7235772357723578 | |
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| "faquad_nli": { | |
| "f1_macro,all": 0.6754332808144468, | |
| "acc,all": 0.8415384615384616, | |
| "alias": "faquad_nli" | |
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| "oab_exams": { | |
| "acc,all": 0.532118451025057, | |
| "acc,exam_id__2017-23": 0.4875, | |
| "acc,exam_id__2010-01": 0.4235294117647059, | |
| "acc,exam_id__2014-14": 0.5875, | |
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| "acc,exam_id__2012-09": 0.37662337662337664, | |
| "acc,exam_id__2012-07": 0.5375, | |
| "acc,exam_id__2018-25": 0.475, | |
| "acc,exam_id__2012-06": 0.525, | |
| "acc,exam_id__2016-21": 0.55, | |
| "acc,exam_id__2016-20": 0.575, | |
| "acc,exam_id__2012-08": 0.475, | |
| "acc,exam_id__2013-12": 0.575, | |
| "acc,exam_id__2012-06a": 0.5625, | |
| "acc,exam_id__2013-10": 0.6125, | |
| "acc,exam_id__2015-17": 0.6410256410256411, | |
| "acc,exam_id__2014-13": 0.55, | |
| "acc,exam_id__2016-20a": 0.55, | |
| "acc,exam_id__2015-18": 0.5375, | |
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| "acc,exam_id__2011-05": 0.625, | |
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| "acc,exam_id__2010-02": 0.56, | |
| "acc,exam_id__2016-19": 0.5, | |
| "alias": "oab_exams" | |
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| "sparrow_emotion-2021-cortiz-por": { | |
| "alias": "emotion-2021-cortiz-por", | |
| "f1_macro,all": 0.08852743450201345, | |
| "acc,all": 0.142 | |
| }, | |
| "sparrow_hate-2019-fortuna-por": { | |
| "alias": "hate-2019-fortuna-por", | |
| "f1_macro,all": 0.510894817930596, | |
| "acc,all": 0.68 | |
| }, | |
| "sparrow_sentiment-2016-mozetic-por": { | |
| "alias": "sentiment-2016-mozetic-por", | |
| "f1_macro,all": 0.5224209601499515, | |
| "acc,all": 0.592 | |
| }, | |
| "sparrow_sentiment-2018-brum-por": { | |
| "alias": "sentiment-2018-brum-por", | |
| "f1_macro,all": 0.3457602858046176, | |
| "acc,all": 0.396 | |
| } | |
| }, | |
| "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", | |
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| "id_column": "sentence_pair_id" | |
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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": [ | |
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| "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 0x7f3050fdd800>", | |
| "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": [ | |
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| "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": [ | |
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| ] | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
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| "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 0x7f3050fdd1c0>", | |
| "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 0x7f3050fdd440>", | |
| "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 0x7f3050fdd9e0>", | |
| "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 0x7f3050fddc60>", | |
| "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": { | |
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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": 1.0 | |
| } | |
| }, | |
| "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 0x7f3050fdcb80>", | |
| "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": [ | |
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| ] | |
| }, | |
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| "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 0x7f3050fdce00>", | |
| "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 0x7f3050fdd080>", | |
| "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", | |
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| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n" | |
| }, | |
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| "metric_list": [ | |
| { | |
| "metric": "f1_macro", | |
| "aggregation": "f1_macro", | |
| "higher_is_better": true | |
| }, | |
| { | |
| "metric": "acc", | |
| "aggregation": "acc", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
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| "do_sample": false, | |
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| { | |
| "name": "all", | |
| "filter": [ | |
| { | |
| "function": "find_similar_label", | |
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| "Diversão", | |
| "Raiva", | |
| "Aborrecimento", | |
| "Aprovação", | |
| "Compaixão", | |
| "Confusão", | |
| "Curiosidade", | |
| "Desejo", | |
| "Decepção", | |
| "Desaprovação", | |
| "Nojo", | |
| " Vergonha", | |
| "Inveja", | |
| "Entusiasmo", | |
| "Medo", | |
| "Gratidão", | |
| "Luto", | |
| "Alegria", | |
| "Saudade", | |
| "Amor", | |
| "Nervosismo", | |
| "Otimismo", | |
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| "Alívio", | |
| "Remorso", | |
| "Tristeza", | |
| "Surpresa" | |
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| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "limit": 500, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
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| "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:", | |
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| "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", | |
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| "fewshot_delimiter": "\n\n", | |
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| "metric": "f1_macro", | |
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| { | |
| "name": "all", | |
| "filter": [ | |
| { | |
| "function": "find_similar_label", | |
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| "Sim", | |
| "Não" | |
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| { | |
| "function": "take_first" | |
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| } | |
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| "limit": 500, | |
| "metadata": { | |
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| } | |
| }, | |
| "sparrow_sentiment-2016-mozetic-por": { | |
| "task": "sparrow_sentiment-2016-mozetic-por", | |
| "task_alias": "sentiment-2016-mozetic-por", | |
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| "pt_benchmark", | |
| "sparrow" | |
| ], | |
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| "fewshot_split": "train", | |
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| "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", | |
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| { | |
| "name": "all", | |
| "filter": [ | |
| { | |
| "function": "find_similar_label", | |
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| "Positivo", | |
| "Neutro", | |
| "Negativo" | |
| ] | |
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| { | |
| "function": "take_first" | |
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| ] | |
| } | |
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| "limit": 500, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
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| "task": "sparrow_sentiment-2018-brum-por", | |
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| "group": [ | |
| "pt_benchmark", | |
| "sparrow" | |
| ], | |
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| "dataset_name": "sentiment-2018-brum-por", | |
| "test_split": "validation", | |
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| "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", | |
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