llm_pt_leaderboard_raw_results
/
huggyllama
/llama-13b
/raw_2024-02-06T03-05-10.640098
/results.json
{ | |
"results": { | |
"assin2_rte": { | |
"f1_macro,all": 0.5505784757177058, | |
"acc,all": 0.616421568627451, | |
"alias": "assin2_rte" | |
}, | |
"assin2_sts": { | |
"pearson,all": 0.3575846951731686, | |
"mse,all": 2.5022630718954253, | |
"alias": "assin2_sts" | |
}, | |
"bluex": { | |
"acc,all": 0.3463143254520167, | |
"acc,exam_id__USP_2024": 0.21951219512195122, | |
"acc,exam_id__UNICAMP_2020": 0.34545454545454546, | |
"acc,exam_id__UNICAMP_2019": 0.36, | |
"acc,exam_id__UNICAMP_2023": 0.4186046511627907, | |
"acc,exam_id__UNICAMP_2018": 0.2962962962962963, | |
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"acc,exam_id__UNICAMP_2021_2": 0.35294117647058826, | |
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"acc,exam_id__USP_2019": 0.175, | |
"acc,exam_id__USP_2021": 0.3269230769230769, | |
"acc,exam_id__USP_2020": 0.44642857142857145, | |
"alias": "bluex" | |
}, | |
"enem_challenge": { | |
"alias": "enem", | |
"acc,all": 0.3722883135059482, | |
"acc,exam_id__2016_2": 0.3821138211382114, | |
"acc,exam_id__2023": 0.4148148148148148, | |
"acc,exam_id__2011": 0.4017094017094017, | |
"acc,exam_id__2015": 0.36134453781512604, | |
"acc,exam_id__2010": 0.37606837606837606, | |
"acc,exam_id__2012": 0.3620689655172414, | |
"acc,exam_id__2009": 0.3739130434782609, | |
"acc,exam_id__2022": 0.42857142857142855, | |
"acc,exam_id__2014": 0.43119266055045874, | |
"acc,exam_id__2017": 0.2672413793103448, | |
"acc,exam_id__2016": 0.2975206611570248, | |
"acc,exam_id__2013": 0.3611111111111111 | |
}, | |
"faquad_nli": { | |
"f1_macro,all": 0.5734565832149147, | |
"acc,all": 0.7861538461538462, | |
"alias": "faquad_nli" | |
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"oab_exams": { | |
"acc,all": 0.3466970387243736, | |
"acc,exam_id__2017-23": 0.3125, | |
"acc,exam_id__2013-10": 0.35, | |
"acc,exam_id__2016-20a": 0.3125, | |
"acc,exam_id__2016-20": 0.3625, | |
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"acc,exam_id__2014-15": 0.32051282051282054, | |
"acc,exam_id__2010-01": 0.25882352941176473, | |
"acc,exam_id__2011-03": 0.3333333333333333, | |
"acc,exam_id__2016-19": 0.4358974358974359, | |
"acc,exam_id__2016-21": 0.3, | |
"acc,exam_id__2018-25": 0.3, | |
"acc,exam_id__2013-12": 0.2375, | |
"acc,exam_id__2011-04": 0.4125, | |
"acc,exam_id__2011-05": 0.325, | |
"acc,exam_id__2012-07": 0.325, | |
"acc,exam_id__2012-06": 0.4125, | |
"acc,exam_id__2012-09": 0.33766233766233766, | |
"acc,exam_id__2013-11": 0.475, | |
"acc,exam_id__2012-06a": 0.3375, | |
"acc,exam_id__2012-08": 0.275, | |
"acc,exam_id__2015-18": 0.3375, | |
"acc,exam_id__2017-22": 0.3875, | |
"acc,exam_id__2015-17": 0.41025641025641024, | |
"acc,exam_id__2017-24": 0.425, | |
"acc,exam_id__2014-13": 0.3625, | |
"acc,exam_id__2015-16": 0.3375, | |
"alias": "oab_exams" | |
}, | |
"sparrow_emotion-2021-cortiz-por": { | |
"alias": "emotion-2021-cortiz-por", | |
"f1_macro,all": 0.08894135125855691, | |
"acc,all": 0.144 | |
}, | |
"sparrow_hate-2019-fortuna-por": { | |
"alias": "hate-2019-fortuna-por", | |
"f1_macro,all": 0.4053965389977856, | |
"acc,all": 0.652 | |
}, | |
"sparrow_sentiment-2016-mozetic-por": { | |
"alias": "sentiment-2016-mozetic-por", | |
"f1_macro,all": 0.32578905562776533, | |
"acc,all": 0.316 | |
}, | |
"sparrow_sentiment-2018-brum-por": { | |
"alias": "sentiment-2018-brum-por", | |
"f1_macro,all": 0.36358408164885087, | |
"acc,all": 0.394 | |
} | |
}, | |
"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": [ | |
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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": 1.0 | |
} | |
}, | |
"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 0x7fa487821760>", | |
"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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2, | |
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4, | |
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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": 1.0 | |
} | |
}, | |
"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 0x7fa487821120>", | |
"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])$", | |
"\\b([ABCDE])\\b" | |
] | |
}, | |
{ | |
"function": "take_first" | |
} | |
], | |
"group_by": { | |
"column": "exam_id" | |
} | |
} | |
], | |
"should_decontaminate": true, | |
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fa4878213a0>", | |
"metadata": { | |
"version": 1.0 | |
} | |
}, | |
"enem_challenge": { | |
"task": "enem_challenge", | |
"task_alias": "enem", | |
"group": [ | |
"pt_benchmark", | |
"vestibular" | |
], | |
"dataset_path": "eduagarcia/enem_challenge", | |
"test_split": "train", | |
"fewshot_split": "train", | |
"doc_to_text": "<function enem_doc_to_text at 0x7fa487821940>", | |
"doc_to_target": "{{answerKey}}", | |
"description": "As perguntas a seguir são questões de multipla escolha do Exame Nacional do Ensino Médio (ENEM), reponda apenas com as letras A, B, C, D ou E.\n\n", | |
"target_delimiter": " ", | |
"fewshot_delimiter": "\n\n", | |
"fewshot_config": { | |
"sampler": "id_sampler", | |
"sampler_config": { | |
"id_list": [ | |
"2022_21", | |
"2022_88", | |
"2022_143" | |
], | |
"id_column": "id", | |
"exclude_from_task": true | |
} | |
}, | |
"num_fewshot": 3, | |
"metric_list": [ | |
{ | |
"metric": "acc", | |
"aggregation": "acc", | |
"higher_is_better": true | |
} | |
], | |
"output_type": "generate_until", | |
"generation_kwargs": { | |
"max_gen_toks": 32, | |
"do_sample": false, | |
"temperature": 0.0, | |
"top_k": null, | |
"top_p": null, | |
"until": [ | |
"\n\n" | |
] | |
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"repeats": 1, | |
"filter_list": [ | |
{ | |
"name": "all", | |
"filter": [ | |
{ | |
"function": "normalize_spaces" | |
}, | |
{ | |
"function": "remove_accents" | |
}, | |
{ | |
"function": "find_choices", | |
"choices": [ | |
"A", | |
"B", | |
"C", | |
"D", | |
"E" | |
], | |
"regex_patterns": [ | |
"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta[Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b", | |
"\\b([ABCDE])\\.", | |
"\\b([ABCDE]) ?[.):-]", | |
"\\b([ABCDE])$", | |
"\\b([ABCDE])\\b" | |
] | |
}, | |
{ | |
"function": "take_first" | |
} | |
], | |
"group_by": { | |
"column": "exam_id" | |
} | |
} | |
], | |
"should_decontaminate": true, | |
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fa487821bc0>", | |
"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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"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 0x7fa487820ae0>", | |
"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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] | |
}, | |
"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 0x7fa487820d60>", | |
"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 0x7fa487820fe0>", | |
"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" | |
}, | |
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"metric_list": [ | |
{ | |
"metric": "f1_macro", | |
"aggregation": "f1_macro", | |
"higher_is_better": true | |
}, | |
{ | |
"metric": "acc", | |
"aggregation": "acc", | |
"higher_is_better": true | |
} | |
], | |
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"do_sample": false, | |
"temperature": 0.0, | |
"top_k": null, | |
"top_p": null, | |
"until": [ | |
"\n\n" | |
] | |
}, | |
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"filter_list": [ | |
{ | |
"name": "all", | |
"filter": [ | |
{ | |
"function": "find_similar_label", | |
"labels": [ | |
"Sim", | |
"Não" | |
] | |
}, | |
{ | |
"function": "take_first" | |
} | |
] | |
} | |
], | |
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"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", | |
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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", | |
"target_delimiter": " ", | |
"fewshot_delimiter": "\n\n", | |
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"metric": "f1_macro", | |
"aggregation": "f1_macro", | |
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}, | |
{ | |
"metric": "acc", | |
"aggregation": "acc", | |
"higher_is_better": true | |
} | |
], | |
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"until": [ | |
"\n\n" | |
] | |
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{ | |
"name": "all", | |
"filter": [ | |
{ | |
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"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", | |
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{ | |
"metric": "acc", | |
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} | |
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{ | |
"function": "take_first" | |
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] | |
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