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{ |
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"results": { |
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"acc,exam_id__2016_2": 0.24390243902439024, |
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"acc,exam_id__2016": 0.14049586776859505, |
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"acc,exam_id__2010": 0.18803418803418803, |
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"acc,exam_id__2014": 0.22935779816513763, |
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"acc,exam_id__2023": 0.17777777777777778, |
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"acc,exam_id__2017": 0.22413793103448276, |
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"acc,exam_id__2015": 0.17647058823529413, |
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"acc,exam_id__2012": 0.28448275862068967, |
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"acc,exam_id__2009": 0.2782608695652174, |
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"acc,exam_id__2016-20": 0.2125, |
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"alias": "emotion-2021-cortiz-por", |
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"f1_macro,all": 0.0485852902984244, |
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"acc,all": 0.072 |
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"sparrow_hate-2019-fortuna-por": { |
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"alias": "hate-2019-fortuna-por", |
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"f1_macro,all": 0.3932038834951456, |
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"acc,all": 0.648 |
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}, |
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"alias": "sentiment-2016-mozetic-por", |
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"f1_macro,all": 0.08330275790374854, |
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"acc,all": 0.114 |
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"alias": "sentiment-2018-brum-por", |
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"f1_macro,all": 0.16121612161216123, |
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"acc,all": 0.258 |
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} |
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}, |
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"configs": { |
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"assin2_rte": { |
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"task": "assin2_rte", |
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], |
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"dataset_path": "assin2", |
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"test_split": "test", |
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"fewshot_split": "train", |
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"doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa?\nResposta:", |
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"doc_to_target": "{{['Não', 'Sim'][entailment_judgment]}}", |
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"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", |
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"target_delimiter": " ", |
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{ |
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"metric": "acc", |
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"aggregation": "acc", |
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"higher_is_better": true |
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}, |
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{ |
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} |
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], |
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], |
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"dataset_path": "assin2", |
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"test_split": "test", |
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"fewshot_split": "train", |
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"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:", |
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"doc_to_target": "<function assin2_float_to_pt_str at 0x7f8bf0f71800>", |
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"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", |
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"id_column": "sentence_pair_id" |
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} |
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"metric_list": [ |
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{ |
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"metric": "pearson", |
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"aggregation": "pearsonr", |
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"higher_is_better": true |
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}, |
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{ |
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"metric": "mse", |
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"aggregation": "mean_squared_error", |
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"higher_is_better": false |
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} |
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], |
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"type": "float", |
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"on_outside_range": "clip", |
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}, |
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{ |
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"function": "take_first" |
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} |
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] |
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} |
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], |
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} |
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}, |
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"bluex": { |
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"task": "bluex", |
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"group": [ |
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"pt_benchmark", |
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"vestibular" |
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], |
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"fewshot_split": "train", |
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"doc_to_text": "<function enem_doc_to_text at 0x7f8bf0f711c0>", |
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"doc_to_target": "{{answerKey}}", |
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"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": " ", |
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"fewshot_delimiter": "\n\n", |
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"fewshot_config": { |
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"sampler": "id_sampler", |
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"sampler_config": { |
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"id_list": [ |
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"USP_2018_3", |
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"UNICAMP_2018_2", |
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"USP_2018_35", |
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"UNICAMP_2018_16", |
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"USP_2018_89" |
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], |
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"id_column": "id", |
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"exclude_from_task": true |
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} |
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}, |
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"num_fewshot": 3, |
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"metric_list": [ |
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{ |
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"metric": "acc", |
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"aggregation": "acc", |
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"higher_is_better": true |
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} |
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], |
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"output_type": "generate_until", |
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"generation_kwargs": { |
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"max_gen_toks": 32, |
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"do_sample": false, |
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"temperature": 0.0, |
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{ |
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}, |
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{ |
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"function": "find_choices", |
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"choices": [ |
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"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8bf0f71440>", |
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"doc_to_text": "<function enem_doc_to_text at 0x7f8bf0f719e0>", |
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"doc_to_target": "{{answerKey}}", |
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"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", |
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"target_delimiter": " ", |
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"fewshot_delimiter": "\n\n", |
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"sampler_config": { |
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"id_column": "id", |
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} |
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"metric_list": [ |
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{ |
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"metric": "acc", |
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"aggregation": "acc", |
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"higher_is_better": true |
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} |
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], |
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"output_type": "generate_until", |
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"generation_kwargs": { |
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"regex_patterns": [ |
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"metadata": { |
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}, |
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"task": "faquad_nli", |
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"group": [ |
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], |
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"dataset_path": "ruanchaves/faquad-nli", |
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"test_split": "test", |
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"fewshot_split": "train", |
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"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", |
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"target_delimiter": " ", |
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"fewshot_delimiter": "\n\n", |
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{ |
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"aggregation": "f1_macro", |
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}, |
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{ |
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"aggregation": "acc", |
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"higher_is_better": true |
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} |
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"output_type": "generate_until", |
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"generation_kwargs": { |
|
"max_gen_toks": 32, |
|
"do_sample": false, |
|
"temperature": 0.0, |
|
"top_k": null, |
|
"top_p": null, |
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"until": [ |
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"\n\n" |
|
] |
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}, |
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"repeats": 1, |
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"filter_list": [ |
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{ |
|
"name": "all", |
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"filter": [ |
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{ |
|
"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 0x7f8bf0f70b80>", |
|
"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", |
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"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" |
|
] |
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}, |
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"repeats": 1, |
|
"filter_list": [ |
|
{ |
|
"name": "all", |
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"filter": [ |
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{ |
|
"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 0x7f8bf0f70e00>", |
|
"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 0x7f8bf0f71080>", |
|
"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": " ", |
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"fewshot_delimiter": "\n\n", |
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"fewshot_config": { |
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"sampler": "first_n" |
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}, |
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"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, |
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"until": [ |
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"\n\n" |
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] |
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}, |
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"repeats": 1, |
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"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": { |
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"max_gen_toks": 32, |
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"do_sample": false, |
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"temperature": 0.0, |
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"top_k": null, |
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"top_p": null, |
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"until": [ |
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"\n\n" |
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] |
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}, |
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"repeats": 1, |
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"filter_list": [ |
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{ |
|
"name": "all", |
|
"filter": [ |
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{ |
|
"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, |
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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, |
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"do_sample": false, |
|
"temperature": 0.0, |
|
"top_k": null, |
|
"top_p": null, |
|
"until": [ |
|
"\n\n" |
|
] |
|
}, |
|
"repeats": 1, |
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"filter_list": [ |
|
{ |
|
"name": "all", |
|
"filter": [ |
|
{ |
|
"function": "find_similar_label", |
|
"labels": [ |
|
"Positivo", |
|
"Neutro", |
|
"Negativo" |
|
] |
|
}, |
|
{ |
|
"function": "take_first" |
|
} |
|
] |
|
} |
|
], |
|
"should_decontaminate": false, |
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"limit": 500, |
|
"metadata": { |
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"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": " ", |
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"fewshot_delimiter": "\n\n", |
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"fewshot_config": { |
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"sampler": "first_n" |
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}, |
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"metric_list": [ |
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{ |
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"metric": "f1_macro", |
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"aggregation": "f1_macro", |
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"higher_is_better": true |
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}, |
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{ |
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"metric": "acc", |
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"aggregation": "acc", |
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"higher_is_better": true |
|
} |
|
], |
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"output_type": "generate_until", |
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"generation_kwargs": { |
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"max_gen_toks": 32, |
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"do_sample": false, |
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"temperature": 0.0, |
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"top_k": null, |
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"top_p": null, |
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"until": [ |
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"\n\n" |
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{ |
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"name": "all", |
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"filter": [ |
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{ |
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"function": "find_similar_label", |
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"labels": [ |
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"Positivo", |
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"Neutro", |
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"Negativo" |
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] |
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}, |
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{ |
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"function": "take_first" |
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} |
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] |
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} |
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], |
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"should_decontaminate": false, |
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"limit": 500, |
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"metadata": { |
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