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{ |
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"results": { |
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"acc,exam_id__USP_2018": 0.25925925925925924, |
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"alias": "bluex" |
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"acc,all": 0.37788663400979705, |
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"acc,exam_id__2015": 0.3697478991596639, |
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"acc,exam_id__2012": 0.33620689655172414, |
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"acc,exam_id__2010": 0.37606837606837606, |
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"acc,exam_id__2014": 0.41284403669724773, |
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"acc,exam_id__2011": 0.3418803418803419, |
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"alias": "faquad_nli" |
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"acc,exam_id__2010-02": 0.37, |
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"alias": "emotion-2021-cortiz-por", |
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"f1_macro,all": 0.06658754253124766, |
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"acc,all": 0.136 |
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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": 0.4337265967292048, |
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"acc,all": 0.65 |
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}, |
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"alias": "sentiment-2016-mozetic-por", |
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"f1_macro,all": 0.3628162647260163, |
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"acc,all": 0.468 |
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"alias": "sentiment-2018-brum-por", |
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"f1_macro,all": 0.3200416049637069, |
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"acc,all": 0.39 |
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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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"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 0x7f96ddc11800>", |
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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": " ", |
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"fewshot_delimiter": "\n\n", |
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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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{ |
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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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"task": "bluex", |
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"group": [ |
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"pt_benchmark", |
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"vestibular" |
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"fewshot_split": "train", |
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"doc_to_text": "<function enem_doc_to_text at 0x7f96ddc111c0>", |
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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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{ |
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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 0x7f96ddc11440>", |
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"doc_to_text": "<function enem_doc_to_text at 0x7f96ddc119e0>", |
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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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{ |
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"aggregation": "acc", |
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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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}, |
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"task": "faquad_nli", |
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"group": [ |
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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]}}", |
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"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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} |
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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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{ |
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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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"Sim", |
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"Não" |
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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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"metadata": { |
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"version": 1.0 |
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} |
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}, |
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"oab_exams": { |
|
"task": "oab_exams", |
|
"group": [ |
|
"legal_benchmark", |
|
"pt_benchmark" |
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], |
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"dataset_path": "eduagarcia/oab_exams", |
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"test_split": "train", |
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"fewshot_split": "train", |
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"doc_to_text": "<function doc_to_text at 0x7f96ddc10b80>", |
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"doc_to_target": "{{answerKey}}", |
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"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", |
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"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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"2010-01_1", |
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"2010-01_11", |
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"2010-01_13", |
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"2010-01_23", |
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"2010-01_26", |
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"2010-01_28", |
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"2010-01_38", |
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"2010-01_48", |
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"2010-01_58", |
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"2010-01_68", |
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"2010-01_76", |
|
"2010-01_83", |
|
"2010-01_85", |
|
"2010-01_91", |
|
"2010-01_99" |
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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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"num_fewshot": 3, |
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"metric_list": [ |
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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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], |
|
"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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}, |
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"repeats": 1, |
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"filter_list": [ |
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{ |
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"name": "all", |
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"filter": [ |
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{ |
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"function": "normalize_spaces" |
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}, |
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{ |
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"function": "remove_accents" |
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}, |
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{ |
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"function": "find_choices", |
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"choices": [ |
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"A", |
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"B", |
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"C", |
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"D" |
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], |
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"regex_patterns": [ |
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"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta[Cc]orreta e|[Oo]pcao):? ([ABCD])\\b", |
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"\\b([ABCD])\\)", |
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"\\b([ABCD]) ?[.):-]", |
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"\\b([ABCD])$", |
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"\\b([ABCD])\\b" |
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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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"group_by": { |
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"column": "exam_id" |
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} |
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} |
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], |
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"should_decontaminate": true, |
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"doc_to_decontamination_query": "<function doc_to_text at 0x7f96ddc10e00>", |
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"metadata": { |
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"version": 1.4 |
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} |
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}, |
|
"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", |
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"doc_to_text": "Texto: {{content}}\nPergunta: Qual a principal emoção apresentada no texto?\nResposta:", |
|
"doc_to_target": "<function sparrow_emotion_por_trans_label at 0x7f96ddc11080>", |
|
"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", |
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"sampler": "first_n" |
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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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} |
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], |
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"output_type": "generate_until", |
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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_p": null, |
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"\n\n" |
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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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|
"Admiração", |
|
"Diversão", |
|
"Raiva", |
|
"Aborrecimento", |
|
"Aprovação", |
|
"Compaixão", |
|
"Confusão", |
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"Curiosidade", |
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"Desejo", |
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"Decepção", |
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"Desaprovação", |
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"Nojo", |
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" Vergonha", |
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"Inveja", |
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"Entusiasmo", |
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"Medo", |
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"Gratidão", |
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"Luto", |
|
"Alegria", |
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"Saudade", |
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"Amor", |
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"Nervosismo", |
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"Otimismo", |
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"Orgulho", |
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"Alívio", |
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"Remorso", |
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"Tristeza", |
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"Surpresa" |
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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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"limit": 500, |
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"metadata": { |
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"version": 1.0 |
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} |
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}, |
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"sparrow_hate-2019-fortuna-por": { |
|
"task": "sparrow_hate-2019-fortuna-por", |
|
"task_alias": "hate-2019-fortuna-por", |
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"group": [ |
|
"pt_benchmark", |
|
"sparrow" |
|
], |
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"dataset_name": "hate-2019-fortuna-por", |
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"test_split": "validation", |
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"fewshot_split": "train", |
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"doc_to_text": "Texto: {{content}}\nPergunta: O texto contém discurso de ódio?\nResposta:", |
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"doc_to_target": "{{'Sim' if label == 'Hate' else 'Não'}}", |
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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", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
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"sampler": "first_n" |
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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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"metric": "acc", |
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"aggregation": "acc", |
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"higher_is_better": true |
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} |
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"top_p": null, |
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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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"Sim", |
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"Não" |
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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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"version": 1.0 |
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} |
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}, |
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"sparrow_sentiment-2016-mozetic-por": { |
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"task": "sparrow_sentiment-2016-mozetic-por", |
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"task_alias": "sentiment-2016-mozetic-por", |
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"group": [ |
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"pt_benchmark", |
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"sparrow" |
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], |
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"dataset_name": "sentiment-2016-mozetic-por", |
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"test_split": "validation", |
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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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"fewshot_delimiter": "\n\n", |
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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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"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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"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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"version": 1.0 |
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} |
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}, |
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"sparrow_sentiment-2018-brum-por": { |
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"task": "sparrow_sentiment-2018-brum-por", |
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"task_alias": "sentiment-2018-brum-por", |
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"group": [ |
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"pt_benchmark", |
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"sparrow" |
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], |
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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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{ |
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