EleutherAI/gpt-neo-2.7B/raw_2024-02-14T21-23-17.848186/results.json

{
  "results": {
    "assin2_rte": {
      "f1_macro,all": 0.3333333333333333,
      "acc,all": 0.5,
      "alias": "assin2_rte"
    },
    "assin2_sts": {
      "pearson,all": 0.006388450736995319,
      "mse,all": 2.6796160130718967,
      "alias": "assin2_sts"
    },
    "bluex": {
      "acc,all": 0.19193324061196107,
      "acc,exam_id__UNICAMP_2022": 0.23076923076923078,
      "acc,exam_id__UNICAMP_2019": 0.16,
      "acc,exam_id__UNICAMP_2023": 0.32558139534883723,
      "acc,exam_id__UNICAMP_2018": 0.2037037037037037,
      "acc,exam_id__UNICAMP_2020": 0.18181818181818182,
      "acc,exam_id__USP_2024": 0.12195121951219512,
      "acc,exam_id__UNICAMP_2021_2": 0.13725490196078433,
      "acc,exam_id__USP_2022": 0.1836734693877551,
      "acc,exam_id__USP_2019": 0.25,
      "acc,exam_id__USP_2021": 0.19230769230769232,
      "acc,exam_id__USP_2023": 0.13636363636363635,
      "acc,exam_id__UNICAMP_2021_1": 0.30434782608695654,
      "acc,exam_id__UNICAMP_2024": 0.15555555555555556,
      "acc,exam_id__USP_2020": 0.19642857142857142,
      "acc,exam_id__USP_2018": 0.12962962962962962,
      "alias": "bluex"
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    "enem_challenge": {
      "alias": "enem",
      "acc,all": 0.1952414275717285,
      "acc,exam_id__2015": 0.14285714285714285,
      "acc,exam_id__2012": 0.1896551724137931,
      "acc,exam_id__2017": 0.20689655172413793,
      "acc,exam_id__2009": 0.19130434782608696,
      "acc,exam_id__2023": 0.2518518518518518,
      "acc,exam_id__2016_2": 0.21138211382113822,
      "acc,exam_id__2010": 0.15384615384615385,
      "acc,exam_id__2014": 0.2018348623853211,
      "acc,exam_id__2013": 0.17592592592592593,
      "acc,exam_id__2022": 0.20300751879699247,
      "acc,exam_id__2011": 0.20512820512820512,
      "acc,exam_id__2016": 0.19834710743801653
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    "faquad_nli": {
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      "acc,all": 0.44461538461538463,
      "alias": "faquad_nli"
    },
    "oab_exams": {
      "acc,all": 0.23234624145785876,
      "acc,exam_id__2012-06a": 0.2625,
      "acc,exam_id__2015-17": 0.2564102564102564,
      "acc,exam_id__2012-06": 0.2375,
      "acc,exam_id__2014-15": 0.20512820512820512,
      "acc,exam_id__2016-20": 0.2375,
      "acc,exam_id__2013-10": 0.2,
      "acc,exam_id__2012-07": 0.1375,
      "acc,exam_id__2011-03": 0.24242424242424243,
      "acc,exam_id__2011-05": 0.2375,
      "acc,exam_id__2016-19": 0.20512820512820512,
      "acc,exam_id__2017-23": 0.2125,
      "acc,exam_id__2017-22": 0.2625,
      "acc,exam_id__2018-25": 0.275,
      "acc,exam_id__2014-13": 0.225,
      "acc,exam_id__2017-24": 0.225,
      "acc,exam_id__2010-01": 0.27058823529411763,
      "acc,exam_id__2014-14": 0.2375,
      "acc,exam_id__2011-04": 0.25,
      "acc,exam_id__2013-12": 0.175,
      "acc,exam_id__2015-16": 0.225,
      "acc,exam_id__2016-21": 0.2125,
      "acc,exam_id__2013-11": 0.1625,
      "acc,exam_id__2012-08": 0.2375,
      "acc,exam_id__2016-20a": 0.3,
      "acc,exam_id__2012-09": 0.24675324675324675,
      "acc,exam_id__2010-02": 0.25,
      "acc,exam_id__2015-18": 0.275,
      "alias": "oab_exams"
    },
    "sparrow_emotion-2021-cortiz-por": {
      "alias": "emotion-2021-cortiz-por",
      "f1_macro,all": 0.04324239689721254,
      "acc,all": 0.094
    },
    "sparrow_hate-2019-fortuna-por": {
      "alias": "hate-2019-fortuna-por",
      "f1_macro,all": 0.4457582027785989,
      "acc,all": 0.64
    },
    "sparrow_sentiment-2016-mozetic-por": {
      "alias": "sentiment-2016-mozetic-por",
      "f1_macro,all": 0.30375309445076887,
      "acc,all": 0.728
    },
    "sparrow_sentiment-2018-brum-por": {
      "alias": "sentiment-2018-brum-por",
      "f1_macro,all": 0.2642692069218195,
      "acc,all": 0.368
    }
  },
  "configs": {
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      "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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            2,
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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
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    },
    "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 0x7f96ddc11800>",
      "description": "Abaixo contém pares de frases, para cada par você deve julgar o grau de similaridade de 1,0 a 5,0, responda apenas com o número.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "id_sampler",
        "sampler_config": {
          "id_list": [
            1,
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            2,
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            15,
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            3262,
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            17,
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            18,
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            3266,
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            20,
            3268,
            3269,
            21,
            3270,
            3271,
            22,
            3272,
            3273,
            23,
            3274,
            24,
            25,
            3275
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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"
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      },
      "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
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    },
    "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 0x7f96ddc111c0>",
      "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"
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      ],
      "should_decontaminate": true,
      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f96ddc11440>",
      "metadata": {
        "version": 1.0
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    },
    "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 0x7f96ddc119e0>",
      "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": [
        {
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          "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"
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          ],
          "group_by": {
            "column": "exam_id"
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      ],
      "should_decontaminate": true,
      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f96ddc11c60>",
      "metadata": {
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    },
    "faquad_nli": {
      "task": "faquad_nli",
      "group": [
        "pt_benchmark"
      ],
      "dataset_path": "ruanchaves/faquad-nli",
      "test_split": "test",
      "fewshot_split": "train",
      "doc_to_text": "Pergunta: {{question}}\nResposta: {{answer}}\nA resposta satisfaz a pergunta? Sim ou Não?",
      "doc_to_target": "{{['Não', 'Sim'][label]}}",
      "description": "Abaixo contém pares de pergunta e reposta, para cada par você deve julgar resposta responde a pergunta de maneira satisfatória e aparenta estar correta, escreva apenas Sim ou Não.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n",
        "sampler_config": {
          "fewshot_indices": [
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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 0x7f96ddc10b80>",
      "doc_to_target": "{{answerKey}}",
      "description": "As perguntas a seguir são questões de multipla escolha do Exame de Ordem da Ordem dos Advogados do Brasil (OAB), reponda apenas com as letras A, B, C ou D.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "id_sampler",
        "sampler_config": {
          "id_list": [
            "2010-01_1",
            "2010-01_11",
            "2010-01_13",
            "2010-01_23",
            "2010-01_26",
            "2010-01_28",
            "2010-01_38",
            "2010-01_48",
            "2010-01_58",
            "2010-01_68",
            "2010-01_76",
            "2010-01_83",
            "2010-01_85",
            "2010-01_91",
            "2010-01_99"
          ],
          "id_column": "id",
          "exclude_from_task": true
        }
      },
      "num_fewshot": 3,
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "acc",
          "higher_is_better": true
        }
      ],
      "output_type": "generate_until",
      "generation_kwargs": {
        "max_gen_toks": 32,
        "do_sample": false,
        "temperature": 0.0,
        "top_k": null,
        "top_p": null,
        "until": [
          "\n\n"
        ]
      },
      "repeats": 1,
      "filter_list": [
        {
          "name": "all",
          "filter": [
            {
              "function": "normalize_spaces"
            },
            {
              "function": "remove_accents"
            },
            {
              "function": "find_choices",
              "choices": [
                "A",
                "B",
                "C",
                "D"
              ],
              "regex_patterns": [
                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta[Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
                "\\b([ABCD])\\)",
                "\\b([ABCD]) ?[.):-]",
                "\\b([ABCD])$",
                "\\b([ABCD])\\b"
              ]
            },
            {
              "function": "take_first"
            }
          ],
          "group_by": {
            "column": "exam_id"
          }
        }
      ],
      "should_decontaminate": true,
      "doc_to_decontamination_query": "<function doc_to_text at 0x7f96ddc10e00>",
      "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 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",
      "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
        },
        {
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