internlm/internlm2-7b/raw_2024-02-17T15-30-06.358225/results.json

{
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      "f1_macro,all": 0.8758216175359033,
      "acc,all": 0.8766339869281046,
      "alias": "assin2_rte"
    },
    "assin2_sts": {
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      "mse,all": 0.48959150326797374,
      "alias": "assin2_sts"
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      "acc,exam_id__UNICAMP_2021_2": 0.5490196078431373,
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      "acc,exam_id__UNICAMP_2023": 0.5581395348837209,
      "acc,exam_id__USP_2024": 0.7073170731707317,
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      "acc,exam_id__USP_2020": 0.5892857142857143,
      "acc,exam_id__USP_2019": 0.45,
      "acc,exam_id__USP_2023": 0.6818181818181818,
      "acc,exam_id__UNICAMP_2019": 0.48,
      "acc,exam_id__USP_2022": 0.42857142857142855,
      "acc,exam_id__UNICAMP_2024": 0.5777777777777777,
      "acc,exam_id__USP_2021": 0.40384615384615385,
      "acc,exam_id__UNICAMP_2022": 0.5384615384615384,
      "acc,exam_id__UNICAMP_2018": 0.42592592592592593,
      "alias": "bluex"
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      "acc,exam_id__2016_2": 0.6260162601626016,
      "acc,exam_id__2011": 0.6837606837606838,
      "acc,exam_id__2022": 0.5714285714285714,
      "acc,exam_id__2015": 0.6218487394957983,
      "acc,exam_id__2013": 0.6481481481481481,
      "acc,exam_id__2014": 0.6238532110091743,
      "acc,exam_id__2009": 0.6173913043478261,
      "acc,exam_id__2016": 0.5867768595041323,
      "acc,exam_id__2012": 0.6206896551724138,
      "acc,exam_id__2017": 0.646551724137931
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      "f1_macro,all": 0.4617741808753045,
      "acc,all": 0.7892307692307692,
      "alias": "faquad_nli"
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    "hatebr_offensive": {
      "alias": "hatebr_offensive_binary",
      "f1_macro,all": 0.6885926784506906,
      "acc,all": 0.7121428571428572
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    "oab_exams": {
      "acc,all": 0.4018223234624146,
      "acc,exam_id__2016-20": 0.4,
      "acc,exam_id__2015-17": 0.47435897435897434,
      "acc,exam_id__2014-13": 0.4125,
      "acc,exam_id__2018-25": 0.4375,
      "acc,exam_id__2017-22": 0.4625,
      "acc,exam_id__2014-14": 0.5,
      "acc,exam_id__2013-11": 0.35,
      "acc,exam_id__2015-18": 0.4375,
      "acc,exam_id__2011-05": 0.425,
      "acc,exam_id__2012-08": 0.3375,
      "acc,exam_id__2012-06a": 0.425,
      "acc,exam_id__2017-24": 0.375,
      "acc,exam_id__2012-07": 0.475,
      "acc,exam_id__2016-20a": 0.2875,
      "acc,exam_id__2016-21": 0.3375,
      "acc,exam_id__2016-19": 0.3974358974358974,
      "acc,exam_id__2010-01": 0.32941176470588235,
      "acc,exam_id__2011-04": 0.35,
      "acc,exam_id__2012-06": 0.4125,
      "acc,exam_id__2017-23": 0.4,
      "acc,exam_id__2012-09": 0.2987012987012987,
      "acc,exam_id__2013-12": 0.4125,
      "acc,exam_id__2013-10": 0.3625,
      "acc,exam_id__2011-03": 0.35353535353535354,
      "acc,exam_id__2015-16": 0.4125,
      "acc,exam_id__2010-02": 0.44,
      "acc,exam_id__2014-15": 0.5512820512820513,
      "alias": "oab_exams"
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    "portuguese_hate_speech": {
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      "f1_macro,all": 0.6847302597120557,
      "acc,all": 0.72737955346651
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    "tweetsentbr": {
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      "acc,all": 0.6746268656716418,
      "alias": "tweetsentbr"
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      "group": [
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        "assin2"
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      "dataset_path": "assin2",
      "test_split": "test",
      "fewshot_split": "train",
      "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? Sim ou Não?\nResposta:",
      "doc_to_target": "{{['Não', 'Sim'][entailment_judgment]}}",
      "description": "Abaixo estão pares de premissa e hipótese. Para cada par, indique 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": {
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        "sampler_config": {
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          "id_column": "sentence_pair_id"
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      "num_fewshot": 15,
      "metric_list": [
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          "aggregation": "f1_macro",
          "higher_is_better": true
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        {
          "metric": "acc",
          "aggregation": "acc",
          "higher_is_better": true
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      "output_type": "generate_until",
      "generation_kwargs": {
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        "do_sample": false,
        "temperature": 0.0,
        "top_k": null,
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        "until": [
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      "filter_list": [
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          "filter": [
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              "labels": [
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                "Não"
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            {
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          ]
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      ],
      "should_decontaminate": false,
      "metadata": {
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    "assin2_sts": {
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      "group": [
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        "assin2"
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      "dataset_path": "assin2",
      "test_split": "test",
      "fewshot_split": "train",
      "doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: Quão similares são as duas frases? Dê uma pontuação entre 1,0 a 5,0.\nResposta:",
      "doc_to_target": "<function assin2_float_to_pt_str at 0x7f8e52c3d8a0>",
      "description": "Abaixo estão pares de frases que você deve avaliar o grau de similaridade. Dê uma pontuação entre 1,0 e 5,0, sendo 1,0 pouco similar e 5,0 muito similar.\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
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        "sampler_config": {
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      "metric_list": [
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          "aggregation": "pearsonr",
          "higher_is_better": true
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          "aggregation": "mean_squared_error",
          "higher_is_better": false
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        "until": [
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      "filter_list": [
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          "filter": [
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              "range_min": 1.0,
              "range_max": 5.0,
              "on_outside_range": "clip",
              "fallback": 5.0
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            {
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          ]
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      "should_decontaminate": false,
      "metadata": {
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    "bluex": {
      "task": "bluex",
      "group": [
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        "vestibular"
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      "dataset_path": "eduagarcia-temp/BLUEX_without_images",
      "test_split": "train",
      "fewshot_split": "train",
      "doc_to_text": "<function enem_doc_to_text at 0x7f8e52c3d260>",
      "doc_to_target": "{{answerKey}}",
      "description": "As perguntas a seguir são questões de múltipla escolha de provas de vestibular de universidades brasileiras, selecione a única alternativa correta e responda 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": [
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            "UNICAMP_2018_2",
            "USP_2018_35",
            "UNICAMP_2018_16",
            "USP_2018_89"
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          "id_column": "id",
          "exclude_from_task": true
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      "metric_list": [
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          "aggregation": "acc",
          "higher_is_better": true
        }
      ],
      "output_type": "generate_until",
      "generation_kwargs": {
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        "do_sample": false,
        "temperature": 0.0,
        "top_k": null,
        "top_p": null,
        "until": [
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      },
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      "filter_list": [
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          "filter": [
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            {
              "function": "remove_accents"
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            {
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              "choices": [
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                "B",
                "C",
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                "E"
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              "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"
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            {
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      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8e52c3d4e0>",
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    "enem_challenge": {
      "task": "enem_challenge",
      "task_alias": "enem",
      "group": [
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        "vestibular"
      ],
      "dataset_path": "eduagarcia/enem_challenge",
      "test_split": "train",
      "fewshot_split": "train",
      "doc_to_text": "<function enem_doc_to_text at 0x7f8e52c3da80>",
      "doc_to_target": "{{answerKey}}",
      "description": "As perguntas a seguir são questões de múltipla escolha do Exame Nacional do Ensino Médio (ENEM), selecione a única alternativa correta e responda 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": [
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          "aggregation": "acc",
          "higher_is_better": true
        }
      ],
      "output_type": "generate_until",
      "generation_kwargs": {
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        "do_sample": false,
        "temperature": 0.0,
        "top_k": null,
        "top_p": null,
        "until": [
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      },
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      "filter_list": [
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          "filter": [
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              "function": "normalize_spaces"
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            {
              "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"
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            },
            {
              "function": "take_first"
            }
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            "column": "exam_id"
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      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8e52c3dd00>",
      "metadata": {
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    "faquad_nli": {
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      "group": [
        "pt_benchmark"
      ],
      "dataset_path": "ruanchaves/faquad-nli",
      "test_split": "test",
      "fewshot_split": "train",
      "doc_to_text": "Pergunta: {{question}}\nResposta: {{answer}}\nA resposta dada satisfaz à pergunta? Sim ou Não?",
      "doc_to_target": "{{['Não', 'Sim'][label]}}",
      "description": "Abaixo estão pares de pergunta e resposta. Para cada par, você deve julgar se a resposta responde à pergunta de maneira satisfatória e aparenta estar correta. Escreva apenas \"Sim\" ou \"Não\".\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "first_n",
        "sampler_config": {
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      },
      "num_fewshot": 15,
      "metric_list": [
        {
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          "aggregation": "f1_macro",
          "higher_is_better": true
        },
        {
          "metric": "acc",
          "aggregation": "acc",
          "higher_is_better": true
        }
      ],
      "output_type": "generate_until",
      "generation_kwargs": {
        "max_gen_toks": 32,
        "do_sample": false,
        "temperature": 0.0,
        "top_k": null,
        "top_p": null,
        "until": [
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      },
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      "filter_list": [
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          "filter": [
            {
              "function": "find_similar_label",
              "labels": [
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                "Não"
              ]
            },
            {
              "function": "take_first"
            }
          ]
        }
      ],
      "should_decontaminate": false,
      "metadata": {
        "version": 1.1
      }
    },
    "hatebr_offensive": {
      "task": "hatebr_offensive",
      "task_alias": "hatebr_offensive_binary",
      "group": [
        "pt_benchmark"
      ],
      "dataset_path": "eduagarcia/portuguese_benchmark",
      "dataset_name": "HateBR_offensive_binary",
      "test_split": "test",
      "fewshot_split": "train",
      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto é ofensivo?\nResposta:",
      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
      "description": "Abaixo contém o texto de comentários de usuários do Instagram em português, sua tarefa é classificar se o texto é ofensivo ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "fewshot_config": {
        "sampler": "id_sampler",
        "sampler_config": {
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          "id_column": "idx"
        }
      },
      "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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        "do_sample": false,
        "temperature": 0.0,
        "top_k": null,
        "top_p": null,
        "until": [
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      "filter_list": [
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              "labels": [
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                "Não"
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            },
            {
              "function": "take_first"
            }
          ]
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      ],
      "should_decontaminate": false,
      "metadata": {
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    },
    "oab_exams": {
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      "group": [
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        "pt_benchmark"
      ],
      "dataset_path": "eduagarcia/oab_exams",
      "test_split": "train",
      "fewshot_split": "train",
      "doc_to_text": "<function doc_to_text at 0x7f8e52c3cc20>",
      "doc_to_target": "{{answerKey}}",
      "description": "As perguntas a seguir são questões de múltipla escolha do Exame de Ordem da Ordem dos Advogados do Brasil (OAB), selecione a única alternativa correta e responda 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",
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            "2010-01_48",
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            "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
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      },
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      "metric_list": [
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          "aggregation": "acc",
          "higher_is_better": true
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      ],
      "output_type": "generate_until",
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