fix f1_score calculation bug

152334H/miqu-1-70b-sf/raw_2024-05-23T11-20-45.843993/results.json

@@ -1,1244 +1,1244 @@
 {
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-          "aggregation": "f1_macro",
-          "higher_is_better": true
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         },
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-          "higher_is_better": true
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+            "acc,exam_id__2013-12": 0.65,
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+            "alias": "oab_exams"
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+        "portuguese_hate_speech": {
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+            "acc,all": 0.7602820211515864
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+            "acc,all": 0.7417910447761195,
+            "alias": "tweetsentbr"
         }
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-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
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-      "filter_list": [
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
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+                        5,
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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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
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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: 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 0x7f660e5ba200>",
-      "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",
-      "fewshot_config": {
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-        "sampler_config": {
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-            2,
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-      "metric_list": [
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-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
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-        "do_sample": false,
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-        "until": [
-          "\n\n"
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-      "filter_list": [
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-          "filter": [
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-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "assin2_sts": {
+            "task": "assin2_sts",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: 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 0x7f660e5ba200>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
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+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
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+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
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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 0x7f660e5b9bc0>",
-      "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": [
-            "USP_2018_3",
-            "UNICAMP_2018_2",
-            "USP_2018_35",
-            "UNICAMP_2018_16",
-            "USP_2018_89"
-          ],
-          "id_column": "id",
-          "exclude_from_task": true
-        }
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-      "num_fewshot": 3,
-      "metric_list": [
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-      "output_type": "generate_until",
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-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
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-              "function": "normalize_spaces"
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+            "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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             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f660e5b9bc0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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+                "until": [
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\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 0x7f660e5b9e40>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
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-        }
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-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f660e5b9e40>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f660e5ba3e0>",
-      "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": {
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-        "sampler_config": {
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-      },
-      "num_fewshot": 3,
-      "metric_list": [
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-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7f660e5ba3e0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f660e5ba660>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f660e5ba660>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
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-            949,
-            663,
-            105,
-            1169,
-            2910,
-            2227,
-            2813,
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-            558,
-            1503,
-            1958,
-            2918,
-            601,
-            1560,
-            984,
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-            995,
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-            1982,
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-            301,
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-            1315,
-            1420,
-            2436,
-            2322,
-            766
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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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
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+                        558,
+                        1503,
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+                        601,
+                        1560,
+                        984,
+                        2388,
+                        995,
+                        2233,
+                        1982,
+                        165,
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+                        1312,
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+                        522,
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+                        301,
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+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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"
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+            },
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
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-    },
-    "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": {
-          "id_list": [
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-          "id_column": "idx"
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-      },
-      "num_fewshot": 25,
-      "metric_list": [
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-          "metric": "f1_macro",
-          "aggregation": "f1_macro",
-          "higher_is_better": true
         },
-        {
-          "metric": "acc",
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-          "higher_is_better": true
-        }
-      ],
-      "output_type": "generate_until",
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-        "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": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
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+                        52,
+                        72,
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+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7f660e5b9580>",
-      "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",
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-            "2010-01_23",
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-            "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": [
-        {
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-          "aggregation": "acc",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "generate_until",
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-        "top_k": null,
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-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7f660e5b9580>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7f660e5b9800>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
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-      ],
-      "should_decontaminate": true,
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-    "portuguese_hate_speech": {
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-      "task_alias": "portuguese_hate_speech_binary",
-      "group": [
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-      ],
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-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
-      "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        52,
+                        50,
+                        39,
+                        28,
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+                        24,
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+                        34,
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+                        32,
+                        119,
+                        114,
+                        2,
+                        58,
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+                        18,
+                        36,
+                        5,
+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
+                    ],
+                    "id_column": "idx"
+                }
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+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
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-      ],
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-      ],
-      "dataset_path": "eduagarcia/tweetsentbr_fewshot",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\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')}}",
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-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Positivo",
-                "Neutro",
-                "Negativo"
-              ]
+        "tweetsentbr": {
+            "task": "tweetsentbr",
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+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/tweetsentbr_fewshot",
+            "test_split": "test",
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+            "doc_to_text": "Texto: {{sentence}}\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 texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o sentimento do texto é Positivo, Neutro ou Negativo. Responda apenas com uma das opções.\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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+                "sampler": "first_n"
             },
-            {
-              "function": "take_first"
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+                    "metric": "f1_macro",
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+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
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+                }
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+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Positivo",
+                                "Neutro",
+                                "Negativo"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
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152334H/miqu-1-70b-sf/results_2024-05-23T11-20-45.843993.json

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BAAI/Infinity-Instruct-3M-0613-Mistral-7B/raw_2024-06-22T01-31-31.647844/results.json

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+            "acc,exam_id__2017-23": 0.4,
+            "acc,exam_id__2014-15": 0.41025641025641024,
+            "acc,exam_id__2011-05": 0.475,
+            "acc,exam_id__2015-16": 0.4375,
+            "acc,exam_id__2016-20a": 0.4,
+            "acc,exam_id__2014-14": 0.4875,
+            "acc,exam_id__2018-25": 0.425,
+            "acc,exam_id__2010-01": 0.3411764705882353,
+            "acc,exam_id__2014-13": 0.4,
+            "acc,exam_id__2013-12": 0.475,
+            "acc,exam_id__2016-20": 0.4125,
+            "acc,exam_id__2012-06a": 0.4875,
+            "acc,exam_id__2011-03": 0.35353535353535354,
+            "acc,exam_id__2011-04": 0.3625,
+            "acc,exam_id__2015-17": 0.5512820512820513,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.7141208181486736,
+            "acc,all": 0.7520564042303173
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.6666509531443612,
+            "acc,all": 0.7079601990049751,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7f8c200b76a0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7f8c200b76a0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f8c200b7060>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f8c200b7060>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8c200b72e0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8c200b72e0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f8c200b7880>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7f8c200b7880>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8c200b7b00>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
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-    "faquad_nli": {
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-      ],
-      "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": {
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-        "sampler_config": {
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         },
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-              "labels": [
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-                "Não"
-              ]
+        "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",
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             },
-            {
-              "function": "take_first"
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+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
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+                    "name": "all",
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+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
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+                }
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+            "should_decontaminate": false,
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-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-              "labels": [
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-                "Não"
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+        "hatebr_offensive": {
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+            "task_alias": "hatebr_offensive_binary",
+            "group": [
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+            "dataset_name": "HateBR_offensive_binary",
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+            "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",
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+            "fewshot_delimiter": "\n\n",
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             },
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-              "function": "take_first"
-            }
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-        }
-      ],
-      "should_decontaminate": false,
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-      "target_delimiter": " ",
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+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
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             },
-            {
-              "function": "remove_accents"
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+            "filter_list": [
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+                    "filter": [
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+                            "labels": [
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+                "pt_benchmark"
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+            "doc_to_text": "<function doc_to_text at 0x7f8c200b6a20>",
+            "doc_to_target": "{{answerKey}}",
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+            "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",
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+                    "id_column": "id",
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             },
-            {
-              "function": "find_choices",
-              "choices": [
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-                "B",
-                "C",
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-              "regex_patterns": [
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-                "\\b([ABCD]) ?[.):-]",
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             },
-            {
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+                            "function": "find_choices",
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-          "group_by": {
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-      "should_decontaminate": true,
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-              "function": "find_similar_label",
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-                "Não"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
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+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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 }

BAAI/Infinity-Instruct-3M-0613-Mistral-7B/results_2024-06-22T01-31-31.647844.json

@@ -34,8 +34,8 @@
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@@ -56,7 +56,7 @@
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@@ -150,9 +150,9 @@
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BAAI/Infinity-Instruct-3M-0625-Mistral-7B/raw_2024-07-19T01-41-09.242433/results.json

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-      "num_fewshot": 3,
-      "metric_list": [
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-      "output_type": "generate_until",
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-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "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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             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f6c7c73a520>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6c7c73a7a0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
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-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6c7c73a7a0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f6c7c73ad40>",
-      "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",
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-        "sampler": "id_sampler",
-        "sampler_config": {
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-      "num_fewshot": 3,
-      "metric_list": [
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-      "output_type": "generate_until",
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-        "temperature": 0.0,
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-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7f6c7c73ad40>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6c7c73afc0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6c7c73afc0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
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-            2227,
-            2813,
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-            558,
-            1503,
-            1958,
-            2918,
-            601,
-            1560,
-            984,
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-            995,
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-            301,
-            1185,
-            1315,
-            1420,
-            2436,
-            2322,
-            766
-          ]
-        }
-      },
-      "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
+                        558,
+                        1503,
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+                        2918,
+                        601,
+                        1560,
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+                        2388,
+                        995,
+                        2233,
+                        1982,
+                        165,
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+                        1312,
+                        2285,
+                        522,
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+                        323,
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+                        108,
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+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
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-          "id_column": "idx"
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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,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
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+                        44,
+                        36,
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+                        52,
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+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7f6c7c739ee0>",
-      "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": [
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-            "2010-01_11",
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-            "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
-        }
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-      "metric_list": [
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-          "aggregation": "acc",
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-        }
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7f6c7c739ee0>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
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+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
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+                    "group_by": {
+                        "column": "exam_id"
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+                }
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+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7f6c7c73a160>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
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-      "should_decontaminate": true,
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-      "task_alias": "portuguese_hate_speech_binary",
-      "group": [
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-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
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-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
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-                "Sim",
-                "Não"
-              ]
+        "portuguese_hate_speech": {
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+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. 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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+                        28,
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+                        34,
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+                        114,
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+                        36,
+                        5,
+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
+                    ],
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+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
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+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
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-      ],
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-              "function": "find_similar_label",
-              "labels": [
-                "Positivo",
-                "Neutro",
-                "Negativo"
-              ]
+        "tweetsentbr": {
+            "task": "tweetsentbr",
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+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/tweetsentbr_fewshot",
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+            "doc_to_text": "Texto: {{sentence}}\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 texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o sentimento do texto é Positivo, Neutro ou Negativo. Responda apenas com uma das opções.\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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-              "function": "take_first"
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+                },
+                {
+                    "metric": "acc",
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+                            "labels": [
+                                "Positivo",
+                                "Neutro",
+                                "Negativo"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
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BAAI/Infinity-Instruct-3M-0625-Mistral-7B/results_2024-07-19T01-41-09.242433.json

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CohereForAI/c4ai-command-r-v01/raw_2024-04-17T00-36-42.568466/results.json

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+            "acc,exam_id__2011-04": 0.4625,
+            "acc,exam_id__2013-10": 0.5875,
+            "acc,exam_id__2012-06a": 0.6375,
+            "acc,exam_id__2010-01": 0.4117647058823529,
+            "acc,exam_id__2017-23": 0.5625,
+            "acc,exam_id__2015-18": 0.5125,
+            "acc,exam_id__2012-06": 0.5375,
+            "acc,exam_id__2017-22": 0.6375,
+            "acc,exam_id__2014-15": 0.6538461538461539,
+            "acc,exam_id__2010-02": 0.62,
+            "acc,exam_id__2014-13": 0.5375,
+            "acc,exam_id__2016-20": 0.575,
+            "acc,exam_id__2011-05": 0.5875,
+            "acc,exam_id__2016-20a": 0.5625,
+            "acc,exam_id__2012-09": 0.45454545454545453,
+            "acc,exam_id__2017-24": 0.4875,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.7102306144559665,
+            "acc,all": 0.7285546415981199
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.6479415106683347,
+            "acc,all": 0.7114427860696517,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7fa6afa8cfe0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7fa6afa8cfe0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fa6afa8c9a0>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7fa6afa8c9a0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fa6afa8cc20>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fa6afa8cc20>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fa6afa8d1c0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7fa6afa8d1c0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fa6afa8d440>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
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-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fa6afa8d440>",
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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 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": {
-          "fewshot_indices": [
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-          "aggregation": "f1_macro",
-          "higher_is_better": true
         },
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-      ],
-      "output_type": "generate_until",
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-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
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-      "filter_list": [
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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 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",
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             },
-            {
-              "function": "take_first"
+            "num_fewshot": 15,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
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+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-      "task": "hatebr_offensive",
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-      "dataset_path": "eduagarcia/portuguese_benchmark",
-      "dataset_name": "HateBR_offensive_binary",
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-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto é ofensivo?\nResposta:",
-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
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+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-      "dataset_path": "eduagarcia/oab_exams",
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-      "doc_to_text": "<function doc_to_text at 0x7fa6afa8c360>",
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-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
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-        "sampler_config": {
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-      "repeats": 1,
-      "filter_list": [
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-              "function": "normalize_spaces"
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+            "metric_list": [
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+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            "output_type": "generate_until",
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "remove_accents"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
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+                        {
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+                }
+            ],
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+            "metadata": {
+                "version": 1.0
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+        "oab_exams": {
+            "task": "oab_exams",
+            "group": [
+                "legal_benchmark",
+                "pt_benchmark"
+            ],
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+            "test_split": "train",
+            "fewshot_split": "train",
+            "doc_to_text": "<function doc_to_text at 0x7fa6afa8c360>",
+            "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",
+                        "2010-01_26",
+                        "2010-01_28",
+                        "2010-01_38",
+                        "2010-01_48",
+                        "2010-01_58",
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+                        "2010-01_76",
+                        "2010-01_83",
+                        "2010-01_85",
+                        "2010-01_91",
+                        "2010-01_99"
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+                    "id_column": "id",
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+                }
             },
-            {
-              "function": "find_choices",
-              "choices": [
-                "A",
-                "B",
-                "C",
-                "D"
-              ],
-              "regex_patterns": [
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-                "\\b([ABCD])\\.",
-                "\\b([ABCD]) ?[.):-]",
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-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
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+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            ],
+            "output_type": "generate_until",
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+                "do_sample": false,
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+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
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+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
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+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
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+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
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+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
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+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7fa6afa8c5e0>",
+            "metadata": {
+                "version": 1.5
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-          ],
-          "group_by": {
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-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7fa6afa8c5e0>",
-      "metadata": {
-        "version": 1.5
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-    "portuguese_hate_speech": {
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-      "num_fewshot": 25,
-      "metric_list": [
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-          "metric": "f1_macro",
-          "aggregation": "f1_macro",
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         },
-        {
-          "metric": "acc",
-          "aggregation": "acc",
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-      ],
-      "output_type": "generate_until",
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-        "temperature": 0.0,
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. 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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 }

CohereForAI/c4ai-command-r-v01/results_2024-04-17T00-36-42.568466.json

@@ -34,8 +34,8 @@
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@@ -56,7 +56,7 @@
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         "harness|enem_challenge|enem_challenge|None|3": {
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@@ -150,9 +150,9 @@
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Columbia-NLP/LION-LLaMA-3-8b-odpo-v1.0/raw_2024-07-15T01-32-05.828202/results.json

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-          ],
-          "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,
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-        "top_p": null,
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-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f783ec42520>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f783ec427a0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f783ec427a0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f783ec42d40>",
-      "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": [
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-            "2022_88",
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-          "id_column": "id",
-          "exclude_from_task": true
-        }
-      },
-      "num_fewshot": 3,
-      "metric_list": [
-        {
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-          "aggregation": "acc",
-          "higher_is_better": true
-        }
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-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
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-        "until": [
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-      },
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-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7f783ec42d40>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f783ec42fc0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f783ec42fc0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
-            2910,
-            2227,
-            2813,
-            974,
-            558,
-            1503,
-            1958,
-            2918,
-            601,
-            1560,
-            984,
-            2388,
-            995,
-            2233,
-            1982,
-            165,
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-            108,
-            301,
-            1185,
-            1315,
-            1420,
-            2436,
-            2322,
-            766
-          ]
-        }
-      },
-      "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
+                        558,
+                        1503,
+                        1958,
+                        2918,
+                        601,
+                        1560,
+                        984,
+                        2388,
+                        995,
+                        2233,
+                        1982,
+                        165,
+                        2788,
+                        1312,
+                        2285,
+                        522,
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+                        323,
+                        236,
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+                        108,
+                        301,
+                        1185,
+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
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-            0,
-            12,
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-          "id_column": "idx"
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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,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
+                        48,
+                        44,
+                        36,
+                        20,
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+                        24,
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+                        52,
+                        72,
+                        8,
+                        3571,
+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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",
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-      "doc_to_text": "<function doc_to_text at 0x7f783ec41ee0>",
-      "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": {
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-      "filter_list": [
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-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
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+                    "aggregation": "acc",
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+                }
+            ],
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+            "generation_kwargs": {
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "remove_accents"
+            "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 0x7f783ec41ee0>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
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+            ],
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+                "do_sample": false,
+                "temperature": 0.0,
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             },
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-              "function": "take_first"
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+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
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+                        },
+                        {
+                            "function": "take_first"
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+                        "column": "exam_id"
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+            "doc_to_decontamination_query": "<function doc_to_text at 0x7f783ec42160>",
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             }
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-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
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-                "Não"
-              ]
+        "portuguese_hate_speech": {
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+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
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+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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+                "sampler_config": {
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+                        39,
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+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
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+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
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+                        },
+                        {
+                            "function": "take_first"
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-                "Negativo"
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+                {
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+                                "Positivo",
+                                "Neutro",
+                                "Negativo"
+                            ]
+                        },
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+                            "function": "take_first"
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Columbia-NLP/LION-LLaMA-3-8b-odpo-v1.0/results_2024-07-15T01-32-05.828202.json

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CultriX/NeuralMona_MoE-4x7B/raw_2024-05-26T13-29-26.736769/results.json

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+            "alias": "enem",
+            "acc,all": 0.6312106368089573,
+            "acc,exam_id__2011": 0.6410256410256411,
+            "acc,exam_id__2017": 0.6379310344827587,
+            "acc,exam_id__2015": 0.6218487394957983,
+            "acc,exam_id__2016": 0.5537190082644629,
+            "acc,exam_id__2016_2": 0.6341463414634146,
+            "acc,exam_id__2009": 0.6173913043478261,
+            "acc,exam_id__2012": 0.6379310344827587,
+            "acc,exam_id__2010": 0.7008547008547008,
+            "acc,exam_id__2013": 0.6851851851851852,
+            "acc,exam_id__2014": 0.6055045871559633,
+            "acc,exam_id__2022": 0.6090225563909775,
+            "acc,exam_id__2023": 0.6370370370370371
+        },
+        "faquad_nli": {
+            "f1_macro,all": 0.7694314032342202,
+            "acc,all": 0.816923076923077,
+            "alias": "faquad_nli"
+        },
+        "hatebr_offensive": {
+            "alias": "hatebr_offensive_binary",
+            "f1_macro,all": 0.8409826856991804,
+            "acc,all": 0.8428571428571429
+        },
+        "oab_exams": {
+            "acc,all": 0.4214123006833713,
+            "acc,exam_id__2011-03": 0.3333333333333333,
+            "acc,exam_id__2014-13": 0.325,
+            "acc,exam_id__2013-10": 0.4125,
+            "acc,exam_id__2017-24": 0.4,
+            "acc,exam_id__2017-22": 0.5375,
+            "acc,exam_id__2012-06a": 0.375,
+            "acc,exam_id__2016-20a": 0.3375,
+            "acc,exam_id__2012-09": 0.38961038961038963,
+            "acc,exam_id__2015-16": 0.4125,
+            "acc,exam_id__2011-04": 0.4125,
+            "acc,exam_id__2012-07": 0.3625,
+            "acc,exam_id__2014-14": 0.5375,
+            "acc,exam_id__2014-15": 0.46153846153846156,
+            "acc,exam_id__2010-02": 0.44,
+            "acc,exam_id__2015-18": 0.4125,
+            "acc,exam_id__2016-19": 0.5128205128205128,
+            "acc,exam_id__2012-06": 0.4625,
+            "acc,exam_id__2013-12": 0.425,
+            "acc,exam_id__2011-05": 0.4875,
+            "acc,exam_id__2017-23": 0.3875,
+            "acc,exam_id__2013-11": 0.475,
+            "acc,exam_id__2016-20": 0.4,
+            "acc,exam_id__2016-21": 0.3625,
+            "acc,exam_id__2018-25": 0.4375,
+            "acc,exam_id__2010-01": 0.3764705882352941,
+            "acc,exam_id__2012-08": 0.4125,
+            "acc,exam_id__2015-17": 0.5128205128205128,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.6819724557061289,
+            "acc,all": 0.7132784958871915
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.6446949695921868,
+            "acc,all": 0.6955223880597015,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7f80d069a200>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7f80d069a200>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f80d0699bc0>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f80d0699bc0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f80d0699e40>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f80d0699e40>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f80d069a3e0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7f80d069a3e0>",
+            "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
+                }
             },
-            {
-              "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]) ?[.):-]",
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+                    "aggregation": "acc",
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+            "output_type": "generate_until",
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+                        {
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-          ],
-          "group_by": {
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-      "target_delimiter": " ",
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+        "faquad_nli": {
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+            "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": " ",
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+                                "Não"
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+                        {
+                            "function": "take_first"
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-                "Não"
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-          "group_by": {
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-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7f80d0699800>",
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-      "metric_list": [
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-          "aggregation": "f1_macro",
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 }

CultriX/NeuralMona_MoE-4x7B/results_2024-05-26T13-29-26.736769.json

@@ -34,8 +34,8 @@
         "eval_version": "1.1.0"
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     "results": {
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-        "all_grouped_npm": 0.5184879950941655,
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             "bluex": 0.5340751043115438,
@@ -45,7 +45,7 @@
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             "portuguese_hate_speech": 0.6819724557061289,
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             "harness|enem_challenge|enem_challenge|None|3": 0.6312106368089573,
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             "harness|portuguese_hate_speech|portuguese_hate_speech|None|25": 0.6819724557061289,
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         "harness|enem_challenge|enem_challenge|None|3": {
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@@ -150,9 +150,9 @@
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         "harness|tweetsentbr|tweetsentbr|None|25": {
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Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO/raw_2024-08-08T02-43-35.640819/results.json

@@ -1,1244 +1,1244 @@
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+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
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-    "bluex": {
-      "task": "bluex",
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-        "pt_benchmark",
-        "vestibular"
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-      "test_split": "train",
-      "fewshot_split": "train",
-      "doc_to_text": "<function enem_doc_to_text at 0x7f39df64a2a0>",
-      "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": [
-            "USP_2018_3",
-            "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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-      "num_fewshot": 3,
-      "metric_list": [
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-          "metric": "acc",
-          "aggregation": "acc",
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-      "output_type": "generate_until",
-      "generation_kwargs": {
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-        "do_sample": false,
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-        "until": [
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f39df64a2a0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f39df64a520>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f39df64a520>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f39df64aac0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7f39df64aac0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f39df64ad40>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f39df64ad40>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
-            2910,
-            2227,
-            2813,
-            974,
-            558,
-            1503,
-            1958,
-            2918,
-            601,
-            1560,
-            984,
-            2388,
-            995,
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-            2816,
-            108,
-            301,
-            1185,
-            1315,
-            1420,
-            2436,
-            2322,
-            766
-          ]
-        }
-      },
-      "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
+                        558,
+                        1503,
+                        1958,
+                        2918,
+                        601,
+                        1560,
+                        984,
+                        2388,
+                        995,
+                        2233,
+                        1982,
+                        165,
+                        2788,
+                        1312,
+                        2285,
+                        522,
+                        1113,
+                        1670,
+                        323,
+                        236,
+                        1263,
+                        1562,
+                        2519,
+                        1049,
+                        432,
+                        1167,
+                        1394,
+                        2022,
+                        2551,
+                        2194,
+                        2187,
+                        2282,
+                        2816,
+                        108,
+                        301,
+                        1185,
+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
-            48,
-            44,
-            36,
-            20,
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-            3551,
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-            3503,
-            84,
-            3539,
-            64,
-            3599,
-            80,
-            3563,
-            3559,
-            3543,
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-            3587,
-            3595,
-            3575,
-            3567,
-            3591,
-            24,
-            96,
-            92,
-            3507,
-            52,
-            72,
-            8,
-            3571,
-            3515,
-            3519,
-            3531,
-            28,
-            32,
-            0,
-            12,
-            3583
-          ],
-          "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": {
-        "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"
-              ]
+        "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",
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+            "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": " ",
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+                    "id_list": [
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+                        "2010-01_11",
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             },
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-              "function": "find_choices",
-              "choices": [
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-                "\\b([ABCD]) ?[.):-]",
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-                "Não"
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+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
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+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
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+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
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+                            "function": "take_first"
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Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO/results_2024-08-08T02-43-35.640819.json

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Danielbrdz/Barcenas-Llama3-8b-ORPO/raw_2024-05-18T00-12-52.690138/results.json

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+            "acc,exam_id__2012": 0.7155172413793104,
+            "acc,exam_id__2017": 0.6896551724137931,
+            "acc,exam_id__2013": 0.6851851851851852,
+            "acc,exam_id__2016": 0.7024793388429752,
+            "acc,exam_id__2011": 0.7264957264957265,
+            "acc,exam_id__2015": 0.7310924369747899,
+            "acc,exam_id__2022": 0.6766917293233082,
+            "acc,exam_id__2014": 0.7155963302752294,
+            "acc,exam_id__2010": 0.7435897435897436,
+            "acc,exam_id__2009": 0.7304347826086957,
+            "acc,exam_id__2016_2": 0.6504065040650406,
+            "acc,exam_id__2023": 0.7555555555555555
+        },
+        "faquad_nli": {
+            "f1_macro,all": 0.7308849598805747,
+            "acc,all": 0.7815384615384615,
+            "alias": "faquad_nli"
+        },
+        "hatebr_offensive": {
+            "alias": "hatebr_offensive_binary",
+            "f1_macro,all": 0.8698828946051447,
+            "acc,all": 0.87
+        },
+        "oab_exams": {
+            "acc,all": 0.508883826879271,
+            "acc,exam_id__2014-15": 0.6282051282051282,
+            "acc,exam_id__2012-07": 0.4625,
+            "acc,exam_id__2016-20a": 0.4375,
+            "acc,exam_id__2015-16": 0.5,
+            "acc,exam_id__2016-21": 0.4,
+            "acc,exam_id__2013-10": 0.475,
+            "acc,exam_id__2014-13": 0.425,
+            "acc,exam_id__2010-02": 0.52,
+            "acc,exam_id__2012-06": 0.5125,
+            "acc,exam_id__2018-25": 0.5125,
+            "acc,exam_id__2011-04": 0.5125,
+            "acc,exam_id__2012-08": 0.5125,
+            "acc,exam_id__2015-18": 0.5,
+            "acc,exam_id__2011-05": 0.4625,
+            "acc,exam_id__2012-09": 0.4935064935064935,
+            "acc,exam_id__2017-24": 0.4625,
+            "acc,exam_id__2012-06a": 0.5375,
+            "acc,exam_id__2016-20": 0.5625,
+            "acc,exam_id__2013-12": 0.575,
+            "acc,exam_id__2016-19": 0.5128205128205128,
+            "acc,exam_id__2014-14": 0.575,
+            "acc,exam_id__2017-22": 0.6,
+            "acc,exam_id__2010-01": 0.4,
+            "acc,exam_id__2011-03": 0.48484848484848486,
+            "acc,exam_id__2015-17": 0.6410256410256411,
+            "acc,exam_id__2017-23": 0.525,
+            "acc,exam_id__2013-11": 0.525,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.5958643988009942,
+            "acc,all": 0.5969447708578144
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.6661915330469502,
+            "acc,all": 0.7203980099502487,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7f4883d942c0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7f4883d942c0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f4883f5bc40>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f4883f5bc40>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f4883f5bec0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f4883f5bec0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f4883d944a0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7f4883d944a0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
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+            "num_fewshot": 3,
+            "metric_list": [
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+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
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+                        {
+                            "function": "normalize_spaces"
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+                        {
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+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
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+                        {
+                            "function": "take_first"
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+                    "group_by": {
+                        "column": "exam_id"
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+                }
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+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f4883d94720>",
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-          ],
-          "group_by": {
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-      "dataset_path": "ruanchaves/faquad-nli",
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-      "fewshot_split": "train",
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-      "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",
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-              ]
+        "faquad_nli": {
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+            "group": [
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+            ],
+            "dataset_path": "ruanchaves/faquad-nli",
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+            "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",
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             },
-            {
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+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
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+                }
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-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-                "Não"
-              ]
+        "hatebr_offensive": {
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+            "group": [
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+            "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",
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-              "function": "take_first"
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-          ]
-        }
-      ],
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+                            "function": "find_choices",
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+                                "\\b([ABCD]) ?[.):-]",
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+                        {
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-          ],
-          "group_by": {
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-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7f4883f5b880>",
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-        "version": 1.5
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-    "portuguese_hate_speech": {
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-      "group": [
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-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
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-      "num_fewshot": 25,
-      "metric_list": [
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-          "metric": "f1_macro",
-          "aggregation": "f1_macro",
-          "higher_is_better": true
         },
-        {
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 }

Danielbrdz/Barcenas-Llama3-8b-ORPO/results_2024-05-18T00-12-52.690138.json

@@ -34,8 +34,8 @@
         "eval_version": "1.1.0"
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     "results": {
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@@ -45,7 +45,7 @@
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             "portuguese_hate_speech": 0.5958643988009942,
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             "harness|portuguese_hate_speech|portuguese_hate_speech|None|25": 0.5958643988009942,
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         "harness|enem_challenge|enem_challenge|None|3": {
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@@ -150,9 +150,9 @@
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DeepMount00/Llama-3-8b-Ita/raw_2024-05-19T23-04-56.757278/results.json

@@ -1,1244 +1,1244 @@
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+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-    "bluex": {
-      "task": "bluex",
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-        "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 0x7f986e583b00>",
-      "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": [
-            "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": [
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-          "metric": "acc",
-          "aggregation": "acc",
-          "higher_is_better": true
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-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
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-        "until": [
-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f986e583b00>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f986e583d80>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f986e583d80>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f986e583560>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7f986e583560>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f986e583880>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f986e583880>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
-            2910,
-            2227,
-            2813,
-            974,
-            558,
-            1503,
-            1958,
-            2918,
-            601,
-            1560,
-            984,
-            2388,
-            995,
-            2233,
-            1982,
-            165,
-            2788,
-            1312,
-            2285,
-            522,
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-            323,
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-            2519,
-            1049,
-            432,
-            1167,
-            1394,
-            2022,
-            2551,
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-            2187,
-            2282,
-            2816,
-            108,
-            301,
-            1185,
-            1315,
-            1420,
-            2436,
-            2322,
-            766
-          ]
-        }
-      },
-      "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
+                        558,
+                        1503,
+                        1958,
+                        2918,
+                        601,
+                        1560,
+                        984,
+                        2388,
+                        995,
+                        2233,
+                        1982,
+                        165,
+                        2788,
+                        1312,
+                        2285,
+                        522,
+                        1113,
+                        1670,
+                        323,
+                        236,
+                        1263,
+                        1562,
+                        2519,
+                        1049,
+                        432,
+                        1167,
+                        1394,
+                        2022,
+                        2551,
+                        2194,
+                        2187,
+                        2282,
+                        2816,
+                        108,
+                        301,
+                        1185,
+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
-            48,
-            44,
-            36,
-            20,
-            3511,
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-            3551,
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-            3503,
-            84,
-            3539,
-            64,
-            3599,
-            80,
-            3563,
-            3559,
-            3543,
-            3547,
-            3587,
-            3595,
-            3575,
-            3567,
-            3591,
-            24,
-            96,
-            92,
-            3507,
-            52,
-            72,
-            8,
-            3571,
-            3515,
-            3519,
-            3531,
-            28,
-            32,
-            0,
-            12,
-            3583
-          ],
-          "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": {
-        "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"
-              ]
+        "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": {
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             },
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-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-    "oab_exams": {
-      "task": "oab_exams",
-      "group": [
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+            "metric_list": [
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+                    "aggregation": "f1_macro",
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+            "doc_to_text": "<function doc_to_text at 0x7f986e5831a0>",
+            "doc_to_target": "{{answerKey}}",
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+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        "2010-01_1",
+                        "2010-01_11",
+                        "2010-01_13",
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+                        "2010-01_91",
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             },
-            {
-              "function": "find_choices",
-              "choices": [
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-                "B",
-                "C",
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-              ],
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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])\\b"
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+            "num_fewshot": 3,
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             },
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+                        {
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+                        {
+                            "function": "find_choices",
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-            {
-              "function": "find_similar_label",
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-                "Não"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
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+                        },
+                        {
+                            "function": "take_first"
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-              "function": "find_similar_label",
-              "labels": [
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-                "Neutro",
-                "Negativo"
-              ]
+        "tweetsentbr": {
+            "task": "tweetsentbr",
+            "group": [
+                "pt_benchmark"
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+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O sentimento do texto é Positivo, Neutro ou Negativo?\nResposta:",
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+            "description": "Abaixo contém o texto de tweets de usuários 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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+                                "Negativo"
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DeepMount00/Llama-3-8b-Ita/results_2024-05-19T23-04-56.757278.json

@@ -34,8 +34,8 @@
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EleutherAI/pythia-14m/raw_2024-04-03T19-47-56.339960/results.json

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+            "alias": "enem",
+            "acc,all": 0.19104268719384185,
+            "acc,exam_id__2013": 0.16666666666666666,
+            "acc,exam_id__2012": 0.19827586206896552,
+            "acc,exam_id__2015": 0.14285714285714285,
+            "acc,exam_id__2016": 0.18181818181818182,
+            "acc,exam_id__2009": 0.16521739130434782,
+            "acc,exam_id__2023": 0.25925925925925924,
+            "acc,exam_id__2016_2": 0.1951219512195122,
+            "acc,exam_id__2010": 0.1623931623931624,
+            "acc,exam_id__2014": 0.1834862385321101,
+            "acc,exam_id__2022": 0.21804511278195488,
+            "acc,exam_id__2011": 0.19658119658119658,
+            "acc,exam_id__2017": 0.20689655172413793
+        },
+        "faquad_nli": {
+            "f1_macro,all": 0.4396551724137931,
+            "acc,all": 0.7846153846153846,
+            "alias": "faquad_nli"
+        },
+        "hatebr_offensive": {
+            "alias": "hatebr_offensive_binary",
+            "f1_macro,all": 0.259929067077872,
+            "acc,all": 0.23142857142857143
+        },
+        "oab_exams": {
+            "acc,all": 0.21822323462414578,
+            "acc,exam_id__2011-03": 0.23232323232323232,
+            "acc,exam_id__2011-04": 0.25,
+            "acc,exam_id__2011-05": 0.2375,
+            "acc,exam_id__2016-19": 0.1794871794871795,
+            "acc,exam_id__2017-23": 0.2,
+            "acc,exam_id__2018-25": 0.25,
+            "acc,exam_id__2012-09": 0.23376623376623376,
+            "acc,exam_id__2017-24": 0.2125,
+            "acc,exam_id__2014-14": 0.2625,
+            "acc,exam_id__2015-17": 0.23076923076923078,
+            "acc,exam_id__2012-07": 0.1,
+            "acc,exam_id__2016-20": 0.2,
+            "acc,exam_id__2013-11": 0.1625,
+            "acc,exam_id__2016-21": 0.2125,
+            "acc,exam_id__2012-06a": 0.2125,
+            "acc,exam_id__2015-18": 0.25,
+            "acc,exam_id__2012-08": 0.2125,
+            "acc,exam_id__2013-12": 0.175,
+            "acc,exam_id__2012-06": 0.225,
+            "acc,exam_id__2015-16": 0.225,
+            "acc,exam_id__2013-10": 0.2,
+            "acc,exam_id__2014-13": 0.225,
+            "acc,exam_id__2010-02": 0.21,
+            "acc,exam_id__2014-15": 0.20512820512820512,
+            "acc,exam_id__2016-20a": 0.2875,
+            "acc,exam_id__2010-01": 0.25882352941176473,
+            "acc,exam_id__2017-22": 0.2375,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.4038189533239038,
+            "acc,all": 0.6709753231492362
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.011187176063075921,
+            "acc,all": 0.004975124378109453,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7fc263b9be20>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7fc263b9be20>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fc263b9b7e0>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7fc263b9b7e0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fc263b9ba60>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fc263b9ba60>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fc263be4040>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7fc263be4040>",
+            "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
+                }
             },
-            {
-              "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])$",
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+            "num_fewshot": 3,
+            "metric_list": [
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+                    "metric": "acc",
+                    "aggregation": "acc",
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+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
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+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
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+                        {
+                            "function": "take_first"
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+                        "column": "exam_id"
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+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fc263be42c0>",
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-          ],
-          "group_by": {
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-      "should_decontaminate": true,
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-      "dataset_path": "ruanchaves/faquad-nli",
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-      "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": " ",
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-              ]
+        "faquad_nli": {
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+            "group": [
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+            ],
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+            "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": " ",
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             },
-            {
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+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
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+                        {
+                            "function": "take_first"
+                        }
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-                "Não"
-              ]
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+            "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",
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-              "function": "take_first"
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+                                "\\b([ABCD]) ?[.):-]",
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-          ],
-          "group_by": {
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-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7fc263b9b420>",
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-        "version": 1.5
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-    "portuguese_hate_speech": {
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-      "target_delimiter": " ",
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-      "num_fewshot": 25,
-      "metric_list": [
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-          "metric": "f1_macro",
-          "aggregation": "f1_macro",
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-                "Não"
-              ]
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+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
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+            "dataset_name": "Portuguese_Hate_Speech_binary",
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+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
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EleutherAI/pythia-14m/results_2024-04-03T19-47-56.339960.json

@@ -34,29 +34,29 @@
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EleutherAI/pythia-70m-deduped/raw_2024-04-03T21-10-06.848681/results.json

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+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.1747835497835498,
+            "acc,all": 0.29502487562189056,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7f92c3f736a0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7f92c3f736a0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f92c3f73060>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f92c3f73060>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f92c3f732e0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f92c3f732e0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f92c3f73880>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7f92c3f73880>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f92c3f73b00>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f92c3f73b00>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
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-            1982,
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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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
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+                        663,
+                        105,
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             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
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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,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
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+                        44,
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+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
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+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7f92c3f72a20>",
-      "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",
-            "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"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7f92c3f72a20>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7f92c3f72ca0>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7f92c3f72ca0>",
-      "metadata": {
-        "version": 1.5
-      }
-    },
-    "portuguese_hate_speech": {
-      "task": "portuguese_hate_speech",
-      "task_alias": "portuguese_hate_speech_binary",
-      "group": [
-        "pt_benchmark"
-      ],
-      "dataset_path": "eduagarcia/portuguese_benchmark",
-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
-      "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. 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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-            39,
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-            5,
-            6,
-            10,
-            35,
-            38,
-            0,
-            21,
-            46
-          ],
-          "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": {
-        "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"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        52,
+                        50,
+                        39,
+                        28,
+                        3,
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+                        22,
+                        25,
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+                        114,
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+                        36,
+                        5,
+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
+                    ],
+                    "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": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
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EleutherAI/pythia-70m-deduped/results_2024-04-03T21-10-06.848681.json

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EleutherAI/pythia-70m/raw_2024-04-24T21-25-37.361813/results.json

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+                {
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+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            ],
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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+                    "\n\n"
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
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             }
-          ]
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-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
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-        "assin2"
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-      "dataset_path": "assin2",
-      "test_split": "test",
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-      "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 0x7ff221d8ff60>",
-      "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": " ",
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-          "higher_is_better": true
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-        {
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-              "on_outside_range": "clip",
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+        "assin2_sts": {
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+            "doc_to_target": "<function assin2_float_to_pt_str at 0x7ff221d8ff60>",
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+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
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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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+            "metadata": {
+                "version": 1.1
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+                "pt_benchmark",
+                "vestibular"
+            ],
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+            "test_split": "train",
+            "fewshot_split": "train",
+            "doc_to_text": "<function enem_doc_to_text at 0x7ff221d8f600>",
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+            "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"
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+                            "function": "find_choices",
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+                                "A",
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+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
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+                                "\\b([ABCDE])\\.",
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-      "task": "enem_challenge",
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-        "vestibular"
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+            "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 0x7ff221d8f060>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            "output_type": "generate_until",
+            "generation_kwargs": {
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-            {
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+                            "function": "normalize_spaces"
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+                            "function": "remove_accents"
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+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff221d8f380>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
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-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff221d8f380>",
-      "metadata": {
-        "version": 1.1
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-    },
-    "faquad_nli": {
-      "task": "faquad_nli",
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-        "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",
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-          "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
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-      ],
-      "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": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
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+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
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+                                "Neutro",
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 }

EleutherAI/pythia-70m/results_2024-04-24T21-25-37.361813.json

@@ -34,8 +34,8 @@
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@@ -150,9 +150,9 @@
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FuseAI/FuseChat-7B-VaRM/raw_2024-03-08T15-26-39.517660/results.json

@@ -1,1324 +1,1324 @@
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-      "acc,exam_id__2014-15": 0.44871794871794873,
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-      "acc,exam_id__2016-20": 0.375,
-      "acc,exam_id__2011-03": 0.3333333333333333,
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-      "alias": "tweetsentbr"
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-      "group": [
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-        "assin2"
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-      "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]}}",
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-          "aggregation": "f1_macro",
-          "higher_is_better": true
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         },
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-          "aggregation": "acc",
-          "higher_is_better": true
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+            "acc,exam_id__UNICAMP_2022": 0.6153846153846154,
+            "acc,exam_id__UNICAMP_2024": 0.5555555555555556,
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+            "acc,exam_id__2014": 0.6605504587155964
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+            "acc,exam_id__2015-18": 0.45,
+            "acc,exam_id__2016-19": 0.47435897435897434,
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+            "acc,exam_id__2011-03": 0.3333333333333333,
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         }
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-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
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-          "filter": [
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-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
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+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
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+                        3251,
+                        2,
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+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
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+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
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+                        {
+                            "function": "take_first"
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-      "metadata": {
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-      "target_delimiter": " ",
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-          "aggregation": "mean_squared_error",
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-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "assin2_sts": {
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+                "assin2"
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+            "dataset_path": "assin2",
+            "test_split": "test",
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+            "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 0x7f116cc853a0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
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+                        22,
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             },
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+                {
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+                    "aggregation": "mean_squared_error",
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+                "until": [
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             },
-            {
-              "function": "remove_accents"
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+            "filter_list": [
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+                    "filter": [
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+                            "type": "float",
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+            ],
+            "should_decontaminate": false,
+            "metadata": {
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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 0x7f116cc84d60>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
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+                    "id_column": "id",
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             },
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-                "\\b([ABCDE])\\.",
-                "\\b([ABCDE]) ?[.):-]",
-                "\\b([ABCDE])$",
-                "\\b([ABCDE])\\b"
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             },
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+            "filter_list": [
+                {
+                    "name": "all",
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+                        {
+                            "function": "normalize_spaces"
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+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
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+                        {
+                            "function": "take_first"
+                        }
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+                        "column": "exam_id"
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+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f116cc84fe0>",
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-      "should_decontaminate": true,
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-    "enem_challenge": {
-      "task": "enem_challenge",
-      "task_alias": "enem",
-      "group": [
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-        "vestibular"
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-      "dataset_path": "eduagarcia/enem_challenge",
-      "test_split": "train",
-      "fewshot_split": "train",
-      "doc_to_text": "<function enem_doc_to_text at 0x7f116cc85580>",
-      "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": " ",
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-              "function": "remove_accents"
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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 0x7f116cc85580>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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-            {
-              "function": "take_first"
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+                    "name": "all",
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+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
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+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f116cc85800>",
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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 0x7f116cc85800>",
-      "metadata": {
-        "version": 1.1
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-      "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 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": {
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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"
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-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
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+                        105,
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+                }
             },
-            {
-              "function": "take_first"
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+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
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+                }
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+                "do_sample": false,
+                "temperature": 0.0,
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+                "top_p": null,
+                "until": [
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
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-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
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-    },
-    "hatebr_offensive": {
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-      "task_alias": "hatebr_offensive_binary",
-      "group": [
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-      ],
-      "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",
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-        "temperature": 0.0,
-        "top_k": null,
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-          "\n\n"
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-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
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+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.0
-      }
-    },
-    "oab_exams": {
-      "task": "oab_exams",
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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 0x7f116cc84720>",
-      "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": [
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-            "2010-01_11",
-            "2010-01_13",
-            "2010-01_23",
-            "2010-01_26",
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-            "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",
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-      },
-      "num_fewshot": 3,
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-      "repeats": 1,
-      "filter_list": [
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-          "name": "all",
-          "filter": [
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-              "function": "normalize_spaces"
+            "num_fewshot": 25,
+            "metric_list": [
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+                    "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": [
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             },
-            {
-              "function": "remove_accents"
+            "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 0x7f116cc84720>",
+            "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",
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FuseAI/FuseChat-7B-VaRM/results_2024-03-08T15-26-39.517660.json

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GritLM/GritLM-7B-KTO/raw_2024-06-15T00-03-38.180499/results.json

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+            "acc,exam_id__2015": 0.5966386554621849,
+            "acc,exam_id__2013": 0.5462962962962963,
+            "acc,exam_id__2023": 0.5925925925925926,
+            "acc,exam_id__2022": 0.6165413533834586,
+            "acc,exam_id__2016_2": 0.5691056910569106,
+            "acc,exam_id__2012": 0.5517241379310345,
+            "acc,exam_id__2016": 0.5537190082644629,
+            "acc,exam_id__2009": 0.5217391304347826
+        },
+        "faquad_nli": {
+            "f1_macro,all": 0.7270998493492381,
+            "acc,all": 0.7646153846153846,
+            "alias": "faquad_nli"
+        },
+        "hatebr_offensive": {
+            "alias": "hatebr_offensive_binary",
+            "f1_macro,all": 0.7778660429262838,
+            "acc,all": 0.7842857142857143
+        },
+        "oab_exams": {
+            "acc,all": 0.4031890660592255,
+            "acc,exam_id__2015-17": 0.5,
+            "acc,exam_id__2015-18": 0.425,
+            "acc,exam_id__2014-14": 0.4875,
+            "acc,exam_id__2012-09": 0.37662337662337664,
+            "acc,exam_id__2016-20a": 0.3375,
+            "acc,exam_id__2012-06": 0.425,
+            "acc,exam_id__2017-23": 0.375,
+            "acc,exam_id__2010-01": 0.4,
+            "acc,exam_id__2011-04": 0.3125,
+            "acc,exam_id__2011-05": 0.4375,
+            "acc,exam_id__2014-13": 0.3125,
+            "acc,exam_id__2016-20": 0.35,
+            "acc,exam_id__2013-10": 0.275,
+            "acc,exam_id__2016-19": 0.46153846153846156,
+            "acc,exam_id__2016-21": 0.3375,
+            "acc,exam_id__2012-06a": 0.4,
+            "acc,exam_id__2012-07": 0.4375,
+            "acc,exam_id__2015-16": 0.4,
+            "acc,exam_id__2013-11": 0.4125,
+            "acc,exam_id__2018-25": 0.475,
+            "acc,exam_id__2017-24": 0.3875,
+            "acc,exam_id__2010-02": 0.44,
+            "acc,exam_id__2012-08": 0.4125,
+            "acc,exam_id__2014-15": 0.47435897435897434,
+            "acc,exam_id__2011-03": 0.3434343434343434,
+            "acc,exam_id__2013-12": 0.4875,
+            "acc,exam_id__2017-22": 0.4125,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.71169854421558,
+            "acc,all": 0.7532314923619271
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.6012020713873997,
+            "acc,all": 0.673134328358209,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7feb2c64b560>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7feb2c64b560>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
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+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7feb2c64b600>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7feb2c64b600>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7feb2c64b880>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7feb2c64b880>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7feb2c64a7a0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7feb2c64a7a0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
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+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
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+        "faquad_nli": {
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+            "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": " ",
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+                                "Não"
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+                        {
+                            "function": "take_first"
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-          "group_by": {
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-      "doc_to_decontamination_query": "<function doc_to_text at 0x7feb2c64af20>",
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-          "aggregation": "f1_macro",
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-        {
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 }

GritLM/GritLM-7B-KTO/results_2024-06-15T00-03-38.180499.json

@@ -34,8 +34,8 @@
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         "all_grouped": {
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             "faquad_nli": 0.7270998493492381,
             "hatebr_offensive": 0.7778660429262838,
             "portuguese_hate_speech": 0.71169854421558,
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             "harness|enem_challenge|enem_challenge|None|3": 0.5808257522743177,
@@ -56,7 +56,7 @@
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             "harness|hatebr_offensive|hatebr_offensive|None|25": 0.7778660429262838,
             "harness|portuguese_hate_speech|portuguese_hate_speech|None|25": 0.71169854421558,
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         "harness|enem_challenge|enem_challenge|None|3": {
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@@ -150,9 +150,9 @@
             "main_score": 0.71169854421558
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         "harness|tweetsentbr|tweetsentbr|None|25": {
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             "acc,all": 0.673134328358209,
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     "config_tasks": {

GritLM/GritLM-7B/raw_2024-06-12T20-31-09.833902/results.json

@@ -1,1244 +1,1244 @@
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             },
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-      ],
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+            "metric_list": [
+                {
+                    "metric": "pearson",
+                    "aggregation": "pearsonr",
+                    "higher_is_better": true
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+                {
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+                "top_k": null,
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             },
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-              "function": "remove_accents"
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+                        {
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+                            "range_min": 1.0,
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+                            "on_outside_range": "clip",
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+                        },
+                        {
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+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
+            }
+        },
+        "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 0x7f6ec2577ba0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "function": "find_choices",
-              "choices": [
-                "A",
-                "B",
-                "C",
-                "D",
-                "E"
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-                "(?:[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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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+                "until": [
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             },
-            {
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+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6ec2577e20>",
+            "metadata": {
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             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6ec2577e20>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f6ec2577600>",
-      "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": [
-        {
-          "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,
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-          "\n\n"
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-      },
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-      "filter_list": [
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-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7f6ec2577600>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6ec2577920>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f6ec2577920>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
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-            2227,
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-            558,
-            1503,
-            1958,
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-            601,
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-            984,
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-            1420,
-            2436,
-            2322,
-            766
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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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
+                        558,
+                        1503,
+                        1958,
+                        2918,
+                        601,
+                        1560,
+                        984,
+                        2388,
+                        995,
+                        2233,
+                        1982,
+                        165,
+                        2788,
+                        1312,
+                        2285,
+                        522,
+                        1113,
+                        1670,
+                        323,
+                        236,
+                        1263,
+                        1562,
+                        2519,
+                        1049,
+                        432,
+                        1167,
+                        1394,
+                        2022,
+                        2551,
+                        2194,
+                        2187,
+                        2282,
+                        2816,
+                        108,
+                        301,
+                        1185,
+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
-            48,
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-            3575,
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-            3591,
-            24,
-            96,
-            92,
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-            52,
-            72,
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-            3519,
-            3531,
-            28,
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-            0,
-            12,
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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": {
-        "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"
-              ]
+        "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",
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+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        "2010-01_1",
+                        "2010-01_11",
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             },
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-              "function": "find_choices",
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-                "\\b([ABCD]) ?[.):-]",
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+                            "function": "find_choices",
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+        "portuguese_hate_speech": {
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+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
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+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
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-                "Negativo"
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+        "tweetsentbr": {
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+            "doc_to_target": "{{'Positivo' if label == 'Positive' else ('Negativo' if label == 'Negative' else 'Neutro')}}",
+            "description": "Abaixo contém o texto de tweets de usuários 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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 }

GritLM/GritLM-7B/results_2024-06-12T20-31-09.833902.json

@@ -34,8 +34,8 @@
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HuggingFaceH4/zephyr-7b-beta/raw_2024-02-21T23-57-52.146406/results.json

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+            "acc,exam_id__2010": 0.5555555555555556,
+            "acc,exam_id__2014": 0.5963302752293578,
+            "acc,exam_id__2015": 0.6218487394957983,
+            "acc,exam_id__2017": 0.5517241379310345
+        },
+        "faquad_nli": {
+            "f1_macro,all": 0.7017672651113582,
+            "acc,all": 0.7384615384615385,
+            "alias": "faquad_nli"
+        },
+        "hatebr_offensive": {
+            "alias": "hatebr_offensive_binary",
+            "f1_macro,all": 0.8176778106453834,
+            "acc,all": 0.82
+        },
+        "oab_exams": {
+            "acc,all": 0.3931662870159453,
+            "acc,exam_id__2010-02": 0.46,
+            "acc,exam_id__2016-19": 0.5,
+            "acc,exam_id__2015-17": 0.4358974358974359,
+            "acc,exam_id__2016-21": 0.4,
+            "acc,exam_id__2017-24": 0.325,
+            "acc,exam_id__2012-09": 0.37662337662337664,
+            "acc,exam_id__2011-04": 0.3125,
+            "acc,exam_id__2017-23": 0.4375,
+            "acc,exam_id__2011-03": 0.41414141414141414,
+            "acc,exam_id__2012-07": 0.3375,
+            "acc,exam_id__2012-06": 0.375,
+            "acc,exam_id__2014-13": 0.35,
+            "acc,exam_id__2016-20a": 0.225,
+            "acc,exam_id__2011-05": 0.3875,
+            "acc,exam_id__2015-18": 0.425,
+            "acc,exam_id__2014-15": 0.5384615384615384,
+            "acc,exam_id__2018-25": 0.4125,
+            "acc,exam_id__2017-22": 0.425,
+            "acc,exam_id__2013-11": 0.425,
+            "acc,exam_id__2014-14": 0.3625,
+            "acc,exam_id__2013-10": 0.3375,
+            "acc,exam_id__2010-01": 0.32941176470588235,
+            "acc,exam_id__2013-12": 0.475,
+            "acc,exam_id__2015-16": 0.3875,
+            "acc,exam_id__2012-06a": 0.3875,
+            "acc,exam_id__2016-20": 0.3875,
+            "acc,exam_id__2012-08": 0.375,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.6658626171810755,
+            "acc,all": 0.6886016451233843
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.614191091794639,
+            "acc,all": 0.6681592039800995,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7fd79f4a5120>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7fd79f4a5120>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fd79f4a4ae0>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7fd79f4a4ae0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fd79f4a4d60>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fd79f4a4d60>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fd79f4a5300>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7fd79f4a5300>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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+                        {
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+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
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+                        {
+                            "function": "take_first"
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+                        "column": "exam_id"
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+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fd79f4a5580>",
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-          ],
-          "group_by": {
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-      "target_delimiter": " ",
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-              ]
+        "faquad_nli": {
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+            ],
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+            "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": " ",
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             },
-            {
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+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
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+                }
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-      ],
-      "should_decontaminate": false,
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-                "Não"
-              ]
+        "hatebr_offensive": {
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+            "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",
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-              "function": "take_first"
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-          ]
-        }
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+            "doc_to_text": "<function doc_to_text at 0x7fd79f4a44a0>",
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+                                "\\b([ABCD]) ?[.):-]",
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-          ],
-          "group_by": {
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-      ],
-      "should_decontaminate": true,
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-        "version": 1.5
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-    "portuguese_hate_speech": {
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-        {
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-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
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+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
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+            "doc_to_target": "{{'Positivo' if label == 'Positive' else ('Negativo' if label == 'Negative' else 'Neutro')}}",
+            "description": "Abaixo contém o texto de tweets de usuários 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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HuggingFaceH4/zephyr-7b-beta/results_2024-02-21T23-57-52.146406.json

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HuggingFaceTB/SmolLM-1.7B-Instruct/raw_2024-07-29T01-29-23.830440/results.json

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+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
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+                "do_sample": false,
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+                "until": [
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
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+                }
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-      ],
-      "should_decontaminate": false,
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-      "test_split": "test",
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-      "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 0x7f0d5c0de8e0>",
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+            "doc_to_target": "<function assin2_float_to_pt_str at 0x7f0d5c0de8e0>",
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+                }
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+                "pt_benchmark",
+                "vestibular"
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+            "doc_to_text": "<function enem_doc_to_text at 0x7f0d5c0de2a0>",
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+            "fewshot_config": {
+                "sampler": "id_sampler",
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+                    "id_list": [
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+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
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+                            "function": "find_choices",
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+                                "B",
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+                                "D",
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+                            "regex_patterns": [
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+            "task": "enem_challenge",
+            "task_alias": "enem",
+            "group": [
+                "pt_benchmark",
+                "vestibular"
+            ],
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+            "test_split": "train",
+            "fewshot_split": "train",
+            "doc_to_text": "<function enem_doc_to_text at 0x7f0d5c0deac0>",
+            "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
+                }
             },
-            {
-              "function": "find_choices",
-              "choices": [
-                "A",
-                "B",
-                "C",
-                "D",
-                "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
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+                    "aggregation": "acc",
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+            "output_type": "generate_until",
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+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f0d5c0ded40>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
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-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f0d5c0ded40>",
-      "metadata": {
-        "version": 1.1
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-      "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",
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-      "fewshot_delimiter": "\n\n",
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-        "sampler": "first_n",
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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",
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-          "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": [
-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
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 }

HuggingFaceTB/SmolLM-1.7B-Instruct/results_2024-07-29T01-29-23.830440.json

@@ -34,29 +34,29 @@
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@@ -135,24 +135,24 @@
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HuggingFaceTB/SmolLM-135M-Instruct/raw_2024-07-24T14-22-33.098781/results.json

@@ -1,1244 +1,1244 @@
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-      "acc,exam_id__2014": 0.1651376146788991,
-      "acc,exam_id__2015": 0.13445378151260504,
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-      "acc,exam_id__2009": 0.1565217391304348,
-      "acc,exam_id__2022": 0.17293233082706766,
-      "acc,exam_id__2017": 0.15517241379310345,
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-        "assin2"
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-      "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",
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-          "aggregation": "f1_macro",
-          "higher_is_better": true
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         },
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-          "higher_is_better": true
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+            "acc,exam_id__2013": 0.1574074074074074,
+            "acc,exam_id__2009": 0.1565217391304348,
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+            "acc,exam_id__2011": 0.18803418803418803,
+            "acc,exam_id__2016_2": 0.17073170731707318,
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+            "acc,exam_id__2012-09": 0.22077922077922077,
+            "acc,exam_id__2015-16": 0.2375,
+            "acc,exam_id__2011-03": 0.24242424242424243,
+            "acc,exam_id__2013-11": 0.15,
+            "acc,exam_id__2016-19": 0.1794871794871795,
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+            "acc,exam_id__2010-02": 0.23,
+            "acc,exam_id__2015-17": 0.24358974358974358,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
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         }
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-      "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": [
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
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+                        3,
+                        4,
+                        5,
+                        6,
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+                        8,
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+                        11,
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+                        12,
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+                        3275
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+                    "id_column": "sentence_pair_id"
+                }
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+                    "aggregation": "f1_macro",
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+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            "output_type": "generate_until",
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
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+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
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-      ],
-      "should_decontaminate": false,
-      "metadata": {
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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 0x7f52406fd4e0>",
-      "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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-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
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-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
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-      "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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-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
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-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "assin2_sts": {
+            "task": "assin2_sts",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: 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 0x7f52406fd4e0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
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+                        3254,
+                        3255,
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+                        8,
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+                        3263,
+                        16,
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+                        18,
+                        3265,
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+                        19,
+                        20,
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+                        21,
+                        3270,
+                        3271,
+                        22,
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+                        3273,
+                        23,
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+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
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-      "should_decontaminate": false,
-      "metadata": {
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-        "vestibular"
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-      "dataset_path": "eduagarcia-temp/BLUEX_without_images",
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-      "doc_to_text": "<function enem_doc_to_text at 0x7f52406fcea0>",
-      "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": {
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-            "USP_2018_35",
-            "UNICAMP_2018_16",
-            "USP_2018_89"
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-              "function": "normalize_spaces"
+            "num_fewshot": 15,
+            "metric_list": [
+                {
+                    "metric": "pearson",
+                    "aggregation": "pearsonr",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "mse",
+                    "aggregation": "mean_squared_error",
+                    "higher_is_better": false
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+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "remove_accents"
+            "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": {
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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 0x7f52406fcea0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "function": "find_choices",
-              "choices": [
-                "A",
-                "B",
-                "C",
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-                "\\b([ABCDE])\\.",
-                "\\b([ABCDE]) ?[.):-]",
-                "\\b([ABCDE])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
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+                    "metric": "acc",
+                    "aggregation": "acc",
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+            "output_type": "generate_until",
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+                "do_sample": false,
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+                {
+                    "name": "all",
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+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
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+                            "function": "take_first"
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+                        "column": "exam_id"
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+            "should_decontaminate": true,
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-      "metadata": {
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-      "task": "enem_challenge",
-      "task_alias": "enem",
-      "group": [
-        "pt_benchmark",
-        "vestibular"
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-      "dataset_path": "eduagarcia/enem_challenge",
-      "test_split": "train",
-      "fewshot_split": "train",
-      "doc_to_text": "<function enem_doc_to_text at 0x7f52406fd6c0>",
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-              "function": "normalize_spaces"
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-            {
-              "function": "remove_accents"
+        },
+        "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 0x7f52406fd6c0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
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-            {
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+                            "function": "normalize_spaces"
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+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "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 0x7f52406fd940>",
+            "metadata": {
+                "version": 1.1
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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 0x7f52406fd940>",
-      "metadata": {
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-    "faquad_nli": {
-      "task": "faquad_nli",
-      "group": [
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-      ],
-      "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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-            1420,
-            2436,
-            2322,
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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"
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-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
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+                        949,
+                        663,
+                        105,
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+                        2227,
+                        2813,
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             },
-            {
-              "function": "take_first"
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+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
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+                }
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+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
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-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
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-    },
-    "hatebr_offensive": {
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-      "group": [
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-      "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": {
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-        "sampler_config": {
-          "id_list": [
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-          "id_column": "idx"
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-      },
-      "num_fewshot": 25,
-      "metric_list": [
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-          "aggregation": "f1_macro",
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-        "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": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
+                        48,
+                        44,
+                        36,
+                        20,
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+                        52,
+                        72,
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+                        3571,
+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7f52406fc860>",
-      "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",
-            "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": [
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-          "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"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7f52406fc860>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7f52406fcae0>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7f52406fcae0>",
-      "metadata": {
-        "version": 1.5
-      }
-    },
-    "portuguese_hate_speech": {
-      "task": "portuguese_hate_speech",
-      "task_alias": "portuguese_hate_speech_binary",
-      "group": [
-        "pt_benchmark"
-      ],
-      "dataset_path": "eduagarcia/portuguese_benchmark",
-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
-      "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. 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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+                        50,
+                        39,
+                        28,
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+                        67,
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+                        27,
+                        24,
+                        14,
+                        16,
+                        48,
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+                        40,
+                        34,
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+                        32,
+                        119,
+                        114,
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+                        58,
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+                        18,
+                        36,
+                        5,
+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
+                    ],
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+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
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+                    "aggregation": "acc",
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+            ],
+            "output_type": "generate_until",
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+                "temperature": 0.0,
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
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-      ],
-      "should_decontaminate": false,
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-      ],
-      "dataset_path": "eduagarcia/tweetsentbr_fewshot",
-      "test_split": "test",
-      "fewshot_split": "train",
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-      "doc_to_target": "{{'Positivo' if label == 'Positive' else ('Negativo' if label == 'Negative' else 'Neutro')}}",
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-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Positivo",
-                "Neutro",
-                "Negativo"
-              ]
+        "tweetsentbr": {
+            "task": "tweetsentbr",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/tweetsentbr_fewshot",
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+            "doc_to_text": "Texto: {{sentence}}\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 texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o sentimento do texto é Positivo, Neutro ou Negativo. Responda apenas com uma das opções.\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
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             },
-            {
-              "function": "take_first"
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+                            "function": "find_similar_label",
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+                                "Positivo",
+                                "Neutro",
+                                "Negativo"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
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HuggingFaceTB/SmolLM-135M-Instruct/results_2024-07-24T14-22-33.098781.json

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HuggingFaceTB/SmolLM-360M-Instruct/raw_2024-07-24T17-08-31.061263/results.json

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+            "acc,exam_id__2014": 0.1926605504587156,
+            "acc,exam_id__2015": 0.13445378151260504,
+            "acc,exam_id__2013": 0.1574074074074074,
+            "acc,exam_id__2009": 0.14782608695652175,
+            "acc,exam_id__2022": 0.18796992481203006,
+            "acc,exam_id__2017": 0.19827586206896552,
+            "acc,exam_id__2010": 0.13675213675213677,
+            "acc,exam_id__2012": 0.1810344827586207,
+            "acc,exam_id__2016": 0.19834710743801653,
+            "acc,exam_id__2011": 0.1794871794871795,
+            "acc,exam_id__2016_2": 0.17886178861788618,
+            "acc,exam_id__2023": 0.2518518518518518
+        },
+        "faquad_nli": {
+            "f1_macro,all": 0.13893376413570277,
+            "acc,all": 0.13230769230769232,
+            "alias": "faquad_nli"
+        },
+        "hatebr_offensive": {
+            "alias": "hatebr_offensive_binary",
+            "f1_macro,all": 0.3523595573670525,
+            "acc,all": 0.3407142857142857
+        },
+        "oab_exams": {
+            "acc,all": 0.23006833712984054,
+            "acc,exam_id__2016-21": 0.2125,
+            "acc,exam_id__2018-25": 0.2875,
+            "acc,exam_id__2017-22": 0.25,
+            "acc,exam_id__2012-08": 0.225,
+            "acc,exam_id__2017-23": 0.2125,
+            "acc,exam_id__2013-12": 0.175,
+            "acc,exam_id__2011-05": 0.2375,
+            "acc,exam_id__2016-20": 0.225,
+            "acc,exam_id__2014-15": 0.21794871794871795,
+            "acc,exam_id__2012-06a": 0.2375,
+            "acc,exam_id__2016-20a": 0.3,
+            "acc,exam_id__2014-13": 0.2375,
+            "acc,exam_id__2013-10": 0.2125,
+            "acc,exam_id__2012-09": 0.23376623376623376,
+            "acc,exam_id__2015-16": 0.2375,
+            "acc,exam_id__2011-03": 0.24242424242424243,
+            "acc,exam_id__2013-11": 0.1625,
+            "acc,exam_id__2016-19": 0.19230769230769232,
+            "acc,exam_id__2014-14": 0.2625,
+            "acc,exam_id__2010-01": 0.25882352941176473,
+            "acc,exam_id__2012-07": 0.1375,
+            "acc,exam_id__2017-24": 0.225,
+            "acc,exam_id__2015-18": 0.25,
+            "acc,exam_id__2011-04": 0.25,
+            "acc,exam_id__2012-06": 0.2375,
+            "acc,exam_id__2010-02": 0.24,
+            "acc,exam_id__2015-17": 0.24358974358974358,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.2918717406329194,
+            "acc,all": 0.20681551116333724
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.16534445394684297,
+            "acc,all": 0.2975124378109453,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7f52406fd4e0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7f52406fd4e0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f52406fcea0>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f52406fcea0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f52406fd120>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f52406fd120>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7f52406fd6c0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7f52406fd6c0>",
+            "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
+                }
             },
-            {
-              "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])$",
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+            "num_fewshot": 3,
+            "metric_list": [
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+                    "aggregation": "acc",
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+            "output_type": "generate_until",
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+                                "\\b([ABCDE])$",
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+                        {
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+                        "column": "exam_id"
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+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f52406fd940>",
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-          "group_by": {
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-      "doc_to_text": "Pergunta: {{question}}\nResposta: {{answer}}\nA resposta dada satisfaz à pergunta? Sim ou Não?",
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-      "target_delimiter": " ",
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+        "faquad_nli": {
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+            "group": [
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+            ],
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+            "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": " ",
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-            {
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+                            "labels": [
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+                                "Não"
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+                        {
+                            "function": "take_first"
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-                "Não"
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+            "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",
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-              "function": "take_first"
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-          "group_by": {
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-      "should_decontaminate": true,
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-      "target_delimiter": " ",
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-      "metric_list": [
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-          "metric": "f1_macro",
-          "aggregation": "f1_macro",
-          "higher_is_better": true
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 }

HuggingFaceTB/SmolLM-360M-Instruct/results_2024-07-24T17-08-31.061263.json

@@ -34,18 +34,18 @@
         "eval_version": "1.1.0"
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@@ -53,10 +53,10 @@
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Intel/neural-chat-7b-v3-1/raw_2024-02-25T06-21-33.008420/results.json

@@ -1,1324 +1,1324 @@
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-                "Não"
-              ]
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+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "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": " ",
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-            {
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+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
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-      "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:",
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-      "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": " ",
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         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
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-      "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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-      "filter_list": [
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-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "assin2_sts": {
+            "task": "assin2_sts",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: 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 0x7fb393d55120>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
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+                        3271,
+                        22,
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+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
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+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fb393d54ae0>",
-      "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": [
-            "USP_2018_3",
-            "UNICAMP_2018_2",
-            "USP_2018_35",
-            "UNICAMP_2018_16",
-            "USP_2018_89"
-          ],
-          "id_column": "id",
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-        }
-      },
-      "num_fewshot": 3,
-      "metric_list": [
-        {
-          "metric": "acc",
-          "aggregation": "acc",
-          "higher_is_better": true
-        }
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-      "output_type": "generate_until",
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-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
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-        "until": [
-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "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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             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7fb393d54ae0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fb393d54d60>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fb393d54d60>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fb393d55300>",
-      "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": [
-        {
-          "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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-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7fb393d55300>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fb393d55580>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fb393d55580>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
-            2910,
-            2227,
-            2813,
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-            558,
-            1503,
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-            601,
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-            984,
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-            2187,
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-            301,
-            1185,
-            1315,
-            1420,
-            2436,
-            2322,
-            766
-          ]
-        }
-      },
-      "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
+                        558,
+                        1503,
+                        1958,
+                        2918,
+                        601,
+                        1560,
+                        984,
+                        2388,
+                        995,
+                        2233,
+                        1982,
+                        165,
+                        2788,
+                        1312,
+                        2285,
+                        522,
+                        1113,
+                        1670,
+                        323,
+                        236,
+                        1263,
+                        1562,
+                        2519,
+                        1049,
+                        432,
+                        1167,
+                        1394,
+                        2022,
+                        2551,
+                        2194,
+                        2187,
+                        2282,
+                        2816,
+                        108,
+                        301,
+                        1185,
+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
-            48,
-            44,
-            36,
-            20,
-            3511,
-            88,
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-            3523,
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-                "Não"
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+            "task_alias": "hatebr_offensive_binary",
+            "group": [
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+            "dataset_name": "HateBR_offensive_binary",
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+            "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",
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             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
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+                "sampler_config": {
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             },
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-              "function": "find_choices",
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-                "\\b([ABCD]) ?[.):-]",
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+            "num_fewshot": 3,
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             },
-            {
-              "function": "take_first"
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+                    "name": "all",
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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"
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+                        {
+                            "function": "take_first"
+                        }
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+                    "group_by": {
+                        "column": "exam_id"
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+            "doc_to_decontamination_query": "<function doc_to_text at 0x7fb393d54720>",
+            "metadata": {
+                "version": 1.5
             }
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-          "group_by": {
-            "column": "exam_id"
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-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7fb393d54720>",
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-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
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-                "Não"
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+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. 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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+            "metric_list": [
+                {
+                    "metric": "f1_macro",
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
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+                        {
+                            "function": "take_first"
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+            ],
+            "should_decontaminate": false,
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-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O sentimento do texto é Positivo, Neutro ou Negativo?\nResposta:",
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-              "labels": [
-                "Positivo",
-                "Neutro",
-                "Negativo"
-              ]
+        "tweetsentbr": {
+            "task": "tweetsentbr",
+            "group": [
+                "pt_benchmark"
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+            "dataset_path": "eduagarcia-temp/tweetsentbr",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\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 texto de tweets de usuários 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": {
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 }

Intel/neural-chat-7b-v3-1/results_2024-02-25T06-21-33.008420.json

@@ -34,8 +34,8 @@
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@@ -150,9 +150,9 @@
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Intel/neural-chat-7b-v3-3/raw_2024-02-21T22-54-50.520595/results.json

@@ -1,1324 +1,1324 @@
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-      "acc,all": 0.6263121063680895,
-      "acc,exam_id__2016_2": 0.6504065040650406,
-      "acc,exam_id__2009": 0.6173913043478261,
-      "acc,exam_id__2011": 0.7008547008547008,
-      "acc,exam_id__2012": 0.6120689655172413,
-      "acc,exam_id__2013": 0.6111111111111112,
-      "acc,exam_id__2016": 0.5867768595041323,
-      "acc,exam_id__2022": 0.6390977443609023,
-      "acc,exam_id__2023": 0.6592592592592592,
-      "acc,exam_id__2010": 0.5982905982905983,
-      "acc,exam_id__2014": 0.6330275229357798,
-      "acc,exam_id__2015": 0.6050420168067226,
-      "acc,exam_id__2017": 0.5948275862068966
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-      "acc,exam_id__2016-19": 0.46153846153846156,
-      "acc,exam_id__2015-17": 0.47435897435897434,
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-      "acc,exam_id__2017-24": 0.3625,
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-      "acc,exam_id__2014-13": 0.3,
-      "acc,exam_id__2016-20a": 0.4375,
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-      "acc,exam_id__2013-10": 0.425,
-      "acc,exam_id__2010-01": 0.3176470588235294,
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-      "acc,exam_id__2015-16": 0.2875,
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-      "acc,exam_id__2016-20": 0.4125,
-      "acc,exam_id__2012-08": 0.325,
-      "alias": "oab_exams"
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-      "alias": "portuguese_hate_speech_binary",
-      "f1_macro,all": 0.6322323153577603,
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-      "acc,all": 0.6925373134328359,
-      "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",
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-      "metric_list": [
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-          "aggregation": "f1_macro",
-          "higher_is_better": true
+    "results": {
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         },
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-          "higher_is_better": true
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+            "acc,exam_id__2009": 0.6173913043478261,
+            "acc,exam_id__2011": 0.7008547008547008,
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+            "acc,exam_id__2023": 0.6592592592592592,
+            "acc,exam_id__2010": 0.5982905982905983,
+            "acc,exam_id__2014": 0.6330275229357798,
+            "acc,exam_id__2015": 0.6050420168067226,
+            "acc,exam_id__2017": 0.5948275862068966
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+            "f1_macro,all": 0.7147222222222223,
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+            "acc,exam_id__2012-09": 0.3116883116883117,
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+            "acc,exam_id__2012-07": 0.35,
+            "acc,exam_id__2012-06": 0.4625,
+            "acc,exam_id__2014-13": 0.3,
+            "acc,exam_id__2016-20a": 0.4375,
+            "acc,exam_id__2011-05": 0.425,
+            "acc,exam_id__2015-18": 0.3875,
+            "acc,exam_id__2014-15": 0.41025641025641024,
+            "acc,exam_id__2018-25": 0.4625,
+            "acc,exam_id__2017-22": 0.475,
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+            "acc,exam_id__2016-20": 0.4125,
+            "acc,exam_id__2012-08": 0.325,
+            "alias": "oab_exams"
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+        "portuguese_hate_speech": {
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+            "alias": "tweetsentbr"
         }
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-      "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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-      "filter_list": [
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
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+                        8,
+                        9,
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+                        11,
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+                        12,
+                        13,
+                        14,
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+                        22,
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+                        3274,
+                        24,
+                        25,
+                        3275
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+                    "id_column": "sentence_pair_id"
+                }
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+            "metric_list": [
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+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
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+                {
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+                    "aggregation": "acc",
+                    "higher_is_better": true
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+            "output_type": "generate_until",
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
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+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
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-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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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 0x7fd79f4a5120>",
-      "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",
-      "fewshot_config": {
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-        "sampler_config": {
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-      "metric_list": [
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-          "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": [
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-          "filter": [
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-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "assin2_sts": {
+            "task": "assin2_sts",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: 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 0x7fd79f4a5120>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
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+                        12,
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+                        3261,
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+                        3263,
+                        16,
+                        17,
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+                        18,
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+                        3266,
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+                        19,
+                        20,
+                        3268,
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+                        21,
+                        3270,
+                        3271,
+                        22,
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+                        3273,
+                        23,
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+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-        "vestibular"
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-      "dataset_path": "eduagarcia-temp/BLUEX_without_images",
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-      "fewshot_split": "train",
-      "doc_to_text": "<function enem_doc_to_text at 0x7fd79f4a4ae0>",
-      "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": {
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-        "sampler_config": {
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-            "USP_2018_35",
-            "UNICAMP_2018_16",
-            "USP_2018_89"
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-          "id_column": "id",
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-      "output_type": "generate_until",
-      "generation_kwargs": {
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-              "function": "normalize_spaces"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7fd79f4a4ae0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
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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 0x7fd79f4a4d60>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
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-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fd79f4a4d60>",
-      "metadata": {
-        "version": 1.1
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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 0x7fd79f4a5300>",
-      "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": {
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-        "sampler_config": {
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-      "num_fewshot": 3,
-      "metric_list": [
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-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7fd79f4a5300>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fd79f4a5580>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fd79f4a5580>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
-            2910,
-            2227,
-            2813,
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-            558,
-            1503,
-            1958,
-            2918,
-            601,
-            1560,
-            984,
-            2388,
-            995,
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-            1982,
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-            301,
-            1185,
-            1315,
-            1420,
-            2436,
-            2322,
-            766
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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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
+                        974,
+                        558,
+                        1503,
+                        1958,
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+                        601,
+                        1560,
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+                        995,
+                        2233,
+                        1982,
+                        165,
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+                        1312,
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+                        522,
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+                        323,
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+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
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-            12,
-            3583
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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": {
-        "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": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
+                        48,
+                        44,
+                        36,
+                        20,
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+                        88,
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+                        24,
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+                        92,
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+                        52,
+                        72,
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+                        3571,
+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7fd79f4a44a0>",
-      "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",
-            "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": {
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-        "until": [
-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7fd79f4a44a0>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
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+                        }
+                    ],
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+                        "column": "exam_id"
+                    }
+                }
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+            "doc_to_decontamination_query": "<function doc_to_text at 0x7fd79f4a4720>",
+            "metadata": {
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             }
-          ],
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-      "doc_to_decontamination_query": "<function doc_to_text at 0x7fd79f4a4720>",
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-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
-      "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
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-          "filter": [
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-              "labels": [
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-                "Não"
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+        "portuguese_hate_speech": {
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+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
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+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
+            "fewshot_config": {
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+                        39,
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+                        42,
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+                        20,
+                        76,
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+                        104,
+                        13,
+                        67,
+                        54,
+                        97,
+                        27,
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+                        6,
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+                        46
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+                    "aggregation": "f1_macro",
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+                    "filter": [
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+                            "labels": [
+                                "Sim",
+                                "Não"
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+            "doc_to_target": "{{'Positivo' if label == 'Positive' else ('Negativo' if label == 'Negative' else 'Neutro')}}",
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Intel/neural-chat-7b-v3-3/results_2024-02-21T22-54-50.520595.json

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JJhooww/Mistral_Relora_Step2k/raw_2024-03-09T08-42-21.029909/results.json

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-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
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-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "f1_macro",
-          "aggregation": "f1_macro",
-          "higher_is_better": true
+    "results": {
+        "assin2_rte": {
+            "f1_macro,all": 0.9113496854193482,
+            "acc,all": 0.9113562091503268,
+            "alias": "assin2_rte"
         },
-        {
-          "metric": "acc",
-          "aggregation": "acc",
-          "higher_is_better": true
+        "assin2_sts": {
+            "pearson,all": 0.7074610038971542,
+            "mse,all": 0.7742524509803921,
+            "alias": "assin2_sts"
+        },
+        "bluex": {
+            "acc,all": 0.5257301808066759,
+            "acc,exam_id__USP_2019": 0.5,
+            "acc,exam_id__UNICAMP_2021_2": 0.5098039215686274,
+            "acc,exam_id__UNICAMP_2020": 0.4909090909090909,
+            "acc,exam_id__UNICAMP_2024": 0.4666666666666667,
+            "acc,exam_id__UNICAMP_2019": 0.58,
+            "acc,exam_id__USP_2020": 0.5714285714285714,
+            "acc,exam_id__UNICAMP_2022": 0.6153846153846154,
+            "acc,exam_id__USP_2024": 0.7073170731707317,
+            "acc,exam_id__UNICAMP_2018": 0.4074074074074074,
+            "acc,exam_id__USP_2022": 0.4489795918367347,
+            "acc,exam_id__UNICAMP_2023": 0.627906976744186,
+            "acc,exam_id__USP_2021": 0.4807692307692308,
+            "acc,exam_id__USP_2023": 0.5909090909090909,
+            "acc,exam_id__USP_2018": 0.4444444444444444,
+            "acc,exam_id__UNICAMP_2021_1": 0.5217391304347826,
+            "alias": "bluex"
+        },
+        "enem_challenge": {
+            "alias": "enem",
+            "acc,all": 0.615815255423373,
+            "acc,exam_id__2011": 0.6837606837606838,
+            "acc,exam_id__2014": 0.6513761467889908,
+            "acc,exam_id__2012": 0.5948275862068966,
+            "acc,exam_id__2016_2": 0.6097560975609756,
+            "acc,exam_id__2013": 0.6296296296296297,
+            "acc,exam_id__2009": 0.6,
+            "acc,exam_id__2022": 0.5939849624060151,
+            "acc,exam_id__2010": 0.5897435897435898,
+            "acc,exam_id__2017": 0.6206896551724138,
+            "acc,exam_id__2023": 0.6592592592592592,
+            "acc,exam_id__2015": 0.5630252100840336,
+            "acc,exam_id__2016": 0.5950413223140496
+        },
+        "faquad_nli": {
+            "f1_macro,all": 0.6526577185427341,
+            "acc,all": 0.816923076923077,
+            "alias": "faquad_nli"
+        },
+        "hatebr_offensive": {
+            "alias": "hatebr_offensive_binary",
+            "f1_macro,all": 0.8133973664850924,
+            "acc,all": 0.8157142857142857
+        },
+        "oab_exams": {
+            "acc,all": 0.3981776765375854,
+            "acc,exam_id__2016-20a": 0.325,
+            "acc,exam_id__2012-07": 0.4125,
+            "acc,exam_id__2015-16": 0.3375,
+            "acc,exam_id__2010-01": 0.3176470588235294,
+            "acc,exam_id__2016-21": 0.3625,
+            "acc,exam_id__2017-23": 0.3625,
+            "acc,exam_id__2012-08": 0.3875,
+            "acc,exam_id__2012-06": 0.5125,
+            "acc,exam_id__2014-15": 0.46153846153846156,
+            "acc,exam_id__2011-04": 0.3125,
+            "acc,exam_id__2014-13": 0.3375,
+            "acc,exam_id__2013-12": 0.425,
+            "acc,exam_id__2014-14": 0.5125,
+            "acc,exam_id__2017-22": 0.5375,
+            "acc,exam_id__2013-10": 0.35,
+            "acc,exam_id__2018-25": 0.3875,
+            "acc,exam_id__2012-06a": 0.425,
+            "acc,exam_id__2016-19": 0.47435897435897434,
+            "acc,exam_id__2017-24": 0.3875,
+            "acc,exam_id__2011-05": 0.35,
+            "acc,exam_id__2015-17": 0.44871794871794873,
+            "acc,exam_id__2011-03": 0.35353535353535354,
+            "acc,exam_id__2010-02": 0.42,
+            "acc,exam_id__2013-11": 0.45,
+            "acc,exam_id__2012-09": 0.35064935064935066,
+            "acc,exam_id__2016-20": 0.4,
+            "acc,exam_id__2015-18": 0.3625,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
+            "alias": "portuguese_hate_speech_binary",
+            "f1_macro,all": 0.6536416538696902,
+            "acc,all": 0.6686251468860165
+        },
+        "tweetsentbr": {
+            "f1_macro,all": 0.6924780806431777,
+            "acc,all": 0.7074626865671642,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
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+                        11,
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+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7ff1779f53a0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
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-            3269,
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-            22,
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-            3273,
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-            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"
-        ]
-      },
-      "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
+        "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: 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 0x7ff1779f53a0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7ff1779f4d60>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7ff1779f4d60>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff1779f4fe0>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff1779f4fe0>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7ff1779f5580>",
-      "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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-        "top_k": null,
-        "top_p": null,
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-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
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-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7ff1779f5580>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff1779f5800>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff1779f5800>",
-      "metadata": {
-        "version": 1.1
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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 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": {
-          "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
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+                        949,
+                        663,
+                        105,
+                        1169,
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+                        2227,
+                        2813,
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+                        995,
+                        2233,
+                        1982,
+                        165,
+                        2788,
+                        1312,
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+                        522,
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+                        323,
+                        236,
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+                        108,
+                        301,
+                        1185,
+                        1315,
+                        1420,
+                        2436,
+                        2322,
+                        766
+                    ]
+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
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-            12,
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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": {
-        "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"
-              ]
+        "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": {
+                    "id_list": [
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+                        44,
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+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7ff1779f4720>",
-      "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": [
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-            "2010-01_11",
-            "2010-01_13",
-            "2010-01_23",
-            "2010-01_26",
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-            "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
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-      },
-      "num_fewshot": 3,
-      "metric_list": [
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-        "temperature": 0.0,
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-        "until": [
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-      "repeats": 1,
-      "filter_list": [
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-          "name": "all",
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-              "function": "normalize_spaces"
+            "num_fewshot": 25,
+            "metric_list": [
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+                    "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7ff1779f4720>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
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-              ]
+            "num_fewshot": 3,
+            "metric_list": [
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+            ],
+            "output_type": "generate_until",
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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+                "until": [
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+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7ff1779f49a0>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
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+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
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+                        9,
+                        10,
+                        3257,
+                        11,
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+                        12,
+                        13,
+                        14,
+                        15,
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+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
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+                        3266,
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+                        19,
+                        20,
+                        3268,
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+                        21,
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+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7ff44266dee0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
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-            6,
-            3253,
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-            3255,
-            3256,
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-            13,
-            14,
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-            17,
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-            3271,
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-            3272,
-            3273,
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-            3274,
-            24,
-            25,
-            3275
-          ],
-          "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
+        "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: 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 0x7ff44266dee0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
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+                        3254,
+                        3255,
+                        3256,
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+                        9,
+                        10,
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+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7ff44266d8a0>",
-      "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": [
-            "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"
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-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "normalize_spaces"
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+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7ff44266d8a0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "function": "find_choices",
-              "choices": [
-                "A",
-                "B",
-                "C",
-                "D",
-                "E"
-              ],
-              "regex_patterns": [
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-                "\\b([ABCDE])\\.",
-                "\\b([ABCDE]) ?[.):-]",
-                "\\b([ABCDE])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff44266db20>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff44266db20>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7ff44266e0c0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7ff44266e0c0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff44266e340>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7ff44266e340>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
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-            2227,
-            2813,
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-            558,
-            1503,
-            1958,
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-            601,
-            1560,
-            984,
-            2388,
-            995,
-            2233,
-            1982,
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-            108,
-            301,
-            1185,
-            1315,
-            1420,
-            2436,
-            2322,
-            766
-          ]
-        }
-      },
-      "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
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+                        2227,
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+                        974,
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+                        995,
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+                }
             },
-            {
-              "function": "take_first"
+            "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": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
-            48,
-            44,
-            36,
-            20,
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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": {
-        "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"
-              ]
+        "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": {
+                    "id_list": [
+                        48,
+                        44,
+                        36,
+                        20,
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+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7ff44266d260>",
-      "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",
-            "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"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7ff44266d260>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7ff44266d4e0>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7ff44266d4e0>",
-      "metadata": {
-        "version": 1.5
-      }
-    },
-    "portuguese_hate_speech": {
-      "task": "portuguese_hate_speech",
-      "task_alias": "portuguese_hate_speech_binary",
-      "group": [
-        "pt_benchmark"
-      ],
-      "dataset_path": "eduagarcia/portuguese_benchmark",
-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
-      "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            52,
-            50,
-            39,
-            28,
-            3,
-            105,
-            22,
-            25,
-            60,
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-            13,
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-            114,
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-            36,
-            5,
-            6,
-            10,
-            35,
-            38,
-            0,
-            21,
-            46
-          ],
-          "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": {
-        "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"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        52,
+                        50,
+                        39,
+                        28,
+                        3,
+                        105,
+                        22,
+                        25,
+                        60,
+                        11,
+                        66,
+                        41,
+                        9,
+                        4,
+                        91,
+                        42,
+                        7,
+                        20,
+                        76,
+                        1,
+                        104,
+                        13,
+                        67,
+                        54,
+                        97,
+                        27,
+                        24,
+                        14,
+                        16,
+                        48,
+                        53,
+                        40,
+                        34,
+                        49,
+                        32,
+                        119,
+                        114,
+                        2,
+                        58,
+                        83,
+                        18,
+                        36,
+                        5,
+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
+                    ],
+                    "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": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.0
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.0
-      }
-    },
-    "tweetsentbr": {
-      "task": "tweetsentbr",
-      "group": [
-        "pt_benchmark"
-      ],
-      "dataset_path": "eduagarcia/tweetsentbr_fewshot",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\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 texto de tweets de usuários 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,
-      "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,
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 }

JJhooww/Mistral_Relora_Step2k/results_2024-03-09T08-42-21.029909.json

@@ -34,8 +34,8 @@
         "eval_version": "1.1.0"
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@@ -45,7 +45,7 @@
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@@ -56,7 +56,7 @@
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@@ -150,9 +150,9 @@
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JJhooww/Mistral_Relora_Step2k/results_2024-04-20T03-09-26.234801.json

@@ -34,8 +34,8 @@
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@@ -150,9 +150,9 @@
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Kquant03/CognitiveFusion2-4x7B-BF16/raw_2024-05-19T01-32-18.922295/results.json

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-      "acc,exam_id__2016_2": 0.6016260162601627,
-      "acc,exam_id__2013": 0.6944444444444444,
-      "acc,exam_id__2016": 0.5867768595041323,
-      "acc,exam_id__2015": 0.6218487394957983,
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-      "acc,exam_id__2014": 0.6146788990825688,
-      "acc,exam_id__2017": 0.6637931034482759,
-      "acc,exam_id__2010": 0.6837606837606838,
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-      "acc,exam_id__2015-18": 0.4125,
-      "acc,exam_id__2013-10": 0.4125,
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-      "acc,exam_id__2015-17": 0.5,
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-      "acc,exam_id__2014-15": 0.44871794871794873,
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-      "acc,exam_id__2015-16": 0.375,
-      "alias": "oab_exams"
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-      "f1_macro,all": 0.7076245180055771,
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-      "group": [
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-      "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",
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-          "aggregation": "f1_macro",
-          "higher_is_better": true
+    "results": {
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         },
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-          "higher_is_better": true
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+            "acc,exam_id__2013": 0.6944444444444444,
+            "acc,exam_id__2016": 0.5867768595041323,
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+            "acc,exam_id__2014": 0.6146788990825688,
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+            "acc,exam_id__2012": 0.6293103448275862
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+            "f1_macro,all": 0.7730900759529709,
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+            "acc,exam_id__2013-11": 0.45,
+            "acc,exam_id__2016-19": 0.5,
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+            "acc,exam_id__2014-14": 0.5125,
+            "acc,exam_id__2017-22": 0.5125,
+            "acc,exam_id__2018-25": 0.45,
+            "acc,exam_id__2014-13": 0.35,
+            "acc,exam_id__2017-23": 0.425,
+            "acc,exam_id__2017-24": 0.3875,
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+            "acc,exam_id__2016-20a": 0.3375,
+            "acc,exam_id__2015-16": 0.375,
+            "alias": "oab_exams"
+        },
+        "portuguese_hate_speech": {
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         }
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-      "output_type": "generate_until",
-      "generation_kwargs": {
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-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
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-      "repeats": 1,
-      "filter_list": [
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-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
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+                        8,
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+                        11,
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+                        12,
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+                        14,
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+                        24,
+                        25,
+                        3275
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+                    "id_column": "sentence_pair_id"
+                }
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+                    "aggregation": "f1_macro",
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+                {
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+                    "higher_is_better": true
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+            "output_type": "generate_until",
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+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
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-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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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 0x7f7d743b82c0>",
-      "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",
-      "fewshot_config": {
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-        "sampler_config": {
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-      "metric_list": [
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-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
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-      "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": [
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-          "filter": [
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-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "assin2_sts": {
+            "task": "assin2_sts",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: 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 0x7f7d743b82c0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
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+                        11,
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+                        12,
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+                        15,
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+                        3262,
+                        3263,
+                        16,
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+                        3264,
+                        18,
+                        3265,
+                        3266,
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+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
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-        "vestibular"
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-      "dataset_path": "eduagarcia-temp/BLUEX_without_images",
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-      "fewshot_split": "train",
-      "doc_to_text": "<function enem_doc_to_text at 0x7f7d74383c40>",
-      "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": {
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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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-      "num_fewshot": 3,
-      "metric_list": [
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-          "aggregation": "acc",
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-        "temperature": 0.0,
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-              "function": "normalize_spaces"
+            "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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             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7f7d74383c40>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "function": "find_choices",
-              "choices": [
-                "A",
-                "B",
-                "C",
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-                "E"
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-                "\\b([ABCDE])\\.",
-                "\\b([ABCDE]) ?[.):-]",
-                "\\b([ABCDE])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
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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 0x7f7d74383ec0>",
+            "metadata": {
+                "version": 1.1
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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 0x7f7d74383ec0>",
-      "metadata": {
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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 0x7f7d743b84a0>",
-      "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",
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-      "metric_list": [
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-          "filter": [
-            {
-              "function": "normalize_spaces"
-            },
-            {
-              "function": "remove_accents"
+        },
+        "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 0x7f7d743b84a0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
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+                "until": [
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-            {
-              "function": "take_first"
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+                    "name": "all",
+                    "filter": [
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+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f7d743b8720>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f7d743b8720>",
-      "metadata": {
-        "version": 1.1
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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 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": {
-          "fewshot_indices": [
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-            949,
-            663,
-            105,
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-            1958,
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-            601,
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-            1420,
-            2436,
-            2322,
-            766
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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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
+                        1169,
+                        2910,
+                        2227,
+                        2813,
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+                        766
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+                }
             },
-            {
-              "function": "take_first"
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+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
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+            },
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
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-    },
-    "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": {
-          "id_list": [
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-          "id_column": "idx"
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-      },
-      "num_fewshot": 25,
-      "metric_list": [
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-          "metric": "f1_macro",
-          "aggregation": "f1_macro",
-          "higher_is_better": true
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-        {
-          "metric": "acc",
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-          "higher_is_better": true
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
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-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
+                        48,
+                        44,
+                        36,
+                        20,
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+                        52,
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+                        3515,
+                        3519,
+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
+                        3583
+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7f7d74383600>",
-      "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",
-            "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": [
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-          "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"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7f7d74383600>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
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             },
-            {
-              "function": "take_first"
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+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7f7d74383880>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
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-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7f7d74383880>",
-      "metadata": {
-        "version": 1.5
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-    },
-    "portuguese_hate_speech": {
-      "task": "portuguese_hate_speech",
-      "task_alias": "portuguese_hate_speech_binary",
-      "group": [
-        "pt_benchmark"
-      ],
-      "dataset_path": "eduagarcia/portuguese_benchmark",
-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
-      "fewshot_split": "train",
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-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
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-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
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-          "filter": [
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-              "labels": [
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-                "Não"
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+        "portuguese_hate_speech": {
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+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
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+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
+            "fewshot_config": {
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+                "sampler_config": {
+                    "id_list": [
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+                        91,
+                        42,
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+                        20,
+                        76,
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+                        13,
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+                        27,
+                        24,
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+                        34,
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+                        32,
+                        119,
+                        114,
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+                        58,
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+                        18,
+                        36,
+                        5,
+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
+                    ],
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+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
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             },
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+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
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+            ],
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-      "dataset_path": "eduagarcia/tweetsentbr_fewshot",
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-                "Positivo",
-                "Neutro",
-                "Negativo"
-              ]
+        "tweetsentbr": {
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+                "pt_benchmark"
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+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O sentimento do texto é Positivo, Neutro ou Negativo?\nResposta:",
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+            "target_delimiter": " ",
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+                            "function": "find_similar_label",
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+                                "Positivo",
+                                "Neutro",
+                                "Negativo"
+                            ]
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Kquant03/CognitiveFusion2-4x7B-BF16/results_2024-05-19T01-32-18.922295.json

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Kukedlc/NeuralExperiment-7b-MagicCoder-v7.5/raw_2024-07-28T01-32-22.165106/results.json

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+            "f1_macro,all": 0.6629793868028777,
+            "acc,all": 0.7059701492537314,
+            "alias": "tweetsentbr"
         }
-      ],
-      "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"
-              ]
+    },
+    "configs": {
+        "assin2_rte": {
+            "task": "assin2_rte",
+            "group": [
+                "pt_benchmark",
+                "assin2"
+            ],
+            "dataset_path": "assin2",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Premissa: {{premise}}\nHipótese: {{hypothesis}}\nPergunta: A hipótese pode ser inferida pela premissa? 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": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "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"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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: 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 0x7fe8c9bd68e0>",
-      "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",
-      "fewshot_config": {
-        "sampler": "id_sampler",
-        "sampler_config": {
-          "id_list": [
-            1,
-            3251,
-            2,
-            3252,
-            3,
-            4,
-            5,
-            6,
-            3253,
-            7,
-            3254,
-            3255,
-            3256,
-            8,
-            9,
-            10,
-            3257,
-            11,
-            3258,
-            12,
-            13,
-            14,
-            15,
-            3259,
-            3260,
-            3261,
-            3262,
-            3263,
-            16,
-            17,
-            3264,
-            18,
-            3265,
-            3266,
-            3267,
-            19,
-            20,
-            3268,
-            3269,
-            21,
-            3270,
-            3271,
-            22,
-            3272,
-            3273,
-            23,
-            3274,
-            24,
-            25,
-            3275
-          ],
-          "id_column": "sentence_pair_id"
-        }
-      },
-      "num_fewshot": 15,
-      "metric_list": [
-        {
-          "metric": "pearson",
-          "aggregation": "pearsonr",
-          "higher_is_better": true
         },
-        {
-          "metric": "mse",
-          "aggregation": "mean_squared_error",
-          "higher_is_better": false
-        }
-      ],
-      "output_type": "generate_until",
-      "generation_kwargs": {
-        "max_gen_toks": 32,
-        "do_sample": false,
-        "temperature": 0.0,
-        "top_k": null,
-        "top_p": null,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "number_filter",
-              "type": "float",
-              "range_min": 1.0,
-              "range_max": 5.0,
-              "on_outside_range": "clip",
-              "fallback": 5.0
+        "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: 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 0x7fe8c9bd68e0>",
+            "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",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        1,
+                        3251,
+                        2,
+                        3252,
+                        3,
+                        4,
+                        5,
+                        6,
+                        3253,
+                        7,
+                        3254,
+                        3255,
+                        3256,
+                        8,
+                        9,
+                        10,
+                        3257,
+                        11,
+                        3258,
+                        12,
+                        13,
+                        14,
+                        15,
+                        3259,
+                        3260,
+                        3261,
+                        3262,
+                        3263,
+                        16,
+                        17,
+                        3264,
+                        18,
+                        3265,
+                        3266,
+                        3267,
+                        19,
+                        20,
+                        3268,
+                        3269,
+                        21,
+                        3270,
+                        3271,
+                        22,
+                        3272,
+                        3273,
+                        23,
+                        3274,
+                        24,
+                        25,
+                        3275
+                    ],
+                    "id_column": "sentence_pair_id"
+                }
             },
-            {
-              "function": "take_first"
-            }
-          ]
-        }
-      ],
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fe8c9bd62a0>",
-      "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": [
-            "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"
+            "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"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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": 1.1
+            }
+        },
+        "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 0x7fe8c9bd62a0>",
+            "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": [
+                        "USP_2018_3",
+                        "UNICAMP_2018_2",
+                        "USP_2018_35",
+                        "UNICAMP_2018_16",
+                        "USP_2018_89"
+                    ],
+                    "id_column": "id",
+                    "exclude_from_task": true
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fe8c9bd6520>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fe8c9bd6520>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 0x7fe8c9bd6ac0>",
-      "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": [
-        {
-          "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"
+        },
+        "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 0x7fe8c9bd6ac0>",
+            "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCDE])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D",
+                                "E"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                                "\\b([ABCDE])\\.",
+                                "\\b([ABCDE]) ?[.):-]",
+                                "\\b([ABCDE])$",
+                                "\\b([ABCDE])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fe8c9bd6d40>",
+            "metadata": {
+                "version": 1.1
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fe8c9bd6d40>",
-      "metadata": {
-        "version": 1.1
-      }
-    },
-    "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 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": {
-          "fewshot_indices": [
-            1893,
-            949,
-            663,
-            105,
-            1169,
-            2910,
-            2227,
-            2813,
-            974,
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-            995,
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-            1982,
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-            1315,
-            1420,
-            2436,
-            2322,
-            766
-          ]
-        }
-      },
-      "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"
-              ]
+        "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 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": {
+                    "fewshot_indices": [
+                        1893,
+                        949,
+                        663,
+                        105,
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             },
-            {
-              "function": "take_first"
+            "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"
+                ]
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+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "find_similar_label",
+                            "labels": [
+                                "Sim",
+                                "Não"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ]
+                }
+            ],
+            "should_decontaminate": false,
+            "metadata": {
+                "version": 1.1
             }
-          ]
-        }
-      ],
-      "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": {
-          "id_list": [
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-          "id_column": "idx"
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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,
-        "until": [
-          "\n\n"
-        ]
-      },
-      "repeats": 1,
-      "filter_list": [
-        {
-          "name": "all",
-          "filter": [
-            {
-              "function": "find_similar_label",
-              "labels": [
-                "Sim",
-                "Não"
-              ]
+        "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": {
+                    "id_list": [
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+                        44,
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+                        20,
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+                        3531,
+                        28,
+                        32,
+                        0,
+                        12,
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+                    ],
+                    "id_column": "idx"
+                }
             },
-            {
-              "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 0x7fe8c9bd5c60>",
-      "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",
-            "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"
+            "num_fewshot": 25,
+            "metric_list": [
+                {
+                    "metric": "f1_macro",
+                    "aggregation": "f1_macro",
+                    "higher_is_better": true
+                },
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "remove_accents"
+            "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 0x7fe8c9bd5c60>",
+            "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",
+                        "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
+                }
             },
-            {
-              "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])$",
-                "\\b([ABCD])\\b"
-              ]
+            "num_fewshot": 3,
+            "metric_list": [
+                {
+                    "metric": "acc",
+                    "aggregation": "acc",
+                    "higher_is_better": true
+                }
+            ],
+            "output_type": "generate_until",
+            "generation_kwargs": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
+                {
+                    "name": "all",
+                    "filter": [
+                        {
+                            "function": "normalize_spaces"
+                        },
+                        {
+                            "function": "remove_accents"
+                        },
+                        {
+                            "function": "find_choices",
+                            "choices": [
+                                "A",
+                                "B",
+                                "C",
+                                "D"
+                            ],
+                            "regex_patterns": [
+                                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                                "\\b([ABCD])\\.",
+                                "\\b([ABCD]) ?[.):-]",
+                                "\\b([ABCD])$",
+                                "\\b([ABCD])\\b"
+                            ]
+                        },
+                        {
+                            "function": "take_first"
+                        }
+                    ],
+                    "group_by": {
+                        "column": "exam_id"
+                    }
+                }
+            ],
+            "should_decontaminate": true,
+            "doc_to_decontamination_query": "<function doc_to_text at 0x7fe8c9bd5ee0>",
+            "metadata": {
+                "version": 1.5
             }
-          ],
-          "group_by": {
-            "column": "exam_id"
-          }
-        }
-      ],
-      "should_decontaminate": true,
-      "doc_to_decontamination_query": "<function doc_to_text at 0x7fe8c9bd5ee0>",
-      "metadata": {
-        "version": 1.5
-      }
-    },
-    "portuguese_hate_speech": {
-      "task": "portuguese_hate_speech",
-      "task_alias": "portuguese_hate_speech_binary",
-      "group": [
-        "pt_benchmark"
-      ],
-      "dataset_path": "eduagarcia/portuguese_benchmark",
-      "dataset_name": "Portuguese_Hate_Speech_binary",
-      "test_split": "test",
-      "fewshot_split": "train",
-      "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
-      "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
-      "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. 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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-            50,
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-            28,
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-            10,
-            35,
-            38,
-            0,
-            21,
-            46
-          ],
-          "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": {
-        "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"
-              ]
+        "portuguese_hate_speech": {
+            "task": "portuguese_hate_speech",
+            "task_alias": "portuguese_hate_speech_binary",
+            "group": [
+                "pt_benchmark"
+            ],
+            "dataset_path": "eduagarcia/portuguese_benchmark",
+            "dataset_name": "Portuguese_Hate_Speech_binary",
+            "test_split": "test",
+            "fewshot_split": "train",
+            "doc_to_text": "Texto: {{sentence}}\nPergunta: O texto contém discurso de ódio?\nResposta:",
+            "doc_to_target": "{{'Sim' if label == 1 else 'Não'}}",
+            "description": "Abaixo contém o texto de tweets de usuários do Twitter em português, sua tarefa é classificar se o texto contém discurso de ódio ou não. Responda apenas com \"Sim\" ou \"Não\".\n\n",
+            "target_delimiter": " ",
+            "fewshot_delimiter": "\n\n",
+            "fewshot_config": {
+                "sampler": "id_sampler",
+                "sampler_config": {
+                    "id_list": [
+                        52,
+                        50,
+                        39,
+                        28,
+                        3,
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+                        22,
+                        25,
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+                        36,
+                        5,
+                        6,
+                        10,
+                        35,
+                        38,
+                        0,
+                        21,
+                        46
+                    ],
+                    "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": {
+                "max_gen_toks": 32,
+                "do_sample": false,
+                "temperature": 0.0,
+                "top_k": null,
+                "top_p": null,
+                "until": [
+                    "\n\n"
+                ]
             },
-            {
-              "function": "take_first"
+            "repeats": 1,
+            "filter_list": [
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 }

Kukedlc/NeuralExperiment-7b-MagicCoder-v7.5/results_2024-07-28T01-32-22.165106.json

@@ -34,8 +34,8 @@
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@@ -56,7 +56,7 @@
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         "harness|enem_challenge|enem_challenge|None|3": {
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@@ -150,9 +150,9 @@
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