Uploading raw results for openlm-research/open_llama_3b

.gitattributes

@@ -814,3 +814,11 @@ Qwen/Qwen-7B/raw_2024-02-17T08-43-57.342331/pretrained__Qwen__Qwen-7B,dtype__bfl
 Qwen/Qwen-7B/raw_2024-02-17T08-43-57.342331/pretrained__Qwen__Qwen-7B,dtype__bfloat16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_oab_exams.jsonl filter=lfs diff=lfs merge=lfs -text
 Qwen/Qwen-7B/raw_2024-02-17T08-43-57.342331/pretrained__Qwen__Qwen-7B,dtype__bfloat16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_portuguese_hate_speech.jsonl filter=lfs diff=lfs merge=lfs -text
 Qwen/Qwen-7B/raw_2024-02-17T08-43-57.342331/pretrained__Qwen__Qwen-7B,dtype__bfloat16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_tweetsentbr.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_assin2_rte.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_assin2_sts.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_bluex.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_enem_challenge.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_hatebr_offensive.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_oab_exams.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_portuguese_hate_speech.jsonl filter=lfs diff=lfs merge=lfs -text
+openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_tweetsentbr.jsonl filter=lfs diff=lfs merge=lfs -text

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_assin2_rte.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fced5bb69a56106c2421d9510e8ee75d6f06759ed1fa98ad9123e528a19d41cd
+size 31811921

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_assin2_sts.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a7ba43642d1ec8047901c2e9224da96466f7902cd71b33024267f7fe9313ebc
+size 33218493

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_bluex.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f8bad0c4dbcebd85dbc36eaef6245e6f790bb2901c48535dc5a72fb434fd5eaa
+size 11481552

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_enem_challenge.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:77920e1e613b3976db59551b8a34379ff8436d28cd207befff9529de44b6419e
+size 23395923

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_hatebr_offensive.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c2d933221ee62f42b0324ef84b45eaee9d5dfb60ce36bfa4830feae0b973c4d
+size 15152733

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_oab_exams.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:532bd6ed4c19b7896c05e020051d1ca74a02ab5bf1673437ccf178846849bb2b
+size 32943652

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_portuguese_hate_speech.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:25c5cf2047d86944850ef4199b40bcecc914470d06c312cf7d8368174d0dd73e
+size 12378587

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/pretrained__openlm-research__open_llama_3b,dtype__float16,device__cuda:0,revision__main,trust_remote_code__True,starting_max_length__4096_tweetsentbr.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a16faf9853cc5ec5ffe2608e1fde1026696d537165fb835624da2fd3e2b35fc
+size 27294104

openlm-research/open_llama_3b/raw_2024-02-17T09-33-21.785739/results.json

@@ -0,0 +1,1324 @@
+{
+  "results": {
+    "assin2_rte": {
+      "f1_macro,all": 0.35297899277093914,
+      "acc,all": 0.5020424836601307,
+      "alias": "assin2_rte"
+    },
+    "assin2_sts": {
+      "pearson,all": 0.05530368768431126,
+      "mse,all": 2.285600490196079,
+      "alias": "assin2_sts"
+    },
+    "bluex": {
+      "acc,all": 0.22253129346314326,
+      "acc,exam_id__UNICAMP_2020": 0.2909090909090909,
+      "acc,exam_id__UNICAMP_2021_2": 0.2549019607843137,
+      "acc,exam_id__USP_2018": 0.1111111111111111,
+      "acc,exam_id__UNICAMP_2023": 0.27906976744186046,
+      "acc,exam_id__USP_2024": 0.04878048780487805,
+      "acc,exam_id__UNICAMP_2021_1": 0.32608695652173914,
+      "acc,exam_id__USP_2020": 0.2857142857142857,
+      "acc,exam_id__USP_2019": 0.15,
+      "acc,exam_id__USP_2023": 0.09090909090909091,
+      "acc,exam_id__UNICAMP_2019": 0.28,
+      "acc,exam_id__USP_2022": 0.22448979591836735,
+      "acc,exam_id__UNICAMP_2024": 0.2222222222222222,
+      "acc,exam_id__USP_2021": 0.19230769230769232,
+      "acc,exam_id__UNICAMP_2022": 0.2564102564102564,
+      "acc,exam_id__UNICAMP_2018": 0.2777777777777778,
+      "alias": "bluex"
+    },
+    "enem_challenge": {
+      "alias": "enem",
+      "acc,all": 0.1966410076976907,
+      "acc,exam_id__2023": 0.2814814814814815,
+      "acc,exam_id__2010": 0.17094017094017094,
+      "acc,exam_id__2016_2": 0.2032520325203252,
+      "acc,exam_id__2011": 0.2222222222222222,
+      "acc,exam_id__2022": 0.21052631578947367,
+      "acc,exam_id__2015": 0.14285714285714285,
+      "acc,exam_id__2013": 0.16666666666666666,
+      "acc,exam_id__2014": 0.1926605504587156,
+      "acc,exam_id__2009": 0.16521739130434782,
+      "acc,exam_id__2016": 0.19008264462809918,
+      "acc,exam_id__2012": 0.1896551724137931,
+      "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": 0.38836470532454603,
+      "acc,all": 0.4471428571428571
+    },
+    "oab_exams": {
+      "acc,all": 0.2305239179954442,
+      "acc,exam_id__2016-20": 0.225,
+      "acc,exam_id__2015-17": 0.24358974358974358,
+      "acc,exam_id__2014-13": 0.225,
+      "acc,exam_id__2018-25": 0.2875,
+      "acc,exam_id__2017-22": 0.2375,
+      "acc,exam_id__2014-14": 0.2625,
+      "acc,exam_id__2013-11": 0.15,
+      "acc,exam_id__2015-18": 0.25,
+      "acc,exam_id__2011-05": 0.225,
+      "acc,exam_id__2012-08": 0.2375,
+      "acc,exam_id__2012-06a": 0.2625,
+      "acc,exam_id__2017-24": 0.225,
+      "acc,exam_id__2012-07": 0.15,
+      "acc,exam_id__2016-20a": 0.275,
+      "acc,exam_id__2016-21": 0.2375,
+      "acc,exam_id__2016-19": 0.19230769230769232,
+      "acc,exam_id__2010-01": 0.3058823529411765,
+      "acc,exam_id__2011-04": 0.25,
+      "acc,exam_id__2012-06": 0.25,
+      "acc,exam_id__2017-23": 0.2,
+      "acc,exam_id__2012-09": 0.2077922077922078,
+      "acc,exam_id__2013-12": 0.1625,
+      "acc,exam_id__2013-10": 0.1875,
+      "acc,exam_id__2011-03": 0.25252525252525254,
+      "acc,exam_id__2015-16": 0.2375,
+      "acc,exam_id__2010-02": 0.26,
+      "acc,exam_id__2014-15": 0.20512820512820512,
+      "alias": "oab_exams"
+    },
+    "portuguese_hate_speech": {
+      "alias": "portuguese_hate_speech_binary",
+      "f1_macro,all": 0.4576046634870164,
+      "acc,all": 0.581668625146886
+    },
+    "tweetsentbr": {
+      "f1_macro,all": 0.3732164088082346,
+      "acc,all": 0.408955223880597,
+      "alias": "tweetsentbr"
+    }
+  },
+  "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"
+        ]
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "all",
+          "filter": [
+            {
+              "function": "find_similar_label",
+              "labels": [
+                "Sim",
+                "Não"
+              ]
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "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 0x7f8e52c3d8a0>",
+      "description": "Abaixo estão pares de frases que você deve avaliar o grau de similaridade. Dê uma pontuação entre 1,0 e 5,0, sendo 1,0 pouco similar e 5,0 muito similar.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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
+            },
+            {
+              "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 0x7f8e52c3d260>",
+      "doc_to_target": "{{answerKey}}",
+      "description": "As perguntas a seguir são questões de múltipla escolha de provas de vestibular de universidades brasileiras, selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\", \"D\" ou \"E\".\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "id_sampler",
+        "sampler_config": {
+          "id_list": [
+            "USP_2018_3",
+            "UNICAMP_2018_2",
+            "USP_2018_35",
+            "UNICAMP_2018_16",
+            "USP_2018_89"
+          ],
+          "id_column": "id",
+          "exclude_from_task": true
+        }
+      },
+      "num_fewshot": 3,
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "acc",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "max_gen_toks": 32,
+        "do_sample": false,
+        "temperature": 0.0,
+        "top_k": null,
+        "top_p": null,
+        "until": [
+          "\n\n"
+        ]
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "all",
+          "filter": [
+            {
+              "function": "normalize_spaces"
+            },
+            {
+              "function": "remove_accents"
+            },
+            {
+              "function": "find_choices",
+              "choices": [
+                "A",
+                "B",
+                "C",
+                "D",
+                "E"
+              ],
+              "regex_patterns": [
+                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                "\\b([ABCDE])\\.",
+                "\\b([ABCDE]) ?[.):-]",
+                "\\b([ABCDE])$",
+                "\\b([ABCDE])\\b"
+              ]
+            },
+            {
+              "function": "take_first"
+            }
+          ],
+          "group_by": {
+            "column": "exam_id"
+          }
+        }
+      ],
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8e52c3d4e0>",
+      "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 0x7f8e52c3da80>",
+      "doc_to_target": "{{answerKey}}",
+      "description": "As perguntas a seguir são questões de múltipla escolha do Exame Nacional do Ensino Médio (ENEM), selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\", \"D\" ou \"E\".\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "id_sampler",
+        "sampler_config": {
+          "id_list": [
+            "2022_21",
+            "2022_88",
+            "2022_143"
+          ],
+          "id_column": "id",
+          "exclude_from_task": true
+        }
+      },
+      "num_fewshot": 3,
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "acc",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "max_gen_toks": 32,
+        "do_sample": false,
+        "temperature": 0.0,
+        "top_k": null,
+        "top_p": null,
+        "until": [
+          "\n\n"
+        ]
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "all",
+          "filter": [
+            {
+              "function": "normalize_spaces"
+            },
+            {
+              "function": "remove_accents"
+            },
+            {
+              "function": "find_choices",
+              "choices": [
+                "A",
+                "B",
+                "C",
+                "D",
+                "E"
+              ],
+              "regex_patterns": [
+                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
+                "\\b([ABCDE])\\.",
+                "\\b([ABCDE]) ?[.):-]",
+                "\\b([ABCDE])$",
+                "\\b([ABCDE])\\b"
+              ]
+            },
+            {
+              "function": "take_first"
+            }
+          ],
+          "group_by": {
+            "column": "exam_id"
+          }
+        }
+      ],
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f8e52c3dd00>",
+      "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,
+            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
+          ]
+        }
+      },
+      "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
+      }
+    },
+    "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,
+            3555,
+            16,
+            56,
+            3535,
+            60,
+            40,
+            3527,
+            4,
+            76,
+            3579,
+            3523,
+            3551,
+            68,
+            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"
+              ]
+            },
+            {
+              "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 0x7f8e52c3cc20>",
+      "doc_to_target": "{{answerKey}}",
+      "description": "As perguntas a seguir são questões de múltipla escolha do Exame de Ordem da Ordem dos Advogados do Brasil (OAB), selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\" ou \"D\".\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "id_sampler",
+        "sampler_config": {
+          "id_list": [
+            "2010-01_1",
+            "2010-01_11",
+            "2010-01_13",
+            "2010-01_23",
+            "2010-01_26",
+            "2010-01_28",
+            "2010-01_38",
+            "2010-01_48",
+            "2010-01_58",
+            "2010-01_68",
+            "2010-01_76",
+            "2010-01_83",
+            "2010-01_85",
+            "2010-01_91",
+            "2010-01_99"
+          ],
+          "id_column": "id",
+          "exclude_from_task": true
+        }
+      },
+      "num_fewshot": 3,
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "acc",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "max_gen_toks": 32,
+        "do_sample": false,
+        "temperature": 0.0,
+        "top_k": null,
+        "top_p": null,
+        "until": [
+          "\n\n"
+        ]
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "all",
+          "filter": [
+            {
+              "function": "normalize_spaces"
+            },
+            {
+              "function": "remove_accents"
+            },
+            {
+              "function": "find_choices",
+              "choices": [
+                "A",
+                "B",
+                "C",
+                "D"
+              ],
+              "regex_patterns": [
+                "(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCD])\\b",
+                "\\b([ABCD])\\.",
+                "\\b([ABCD]) ?[.):-]",
+                "\\b([ABCD])$",
+                "\\b([ABCD])\\b"
+              ]
+            },
+            {
+              "function": "take_first"
+            }
+          ],
+          "group_by": {
+            "column": "exam_id"
+          }
+        }
+      ],
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "<function doc_to_text at 0x7f8e52c3cea0>",
+      "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,
+            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"
+        ]
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "all",
+          "filter": [
+            {
+              "function": "find_similar_label",
+              "labels": [
+                "Sim",
+                "Não"
+              ]
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "tweetsentbr": {
+      "task": "tweetsentbr",
+      "group": [
+        "pt_benchmark"
+      ],
+      "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": {
+        "sampler": "id_sampler",
+        "sampler_config": {
+          "id_list": [
+            "862006098672459776",
+            "861612241703063552",
+            "861833257087848448",
+            "861283345476571138",
+            "861283000335695873",
+            "862139461274152962",
+            "862139468702265344",
+            "862006107702734848",
+            "862004354458537984",
+            "861833322925883392",
+            "861603063190171648",
+            "862139462716989440",
+            "862005877355810818",
+            "861751885862244353",
+            "862045180261695489",
+            "862004252499226630",
+            "862023970828292097",
+            "862041752127107074",
+            "862034961863503872",
+            "861293756548608001",
+            "861993527575695360",
+            "862003099355021315",
+            "862002404086206467",
+            "861282989602463744",
+            "862139454399668229",
+            "862139463769743361",
+            "862054906689138688",
+            "862139446535360513",
+            "861997363744911361",
+            "862057988898648065",
+            "861329080083521536",
+            "861286289034838016",
+            "861833050526806017",
+            "861300658565255169",
+            "861989003821813760",
+            "861682750398631938",
+            "861283275716907008",
+            "861283402523267072",
+            "861873108147466240",
+            "862139462138171392",
+            "861284090271715333",
+            "862139446149427201",
+            "861629109331525633",
+            "861721698609098753",
+            "862139453124612096",
+            "861283339482914816",
+            "861282466291748867",
+            "862055346759749632",
+            "862003019860389891",
+            "862140698346344449",
+            "862084376280092672",
+            "862003058708017152",
+            "862000677345787904",
+            "862029129310502913",
+            "862005822376882178",
+            "861969836297134085",
+            "861302955361927168",
+            "862064949451005953",
+            "861282589541355520",
+            "862005476858486784",
+            "862004684411850757",
+            "862139471101349890",
+            "862139467146170368",
+            "862139475098558465",
+            "862140706550403072",
+            "861282777001537536",
+            "862003184147079169",
+            "861283410656059394",
+            "861283417857691649",
+            "861888778922856448",
+            "861655860812099585",
+            "861834248063504384",
+            "862005210935382017",
+            "861282716930760704",
+            "861287082433622022"
+          ],
+          "id_column": "id"
+        }
+      },
+      "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": [
+                "Positivo",
+                "Neutro",
+                "Negativo"
+              ]
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "assin2_rte": 1.1,
+    "assin2_sts": 1.1,
+    "bluex": 1.1,
+    "enem_challenge": 1.1,
+    "faquad_nli": 1.1,
+    "hatebr_offensive": 1.0,
+    "oab_exams": 1.5,
+    "portuguese_hate_speech": 1.0,
+    "tweetsentbr": 1.0
+  },
+  "n-shot": {
+    "assin2_rte": 15,
+    "assin2_sts": 15,
+    "bluex": 3,
+    "enem_challenge": 3,
+    "faquad_nli": 15,
+    "hatebr_offensive": 25,
+    "oab_exams": 3,
+    "portuguese_hate_speech": 25,
+    "tweetsentbr": 25
+  },
+  "model_meta": {
+    "truncated": 376,
+    "non_truncated": 13774,
+    "padded": 0,
+    "non_padded": 14150,
+    "fewshots_truncated": 453,
+    "has_chat_template": false,
+    "chat_type": null,
+    "n_gpus": 1,
+    "accelerate_num_process": null,
+    "model_sha": "141067009124b9c0aea62c76b3eb952174864057",
+    "model_dtype": "torch.float16",
+    "model_memory_footprint": 6874251600,
+    "model_num_parameters": 3426473600,
+    "model_is_loaded_in_4bit": false,
+    "model_is_loaded_in_8bit": false,
+    "model_is_quantized": null,
+    "model_device": "cuda:0",
+    "batch_size": 32,
+    "max_length": 2048,
+    "max_ctx_length": 2016,
+    "max_gen_toks": 32
+  },
+  "task_model_meta": {
+    "assin2_rte": {
+      "sample_size": 2448,
+      "truncated": 0,
+      "non_truncated": 2448,
+      "padded": 0,
+      "non_padded": 2448,
+      "fewshots_truncated": 0,
+      "mean_seq_length": 1495.0273692810458,
+      "min_seq_length": 1470,
+      "max_seq_length": 1564,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 15.0,
+      "mean_effective_fewshot_size": 15.0
+    },
+    "assin2_sts": {
+      "sample_size": 2448,
+      "truncated": 0,
+      "non_truncated": 2448,
+      "padded": 0,
+      "non_padded": 2448,
+      "fewshots_truncated": 0,
+      "mean_seq_length": 1718.0273692810458,
+      "min_seq_length": 1693,
+      "max_seq_length": 1787,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 15.0,
+      "mean_effective_fewshot_size": 15.0
+    },
+    "bluex": {
+      "sample_size": 719,
+      "truncated": 215,
+      "non_truncated": 504,
+      "padded": 0,
+      "non_padded": 719,
+      "fewshots_truncated": 284,
+      "mean_seq_length": 1889.3643949930458,
+      "min_seq_length": 1476,
+      "max_seq_length": 2763,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 3.0,
+      "mean_effective_fewshot_size": 2.6050069541029206
+    },
+    "enem_challenge": {
+      "sample_size": 1429,
+      "truncated": 160,
+      "non_truncated": 1269,
+      "padded": 0,
+      "non_padded": 1429,
+      "fewshots_truncated": 168,
+      "mean_seq_length": 1795.555633310007,
+      "min_seq_length": 1494,
+      "max_seq_length": 2885,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 3.0,
+      "mean_effective_fewshot_size": 2.882435269419174
+    },
+    "faquad_nli": {
+      "sample_size": 650,
+      "truncated": 0,
+      "non_truncated": 650,
+      "padded": 0,
+      "non_padded": 650,
+      "fewshots_truncated": 0,
+      "mean_seq_length": 1766.9384615384615,
+      "min_seq_length": 1705,
+      "max_seq_length": 1897,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 15.0,
+      "mean_effective_fewshot_size": 15.0
+    },
+    "hatebr_offensive": {
+      "sample_size": 1400,
+      "truncated": 0,
+      "non_truncated": 1400,
+      "padded": 0,
+      "non_padded": 1400,
+      "fewshots_truncated": 0,
+      "mean_seq_length": 1381.715,
+      "min_seq_length": 1354,
+      "max_seq_length": 1669,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 25.0,
+      "mean_effective_fewshot_size": 25.0
+    },
+    "oab_exams": {
+      "sample_size": 2195,
+      "truncated": 1,
+      "non_truncated": 2194,
+      "padded": 0,
+      "non_padded": 2195,
+      "fewshots_truncated": 1,
+      "mean_seq_length": 1550.2555808656036,
+      "min_seq_length": 1249,
+      "max_seq_length": 2101,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 3.0,
+      "mean_effective_fewshot_size": 2.9995444191343963
+    },
+    "portuguese_hate_speech": {
+      "sample_size": 851,
+      "truncated": 0,
+      "non_truncated": 851,
+      "padded": 0,
+      "non_padded": 851,
+      "fewshots_truncated": 0,
+      "mean_seq_length": 1925.7978848413632,
+      "min_seq_length": 1888,
+      "max_seq_length": 1965,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 25.0,
+      "mean_effective_fewshot_size": 25.0
+    },
+    "tweetsentbr": {
+      "sample_size": 2010,
+      "truncated": 0,
+      "non_truncated": 2010,
+      "padded": 0,
+      "non_padded": 2010,
+      "fewshots_truncated": 0,
+      "mean_seq_length": 1666.0656716417911,
+      "min_seq_length": 1643,
+      "max_seq_length": 1783,
+      "max_ctx_length": 2016,
+      "max_gen_toks": 32,
+      "mean_original_fewshots_size": 25.0,
+      "mean_effective_fewshot_size": 25.0
+    }
+  },
+  "config": {
+    "model": "huggingface",
+    "model_args": "pretrained=openlm-research/open_llama_3b,dtype=float16,device=cuda:0,revision=main,trust_remote_code=True,starting_max_length=4096",
+    "batch_size": "auto",
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": [
+      null,
+      null,
+      null,
+      null,
+      null,
+      null,
+      null,
+      null,
+      null
+    ],
+    "bootstrap_iters": 0,
+    "gen_kwargs": null
+  },
+  "git_hash": "804df15"
+}

openlm-research/open_llama_3b/results_2024-02-17T09-33-21.785739.json

@@ -0,0 +1,325 @@
+{
+    "config_general": {
+        "start_date": "2024-02-17T09-33-21.785739",
+        "start_time": 1708162402.684483,
+        "end_time": 1708165939.1434646,
+        "total_evaluation_time_seconds": 3536.458981513977,
+        "has_chat_template": false,
+        "chat_type": null,
+        "n_gpus": 1,
+        "accelerate_num_process": null,
+        "model_sha": "141067009124b9c0aea62c76b3eb952174864057",
+        "model_dtype": "float16",
+        "model_memory_footprint": 6874251600,
+        "model_num_parameters": 3426473600,
+        "model_is_loaded_in_4bit": false,
+        "model_is_loaded_in_8bit": false,
+        "model_is_quantized": null,
+        "model_device": "cuda:0",
+        "batch_size": 32,
+        "max_length": 2048,
+        "max_ctx_length": 2016,
+        "max_gen_toks": 32,
+        "model_name": "openlm-research/open_llama_3b",
+        "job_id": 235,
+        "model_id": "openlm-research/open_llama_3b_eval_request_False_float16_Original",
+        "model_base_model": "",
+        "model_weight_type": "Original",
+        "model_revision": "main",
+        "model_private": false,
+        "model_type": "🟢 : pretrained",
+        "model_architectures": "LlamaForCausalLM",
+        "submitted_time": "2024-02-11T13:34:13Z",
+        "lm_eval_model_type": "huggingface",
+        "eval_version": "1.1.0"
+    },
+    "results": {
+        "all_grouped_average": 0.3018688721827909,
+        "all_grouped_npm": -0.055465157217862306,
+        "all_grouped": {
+            "enem_challenge": 0.1966410076976907,
+            "bluex": 0.22253129346314326,
+            "oab_exams": 0.2305239179954442,
+            "assin2_rte": 0.35297899277093914,
+            "assin2_sts": 0.05530368768431126,
+            "faquad_nli": 0.4396551724137931,
+            "hatebr_offensive": 0.38836470532454603,
+            "portuguese_hate_speech": 0.4576046634870164,
+            "tweetsentbr": 0.3732164088082346
+        },
+        "all": {
+            "harness|enem_challenge|enem_challenge|None|3": 0.1966410076976907,
+            "harness|bluex|bluex|None|3": 0.22253129346314326,
+            "harness|oab_exams|oab_exams|None|3": 0.2305239179954442,
+            "harness|assin2_rte|assin2_rte|None|15": 0.35297899277093914,
+            "harness|assin2_sts|assin2_sts|None|15": 0.05530368768431126,
+            "harness|faquad_nli|faquad_nli|None|15": 0.4396551724137931,
+            "harness|hatebr_offensive|hatebr_offensive|None|25": 0.38836470532454603,
+            "harness|portuguese_hate_speech|portuguese_hate_speech|None|25": 0.4576046634870164,
+            "harness|tweetsentbr|tweetsentbr|None|25": 0.3732164088082346
+        },
+        "harness|enem_challenge|enem_challenge|None|3": {
+            "acc,all": 0.1966410076976907,
+            "acc,exam_id__2023": 0.2814814814814815,
+            "acc,exam_id__2010": 0.17094017094017094,
+            "acc,exam_id__2016_2": 0.2032520325203252,
+            "acc,exam_id__2011": 0.2222222222222222,
+            "acc,exam_id__2022": 0.21052631578947367,
+            "acc,exam_id__2015": 0.14285714285714285,
+            "acc,exam_id__2013": 0.16666666666666666,
+            "acc,exam_id__2014": 0.1926605504587156,
+            "acc,exam_id__2009": 0.16521739130434782,
+            "acc,exam_id__2016": 0.19008264462809918,
+            "acc,exam_id__2012": 0.1896551724137931,
+            "acc,exam_id__2017": 0.20689655172413793,
+            "main_score": 0.1966410076976907
+        },
+        "harness|bluex|bluex|None|3": {
+            "acc,all": 0.22253129346314326,
+            "acc,exam_id__UNICAMP_2020": 0.2909090909090909,
+            "acc,exam_id__UNICAMP_2021_2": 0.2549019607843137,
+            "acc,exam_id__USP_2018": 0.1111111111111111,
+            "acc,exam_id__UNICAMP_2023": 0.27906976744186046,
+            "acc,exam_id__USP_2024": 0.04878048780487805,
+            "acc,exam_id__UNICAMP_2021_1": 0.32608695652173914,
+            "acc,exam_id__USP_2020": 0.2857142857142857,
+            "acc,exam_id__USP_2019": 0.15,
+            "acc,exam_id__USP_2023": 0.09090909090909091,
+            "acc,exam_id__UNICAMP_2019": 0.28,
+            "acc,exam_id__USP_2022": 0.22448979591836735,
+            "acc,exam_id__UNICAMP_2024": 0.2222222222222222,
+            "acc,exam_id__USP_2021": 0.19230769230769232,
+            "acc,exam_id__UNICAMP_2022": 0.2564102564102564,
+            "acc,exam_id__UNICAMP_2018": 0.2777777777777778,
+            "main_score": 0.22253129346314326
+        },
+        "harness|oab_exams|oab_exams|None|3": {
+            "acc,all": 0.2305239179954442,
+            "acc,exam_id__2016-20": 0.225,
+            "acc,exam_id__2015-17": 0.24358974358974358,
+            "acc,exam_id__2014-13": 0.225,
+            "acc,exam_id__2018-25": 0.2875,
+            "acc,exam_id__2017-22": 0.2375,
+            "acc,exam_id__2014-14": 0.2625,
+            "acc,exam_id__2013-11": 0.15,
+            "acc,exam_id__2015-18": 0.25,
+            "acc,exam_id__2011-05": 0.225,
+            "acc,exam_id__2012-08": 0.2375,
+            "acc,exam_id__2012-06a": 0.2625,
+            "acc,exam_id__2017-24": 0.225,
+            "acc,exam_id__2012-07": 0.15,
+            "acc,exam_id__2016-20a": 0.275,
+            "acc,exam_id__2016-21": 0.2375,
+            "acc,exam_id__2016-19": 0.19230769230769232,
+            "acc,exam_id__2010-01": 0.3058823529411765,
+            "acc,exam_id__2011-04": 0.25,
+            "acc,exam_id__2012-06": 0.25,
+            "acc,exam_id__2017-23": 0.2,
+            "acc,exam_id__2012-09": 0.2077922077922078,
+            "acc,exam_id__2013-12": 0.1625,
+            "acc,exam_id__2013-10": 0.1875,
+            "acc,exam_id__2011-03": 0.25252525252525254,
+            "acc,exam_id__2015-16": 0.2375,
+            "acc,exam_id__2010-02": 0.26,
+            "acc,exam_id__2014-15": 0.20512820512820512,
+            "main_score": 0.2305239179954442
+        },
+        "harness|assin2_rte|assin2_rte|None|15": {
+            "f1_macro,all": 0.35297899277093914,
+            "acc,all": 0.5020424836601307,
+            "main_score": 0.35297899277093914
+        },
+        "harness|assin2_sts|assin2_sts|None|15": {
+            "pearson,all": 0.05530368768431126,
+            "mse,all": 2.285600490196079,
+            "main_score": 0.05530368768431126
+        },
+        "harness|faquad_nli|faquad_nli|None|15": {
+            "f1_macro,all": 0.4396551724137931,
+            "acc,all": 0.7846153846153846,
+            "main_score": 0.4396551724137931
+        },
+        "harness|hatebr_offensive|hatebr_offensive|None|25": {
+            "f1_macro,all": 0.38836470532454603,
+            "acc,all": 0.4471428571428571,
+            "main_score": 0.38836470532454603
+        },
+        "harness|portuguese_hate_speech|portuguese_hate_speech|None|25": {
+            "f1_macro,all": 0.4576046634870164,
+            "acc,all": 0.581668625146886,
+            "main_score": 0.4576046634870164
+        },
+        "harness|tweetsentbr|tweetsentbr|None|25": {
+            "f1_macro,all": 0.3732164088082346,
+            "acc,all": 0.408955223880597,
+            "main_score": 0.3732164088082346
+        }
+    },
+    "config_tasks": {
+        "harness|enem_challenge|enem_challenge": "LM Harness task",
+        "harness|bluex|bluex": "LM Harness task",
+        "harness|oab_exams|oab_exams": "LM Harness task",
+        "harness|assin2_rte|assin2_rte": "LM Harness task",
+        "harness|assin2_sts|assin2_sts": "LM Harness task",
+        "harness|faquad_nli|faquad_nli": "LM Harness task",
+        "harness|hatebr_offensive|hatebr_offensive": "LM Harness task",
+        "harness|portuguese_hate_speech|portuguese_hate_speech": "LM Harness task",
+        "harness|tweetsentbr|tweetsentbr": "LM Harness task"
+    },
+    "versions": {
+        "all": 0,
+        "harness|enem_challenge|enem_challenge": 1.1,
+        "harness|bluex|bluex": 1.1,
+        "harness|oab_exams|oab_exams": 1.5,
+        "harness|assin2_rte|assin2_rte": 1.1,
+        "harness|assin2_sts|assin2_sts": 1.1,
+        "harness|faquad_nli|faquad_nli": 1.1,
+        "harness|hatebr_offensive|hatebr_offensive": 1.0,
+        "harness|portuguese_hate_speech|portuguese_hate_speech": 1.0,
+        "harness|tweetsentbr|tweetsentbr": 1.0
+    },
+    "summary_tasks": {
+        "harness|enem_challenge|enem_challenge|None|3": {
+            "sample_size": 1429,
+            "truncated": 160,
+            "non_truncated": 1269,
+            "padded": 0,
+            "non_padded": 1429,
+            "fewshots_truncated": 168,
+            "mean_seq_length": 1795.555633310007,
+            "min_seq_length": 1494,
+            "max_seq_length": 2885,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 3.0,
+            "mean_effective_fewshot_size": 2.882435269419174
+        },
+        "harness|bluex|bluex|None|3": {
+            "sample_size": 719,
+            "truncated": 215,
+            "non_truncated": 504,
+            "padded": 0,
+            "non_padded": 719,
+            "fewshots_truncated": 284,
+            "mean_seq_length": 1889.3643949930458,
+            "min_seq_length": 1476,
+            "max_seq_length": 2763,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 3.0,
+            "mean_effective_fewshot_size": 2.6050069541029206
+        },
+        "harness|oab_exams|oab_exams|None|3": {
+            "sample_size": 2195,
+            "truncated": 1,
+            "non_truncated": 2194,
+            "padded": 0,
+            "non_padded": 2195,
+            "fewshots_truncated": 1,
+            "mean_seq_length": 1550.2555808656036,
+            "min_seq_length": 1249,
+            "max_seq_length": 2101,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 3.0,
+            "mean_effective_fewshot_size": 2.9995444191343963
+        },
+        "harness|assin2_rte|assin2_rte|None|15": {
+            "sample_size": 2448,
+            "truncated": 0,
+            "non_truncated": 2448,
+            "padded": 0,
+            "non_padded": 2448,
+            "fewshots_truncated": 0,
+            "mean_seq_length": 1495.0273692810458,
+            "min_seq_length": 1470,
+            "max_seq_length": 1564,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 15.0,
+            "mean_effective_fewshot_size": 15.0
+        },
+        "harness|assin2_sts|assin2_sts|None|15": {
+            "sample_size": 2448,
+            "truncated": 0,
+            "non_truncated": 2448,
+            "padded": 0,
+            "non_padded": 2448,
+            "fewshots_truncated": 0,
+            "mean_seq_length": 1718.0273692810458,
+            "min_seq_length": 1693,
+            "max_seq_length": 1787,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 15.0,
+            "mean_effective_fewshot_size": 15.0
+        },
+        "harness|faquad_nli|faquad_nli|None|15": {
+            "sample_size": 650,
+            "truncated": 0,
+            "non_truncated": 650,
+            "padded": 0,
+            "non_padded": 650,
+            "fewshots_truncated": 0,
+            "mean_seq_length": 1766.9384615384615,
+            "min_seq_length": 1705,
+            "max_seq_length": 1897,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 15.0,
+            "mean_effective_fewshot_size": 15.0
+        },
+        "harness|hatebr_offensive|hatebr_offensive|None|25": {
+            "sample_size": 1400,
+            "truncated": 0,
+            "non_truncated": 1400,
+            "padded": 0,
+            "non_padded": 1400,
+            "fewshots_truncated": 0,
+            "mean_seq_length": 1381.715,
+            "min_seq_length": 1354,
+            "max_seq_length": 1669,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 25.0,
+            "mean_effective_fewshot_size": 25.0
+        },
+        "harness|portuguese_hate_speech|portuguese_hate_speech|None|25": {
+            "sample_size": 851,
+            "truncated": 0,
+            "non_truncated": 851,
+            "padded": 0,
+            "non_padded": 851,
+            "fewshots_truncated": 0,
+            "mean_seq_length": 1925.7978848413632,
+            "min_seq_length": 1888,
+            "max_seq_length": 1965,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 25.0,
+            "mean_effective_fewshot_size": 25.0
+        },
+        "harness|tweetsentbr|tweetsentbr|None|25": {
+            "sample_size": 2010,
+            "truncated": 0,
+            "non_truncated": 2010,
+            "padded": 0,
+            "non_padded": 2010,
+            "fewshots_truncated": 0,
+            "mean_seq_length": 1666.0656716417911,
+            "min_seq_length": 1643,
+            "max_seq_length": 1783,
+            "max_ctx_length": 2016,
+            "max_gen_toks": 32,
+            "mean_original_fewshots_size": 25.0,
+            "mean_effective_fewshot_size": 25.0
+        }
+    },
+    "summary_general": {
+        "truncated": 376,
+        "non_truncated": 13774,
+        "padded": 0,
+        "non_padded": 14150,
+        "fewshots_truncated": 453
+    }
+}