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llm_pt_leaderboard_raw_results / Intel /neural-chat-7b-v3-3 /raw_2024-02-21T22-54-50.520595 /results.json
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{
"results": {
"assin2_rte": {
"f1_macro,all": 0.9140545431322211,
"acc,all": 0.9142156862745098,
"alias": "assin2_rte"
},
"assin2_sts": {
"pearson,all": 0.7587721518241414,
"mse,all": 0.5857066993464052,
"alias": "assin2_sts"
},
"bluex": {
"acc,all": 0.5034770514603616,
"acc,exam_id__USP_2021": 0.4423076923076923,
"acc,exam_id__UNICAMP_2021_2": 0.47058823529411764,
"acc,exam_id__UNICAMP_2023": 0.6046511627906976,
"acc,exam_id__UNICAMP_2021_1": 0.43478260869565216,
"acc,exam_id__USP_2024": 0.6585365853658537,
"acc,exam_id__UNICAMP_2018": 0.46296296296296297,
"acc,exam_id__USP_2022": 0.42857142857142855,
"acc,exam_id__UNICAMP_2020": 0.45454545454545453,
"acc,exam_id__USP_2018": 0.3888888888888889,
"acc,exam_id__USP_2020": 0.5535714285714286,
"acc,exam_id__UNICAMP_2022": 0.5641025641025641,
"acc,exam_id__USP_2019": 0.475,
"acc,exam_id__USP_2023": 0.6590909090909091,
"acc,exam_id__UNICAMP_2019": 0.58,
"acc,exam_id__UNICAMP_2024": 0.4444444444444444,
"alias": "bluex"
},
"enem_challenge": {
"alias": "enem",
"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
},
"faquad_nli": {
"f1_macro,all": 0.7147222222222223,
"acc,all": 0.7569230769230769,
"alias": "faquad_nli"
},
"hatebr_offensive": {
"alias": "hatebr_offensive_binary",
"f1_macro,all": 0.8653967318817455,
"acc,all": 0.8657142857142858
},
"oab_exams": {
"acc,all": 0.39635535307517084,
"acc,exam_id__2010-02": 0.43,
"acc,exam_id__2016-19": 0.46153846153846156,
"acc,exam_id__2015-17": 0.47435897435897434,
"acc,exam_id__2016-21": 0.3625,
"acc,exam_id__2017-24": 0.3625,
"acc,exam_id__2012-09": 0.3116883116883117,
"acc,exam_id__2011-04": 0.3625,
"acc,exam_id__2017-23": 0.3875,
"acc,exam_id__2011-03": 0.36363636363636365,
"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,
"acc,exam_id__2013-11": 0.4375,
"acc,exam_id__2014-14": 0.425,
"acc,exam_id__2013-10": 0.425,
"acc,exam_id__2010-01": 0.3176470588235294,
"acc,exam_id__2013-12": 0.4125,
"acc,exam_id__2015-16": 0.2875,
"acc,exam_id__2012-06a": 0.4375,
"acc,exam_id__2016-20": 0.4125,
"acc,exam_id__2012-08": 0.325,
"alias": "oab_exams"
},
"portuguese_hate_speech": {
"alias": "portuguese_hate_speech_binary",
"f1_macro,all": 0.6322323153577603,
"acc,all": 0.6404230317273796
},
"tweetsentbr": {
"f1_macro,all": 0.6252347993335684,
"acc,all": 0.6925373134328359,
"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,
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7,
3254,
3255,
3256,
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10,
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3258,
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13,
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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 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
},
{
"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"
},
{
"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])$",
"\\b([ABCDE])\\b"
]
},
{
"function": "take_first"
}
],
"group_by": {
"column": "exam_id"
}
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7fd79f4a4d60>",
"metadata": {
"version": 1.1
}
},
"enem_challenge": {
"task": "enem_challenge",
"task_alias": "enem",
"group": [
"pt_benchmark",
"vestibular"
],
"dataset_path": "eduagarcia/enem_challenge",
"test_split": "train",
"fewshot_split": "train",
"doc_to_text": "<function enem_doc_to_text at 0x7fd79f4a5300>",
"doc_to_target": "{{answerKey}}",
"description": "As perguntas a seguir são questões de múltipla escolha do Exame Nacional do Ensino Médio (ENEM), selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\", \"D\" ou \"E\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
"2022_21",
"2022_88",
"2022_143"
],
"id_column": "id",
"exclude_from_task": true
}
},
"num_fewshot": 3,
"metric_list": [
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "normalize_spaces"
},
{
"function": "remove_accents"
},
{
"function": "find_choices",
"choices": [
"A",
"B",
"C",
"D",
"E"
],
"regex_patterns": [
"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
"\\b([ABCDE])\\.",
"\\b([ABCDE]) ?[.):-]",
"\\b([ABCDE])$",
"\\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
}
},
"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,
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3523,
3551,
68,
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84,
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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 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": {
"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 0x7fd79f4a4720>",
"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": " ",
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