eduagarcia's picture
Uploading raw results for 01-ai/Yi-1.5-9B-32K
8e3f3a8 verified
{
"results": {
"assin2_rte": {
"f1_macro,all": 0.8657419886018202,
"acc,all": 0.8660130718954249,
"alias": "assin2_rte"
},
"assin2_sts": {
"pearson,all": 0.7267527969011244,
"mse,all": 0.6419730392156864,
"alias": "assin2_sts"
},
"bluex": {
"acc,all": 0.5702364394993046,
"acc,exam_id__UNICAMP_2021_2": 0.5098039215686274,
"acc,exam_id__USP_2022": 0.5714285714285714,
"acc,exam_id__UNICAMP_2019": 0.68,
"acc,exam_id__USP_2020": 0.5892857142857143,
"acc,exam_id__UNICAMP_2021_1": 0.5869565217391305,
"acc,exam_id__USP_2021": 0.4807692307692308,
"acc,exam_id__USP_2024": 0.7317073170731707,
"acc,exam_id__USP_2018": 0.46296296296296297,
"acc,exam_id__USP_2023": 0.5909090909090909,
"acc,exam_id__USP_2019": 0.55,
"acc,exam_id__UNICAMP_2022": 0.5384615384615384,
"acc,exam_id__UNICAMP_2023": 0.7674418604651163,
"acc,exam_id__UNICAMP_2020": 0.509090909090909,
"acc,exam_id__UNICAMP_2024": 0.4888888888888889,
"acc,exam_id__UNICAMP_2018": 0.5555555555555556,
"alias": "bluex"
},
"enem_challenge": {
"alias": "enem",
"acc,all": 0.6724982505248426,
"acc,exam_id__2022": 0.6466165413533834,
"acc,exam_id__2016_2": 0.6666666666666666,
"acc,exam_id__2011": 0.7777777777777778,
"acc,exam_id__2017": 0.6982758620689655,
"acc,exam_id__2012": 0.6896551724137931,
"acc,exam_id__2009": 0.6260869565217392,
"acc,exam_id__2010": 0.7008547008547008,
"acc,exam_id__2013": 0.6203703703703703,
"acc,exam_id__2016": 0.6446280991735537,
"acc,exam_id__2014": 0.7064220183486238,
"acc,exam_id__2015": 0.6470588235294118,
"acc,exam_id__2023": 0.6518518518518519
},
"faquad_nli": {
"f1_macro,all": 0.5410839160839161,
"acc,all": 0.8061538461538461,
"alias": "faquad_nli"
},
"hatebr_offensive": {
"alias": "hatebr_offensive_binary",
"f1_macro,all": 0.7806530019415174,
"acc,all": 0.7885714285714286
},
"oab_exams": {
"acc,all": 0.5011389521640092,
"acc,exam_id__2011-03": 0.40404040404040403,
"acc,exam_id__2017-23": 0.5125,
"acc,exam_id__2015-17": 0.6410256410256411,
"acc,exam_id__2017-24": 0.5125,
"acc,exam_id__2018-25": 0.4875,
"acc,exam_id__2014-13": 0.4875,
"acc,exam_id__2013-12": 0.5,
"acc,exam_id__2014-14": 0.6,
"acc,exam_id__2012-08": 0.4875,
"acc,exam_id__2012-06": 0.5375,
"acc,exam_id__2012-07": 0.425,
"acc,exam_id__2015-18": 0.5375,
"acc,exam_id__2011-05": 0.45,
"acc,exam_id__2012-09": 0.38961038961038963,
"acc,exam_id__2016-20a": 0.45,
"acc,exam_id__2017-22": 0.575,
"acc,exam_id__2012-06a": 0.4875,
"acc,exam_id__2016-19": 0.5256410256410257,
"acc,exam_id__2013-11": 0.55,
"acc,exam_id__2016-20": 0.5125,
"acc,exam_id__2014-15": 0.6153846153846154,
"acc,exam_id__2010-01": 0.4235294117647059,
"acc,exam_id__2011-04": 0.475,
"acc,exam_id__2013-10": 0.55,
"acc,exam_id__2010-02": 0.46,
"acc,exam_id__2015-16": 0.5,
"acc,exam_id__2016-21": 0.475,
"alias": "oab_exams"
},
"portuguese_hate_speech": {
"alias": "portuguese_hate_speech_binary",
"f1_macro,all": 0.6955025872509083,
"acc,all": 0.7250293772032902
},
"tweetsentbr": {
"f1_macro,all": 0.6843568952184516,
"acc,all": 0.7203980099502487,
"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 0x7f2892362160>",
"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 0x7f2892361b20>",
"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])$",
"\\b([ABCDE])\\b"
]
},
{
"function": "take_first"
}
],
"group_by": {
"column": "exam_id"
}
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f2892361da0>",
"metadata": {
"version": 1.1
}
},
"enem_challenge": {
"task": "enem_challenge",
"task_alias": "enem",
"group": [
"pt_benchmark",
"vestibular"
],
"dataset_path": "eduagarcia/enem_challenge",
"test_split": "train",
"fewshot_split": "train",
"doc_to_text": "<function enem_doc_to_text at 0x7f2892362340>",
"doc_to_target": "{{answerKey}}",
"description": "As perguntas a seguir são questões de múltipla escolha do Exame Nacional do Ensino Médio (ENEM), selecione a única alternativa correta e responda apenas com as letras \"A\", \"B\", \"C\", \"D\" ou \"E\".\n\n",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"fewshot_config": {
"sampler": "id_sampler",
"sampler_config": {
"id_list": [
"2022_21",
"2022_88",
"2022_143"
],
"id_column": "id",
"exclude_from_task": true
}
},
"num_fewshot": 3,
"metric_list": [
{
"metric": "acc",
"aggregation": "acc",
"higher_is_better": true
}
],
"output_type": "generate_until",
"generation_kwargs": {
"max_gen_toks": 32,
"do_sample": false,
"temperature": 0.0,
"top_k": null,
"top_p": null,
"until": [
"\n\n"
]
},
"repeats": 1,
"filter_list": [
{
"name": "all",
"filter": [
{
"function": "normalize_spaces"
},
{
"function": "remove_accents"
},
{
"function": "find_choices",
"choices": [
"A",
"B",
"C",
"D",
"E"
],
"regex_patterns": [
"(?:[Ll]etra|[Aa]lternativa|[Rr]esposta|[Rr]esposta [Cc]orreta|[Rr]esposta [Cc]orreta e|[Oo]pcao):? ([ABCDE])\\b",
"\\b([ABCDE])\\.",
"\\b([ABCDE]) ?[.):-]",
"\\b([ABCDE])$",
"\\b([ABCDE])\\b"
]
},
{
"function": "take_first"
}
],
"group_by": {
"column": "exam_id"
}
}
],
"should_decontaminate": true,
"doc_to_decontamination_query": "<function enem_doc_to_text at 0x7f28923625c0>",
"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 0x7f28923614e0>",
"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 0x7f2892361760>",
"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/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,
"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": 5,
"non_truncated": 14145,
"padded": 0,
"non_padded": 14150,
"fewshots_truncated": 7,
"has_chat_template": false,
"chat_type": null,
"n_gpus": 1,
"accelerate_num_process": null,
"model_sha": "989edca375ebca9efd8f3a3b567b1e9dd160ee17",
"model_dtype": "torch.bfloat16",
"model_memory_footprint": 17658826752,
"model_num_parameters": 8829407232,
"model_is_loaded_in_4bit": null,
"model_is_loaded_in_8bit": null,
"model_is_quantized": null,
"model_device": "cuda:0",
"batch_size": 16,
"max_length": 2560,
"max_ctx_length": 2528,
"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": 1501.5265522875818,
"min_seq_length": 1477,
"max_seq_length": 1573,
"max_ctx_length": 2528,
"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": 1720.5265522875818,
"min_seq_length": 1696,
"max_seq_length": 1792,
"max_ctx_length": 2528,
"max_gen_toks": 32,
"mean_original_fewshots_size": 15.0,
"mean_effective_fewshot_size": 15.0
},
"bluex": {
"sample_size": 719,
"truncated": 3,
"non_truncated": 716,
"padded": 0,
"non_padded": 719,
"fewshots_truncated": 5,
"mean_seq_length": 1887.1738525730182,
"min_seq_length": 1475,
"max_seq_length": 2769,
"max_ctx_length": 2528,
"max_gen_toks": 32,
"mean_original_fewshots_size": 3.0,
"mean_effective_fewshot_size": 2.9930458970792766
},
"enem_challenge": {
"sample_size": 1429,
"truncated": 2,
"non_truncated": 1427,
"padded": 0,
"non_padded": 1429,
"fewshots_truncated": 2,
"mean_seq_length": 1773.6696990902728,
"min_seq_length": 1479,
"max_seq_length": 2789,
"max_ctx_length": 2528,
"max_gen_toks": 32,
"mean_original_fewshots_size": 3.0,
"mean_effective_fewshot_size": 2.998600419874038
},
"faquad_nli": {
"sample_size": 650,
"truncated": 0,
"non_truncated": 650,
"padded": 0,
"non_padded": 650,
"fewshots_truncated": 0,
"mean_seq_length": 1760.1292307692308,
"min_seq_length": 1700,
"max_seq_length": 1893,
"max_ctx_length": 2528,
"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": 1417.9257142857143,
"min_seq_length": 1390,
"max_seq_length": 1696,
"max_ctx_length": 2528,
"max_gen_toks": 32,
"mean_original_fewshots_size": 25.0,
"mean_effective_fewshot_size": 25.0
},
"oab_exams": {
"sample_size": 2195,
"truncated": 0,
"non_truncated": 2195,
"padded": 0,
"non_padded": 2195,
"fewshots_truncated": 0,
"mean_seq_length": 1523.7266514806379,
"min_seq_length": 1223,
"max_seq_length": 2061,
"max_ctx_length": 2528,
"max_gen_toks": 32,
"mean_original_fewshots_size": 3.0,
"mean_effective_fewshot_size": 3.0
},
"portuguese_hate_speech": {
"sample_size": 851,
"truncated": 0,
"non_truncated": 851,
"padded": 0,
"non_padded": 851,
"fewshots_truncated": 0,
"mean_seq_length": 1945.7544065804934,
"min_seq_length": 1908,
"max_seq_length": 1981,
"max_ctx_length": 2528,
"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": 1614.844776119403,
"min_seq_length": 1592,
"max_seq_length": 1730,
"max_ctx_length": 2528,
"max_gen_toks": 32,
"mean_original_fewshots_size": 25.0,
"mean_effective_fewshot_size": 25.0
}
},
"config": {
"model": "huggingface",
"model_args": "pretrained=01-ai/Yi-1.5-9B-32K,dtype=bfloat16,device=cuda:0,revision=main,trust_remote_code=True,starting_max_length=2560",
"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": "51e0e5e"
}