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| "results": { | |
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| "mse,all": 2.7414133986928113, | |
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| "f1_macro,all": 0.19385342789598106, | |
| "acc,all": 0.41 | |
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| "task": "assin2_rte", | |
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| "dataset_path": "assin2", | |
| "test_split": "test", | |
| "fewshot_split": "train", | |
| "doc_to_text": "Premissa: {{premise}}\nHip贸tese: {{hypothesis}}\nPergunta: A hip贸tese pode ser inferida pela premissa?\nResposta:", | |
| "doc_to_target": "{{['N茫o', 'Sim'][entailment_judgment]}}", | |
| "description": "Abaixo cont茅m pares de premissa e hip贸tese, para cada par voc锚 deve julgar se a hip贸tese pode ser inferida a partir da premissa, responda apenas com Sim ou N茫o.\n\n", | |
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| "dataset_path": "assin2", | |
| "test_split": "test", | |
| "fewshot_split": "train", | |
| "doc_to_text": "Frase 1: {{premise}}\nFrase 2: {{hypothesis}}\nPergunta: Qual o grau de similaridade entre as duas frases de 1,0 a 5,0?\nResposta:", | |
| "doc_to_target": "<function assin2_float_to_pt_str at 0x7f96ddc11800>", | |
| "description": "Abaixo cont茅m pares de frases, para cada par voc锚 deve julgar o grau de similaridade de 1,0 a 5,0, responda apenas com o n煤mero.\n\n", | |
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| "fewshot_delimiter": "\n\n", | |
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| "doc_to_target": "{{answerKey}}", | |
| "description": "As perguntas a seguir s茫o quest玫es de multipla escolha de provas de vestibular de Universidades Brasileiras, reponda apenas com as letras A, B, C, D ou E.\n\n", | |
| "target_delimiter": " ", | |
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| "sampler_config": { | |
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| "UNICAMP_2018_2", | |
| "USP_2018_35", | |
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| "aggregation": "acc", | |
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| "output_type": "generate_until", | |
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| "\\b([ABCDE])\\.", | |
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| "task_alias": "enem", | |
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| "doc_to_text": "<function enem_doc_to_text at 0x7f96ddc119e0>", | |
| "doc_to_target": "{{answerKey}}", | |
| "description": "As perguntas a seguir s茫o quest玫es de multipla escolha do Exame Nacional do Ensino M茅dio (ENEM), reponda apenas com as letras A, B, C, D ou E.\n\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
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| "metric_list": [ | |
| { | |
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| "aggregation": "acc", | |
| "higher_is_better": true | |
| } | |
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| "output_type": "generate_until", | |
| "generation_kwargs": { | |
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| "do_sample": false, | |
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| { | |
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| "B", | |
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| "E" | |
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| "\\b([ABCDE])\\.", | |
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| "metadata": { | |
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| "faquad_nli": { | |
| "task": "faquad_nli", | |
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| "dataset_path": "ruanchaves/faquad-nli", | |
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| "doc_to_target": "{{['N茫o', 'Sim'][label]}}", | |
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| { | |
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| { | |
| "function": "take_first" | |
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| "oab_exams": { | |
| "task": "oab_exams", | |
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| "pt_benchmark" | |
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| "doc_to_text": "<function doc_to_text at 0x7f96ddc10b80>", | |
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| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "id_sampler", | |
| "sampler_config": { | |
| "id_list": [ | |
| "2010-01_1", | |
| "2010-01_11", | |
| "2010-01_13", | |
| "2010-01_23", | |
| "2010-01_26", | |
| "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 0x7f96ddc10e00>", | |
| "metadata": { | |
| "version": 1.4 | |
| } | |
| }, | |
| "sparrow_emotion-2021-cortiz-por": { | |
| "task": "sparrow_emotion-2021-cortiz-por", | |
| "task_alias": "emotion-2021-cortiz-por", | |
| "group": [ | |
| "pt_benchmark", | |
| "sparrow" | |
| ], | |
| "dataset_path": "UBC-NLP/sparrow", | |
| "dataset_name": "emotion-2021-cortiz-por", | |
| "test_split": "validation", | |
| "fewshot_split": "train", | |
| "doc_to_text": "Texto: {{content}}\nPergunta: Qual a principal emo莽茫o apresentada no texto?\nResposta:", | |
| "doc_to_target": "<function sparrow_emotion_por_trans_label at 0x7f96ddc11080>", | |
| "description": "Abaixo cont茅m o conte煤do de tweets de usuarios do Twitter em portugu锚s, sua tarefa 茅 extrair qual a principal emo莽茫o dos textos. Responda com apenas uma das seguintes op莽玫es:\n Admira莽茫o, Divers茫o, Raiva, Aborrecimento, Aprova莽茫o, Compaix茫o, Confus茫o, Curiosidade, Desejo, Decep莽茫o, Desaprova莽茫o, Nojo, Vergonha, Inveja, Entusiasmo, Medo, Gratid茫o, Luto, Alegria, Saudade, Amor, Nervosismo, Otimismo, Orgulho, Al铆vio, Remorso, Tristeza ou Surpresa.\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": [ | |
| "Admira莽茫o", | |
| "Divers茫o", | |
| "Raiva", | |
| "Aborrecimento", | |
| "Aprova莽茫o", | |
| "Compaix茫o", | |
| "Confus茫o", | |
| "Curiosidade", | |
| "Desejo", | |
| "Decep莽茫o", | |
| "Desaprova莽茫o", | |
| "Nojo", | |
| " Vergonha", | |
| "Inveja", | |
| "Entusiasmo", | |
| "Medo", | |
| "Gratid茫o", | |
| "Luto", | |
| "Alegria", | |
| "Saudade", | |
| "Amor", | |
| "Nervosismo", | |
| "Otimismo", | |
| "Orgulho", | |
| "Al铆vio", | |
| "Remorso", | |
| "Tristeza", | |
| "Surpresa" | |
| ] | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "limit": 500, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "sparrow_hate-2019-fortuna-por": { | |
| "task": "sparrow_hate-2019-fortuna-por", | |
| "task_alias": "hate-2019-fortuna-por", | |
| "group": [ | |
| "pt_benchmark", | |
| "sparrow" | |
| ], | |
| "dataset_path": "UBC-NLP/sparrow", | |
| "dataset_name": "hate-2019-fortuna-por", | |
| "test_split": "validation", | |
| "fewshot_split": "train", | |
| "doc_to_text": "Texto: {{content}}\nPergunta: O texto cont茅m discurso de 贸dio?\nResposta:", | |
| "doc_to_target": "{{'Sim' if label == 'Hate' else 'N茫o'}}", | |
| "description": "Abaixo cont茅m o conte煤do de tweets de usuarios do Twitter em portugu锚s, sua tarefa 茅 classificar se o texto contem discurso de 贸dio our n茫o. Responda apenas com Sim ou N茫o.\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": [ | |
| "Sim", | |
| "N茫o" | |
| ] | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "limit": 500, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "sparrow_sentiment-2016-mozetic-por": { | |
| "task": "sparrow_sentiment-2016-mozetic-por", | |
| "task_alias": "sentiment-2016-mozetic-por", | |
| "group": [ | |
| "pt_benchmark", | |
| "sparrow" | |
| ], | |
| "dataset_path": "UBC-NLP/sparrow", | |
| "dataset_name": "sentiment-2016-mozetic-por", | |
| "test_split": "validation", | |
| "fewshot_split": "train", | |
| "doc_to_text": "Texto: {{content}}\nPergunta: O sentimento do texto 茅 Positivo, Neutro ou Negativo?\nResposta:", | |
| "doc_to_target": "{{'Positivo' if label == 'Positive' else ('Negativo' if label == 'Negative' else 'Neutro')}}", | |
| "description": "Abaixo cont茅m o conte煤do de tweets de usuarios do Twitter em portugu锚s, sua tarefa 茅 classificar se o sentimento do texto 茅 Positivo, Neutro ou Negativo. Responda apenas com uma das op莽玫es.\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, | |
| "limit": 500, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "sparrow_sentiment-2018-brum-por": { | |
| "task": "sparrow_sentiment-2018-brum-por", | |
| "task_alias": "sentiment-2018-brum-por", | |
| "group": [ | |
| "pt_benchmark", | |
| "sparrow" | |
| ], | |
| "dataset_path": "UBC-NLP/sparrow", | |
| "dataset_name": "sentiment-2018-brum-por", | |
| "test_split": "validation", | |
| "fewshot_split": "train", | |
| "doc_to_text": "Texto: {{content}}\nPergunta: O sentimento do texto 茅 Positivo, Neutro ou Negativo?\nResposta:", | |
| "doc_to_target": "{{'Positivo' if label == 'Positive' else ('Negativo' if label == 'Negative' else 'Neutro')}}", | |
| "description": "Abaixo cont茅m o conte煤do de tweets de usuarios do Twitter em portugu锚s, sua tarefa 茅 classificar se o sentimento do texto 茅 Positivo, Neutro ou Negativo. Responda apenas com uma das op莽玫es.\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, | |
| "limit": 500, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| } | |
| }, | |
| "versions": { | |
| "assin2_rte": 1.0, | |
| "assin2_sts": 1.0, | |
| "bluex": 1.0, | |
| "enem_challenge": 1.0, | |
| "faquad_nli": 1.0, | |
| "oab_exams": 1.4, | |
| "sparrow_emotion-2021-cortiz-por": 1.0, | |
| "sparrow_hate-2019-fortuna-por": 1.0, | |
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| "bluex": 3, | |
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| "sparrow_sentiment-2016-mozetic-por": 25, | |
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| }, | |
| "model_meta": { | |
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| "non_truncated": 0, | |
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| "non_padded": 11889, | |
| "fewshots_truncated": 65357, | |
| "has_chat_template": false, | |
| "chat_type": null, | |
| "n_gpus": 1, | |
| "accelerate_num_process": null, | |
| "model_sha": "11c5a3d5811f50298f278a704980280950aedb10", | |
| "model_dtype": "torch.float16", | |
| "model_memory_footprint": 261462552, | |
| "model_num_parameters": 124439808, | |
| "model_is_loaded_in_4bit": false, | |
| "model_is_loaded_in_8bit": false, | |
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| "assin2_sts": { | |
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| "faquad_nli": { | |
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| "sparrow_emotion-2021-cortiz-por": { | |
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| }, | |
| "sparrow_hate-2019-fortuna-por": { | |
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| "mean_seq_length": 1824.748, | |
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| "max_ctx_length": 992, | |
| "max_gen_toks": 32, | |
| "mean_original_fewshots_size": 25.0, | |
| "mean_effective_fewshot_size": 12.434 | |
| }, | |
| "sparrow_sentiment-2016-mozetic-por": { | |
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| "non_padded": 500, | |
| "fewshots_truncated": 5303, | |
| "mean_seq_length": 1551.478, | |
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| "max_seq_length": 1588, | |
| "max_ctx_length": 992, | |
| "max_gen_toks": 32, | |
| "mean_original_fewshots_size": 25.0, | |
| "mean_effective_fewshot_size": 14.394 | |
| }, | |
| "sparrow_sentiment-2018-brum-por": { | |
| "sample_size": 500, | |
| "truncated": 500, | |
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| "max_gen_toks": 32, | |
| "mean_original_fewshots_size": 25.0, | |
| "mean_effective_fewshot_size": 12.986 | |
| } | |
| }, | |
| "config": { | |
| "model": "huggingface", | |
| "model_args": "pretrained=gpt2,dtype=float16,device=cuda:1,revision=main,trust_remote_code=True,starting_max_length=4096", | |
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