davanstrien/summary-test · Datasets at Hugging Face

datasetId stringlengths 2 117	card stringlengths 19 1.01M
automated-research-group/llama2_7b_chat-siqa-results	--- dataset_info: - config_name: '{''do_sample''=False, ''beams''=10}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96342 num_examples: 1935 download_size: 47737 dataset_size: 96342 - config_name: '{''do_sample''=False, ''beams''=1}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 180990 num_examples: 1935 download_size: 78972 dataset_size: 180990 - config_name: '{''do_sample''=False, ''beams''=5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96342 num_examples: 1935 download_size: 47737 dataset_size: 96342 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96734 num_examples: 1935 download_size: 47798 dataset_size: 96734 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96981 num_examples: 1935 download_size: 47639 dataset_size: 96981 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96734 num_examples: 1935 download_size: 47798 dataset_size: 96734 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96496 num_examples: 1935 download_size: 47755 dataset_size: 96496 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96746 num_examples: 1935 download_size: 47779 dataset_size: 96746 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96652 num_examples: 1935 download_size: 47680 dataset_size: 96652 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97052 num_examples: 1935 download_size: 47880 dataset_size: 97052 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111264 num_examples: 1935 download_size: 52779 dataset_size: 111264 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97197 num_examples: 1935 download_size: 47939 dataset_size: 97197 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 110781 num_examples: 1935 download_size: 50670 dataset_size: 110781 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97258 num_examples: 1935 download_size: 47698 dataset_size: 97258 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111045 num_examples: 1935 download_size: 50862 dataset_size: 111045 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 98672 num_examples: 1935 download_size: 48132 dataset_size: 98672 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 134089 num_examples: 1935 download_size: 61398 dataset_size: 134089 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 99516 num_examples: 1935 download_size: 48161 dataset_size: 99516 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 137455 num_examples: 1935 download_size: 62213 dataset_size: 137455 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 101581 num_examples: 1935 download_size: 48732 dataset_size: 101581 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 134295 num_examples: 1935 download_size: 61358 dataset_size: 134295 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96734 num_examples: 1935 download_size: 47798 dataset_size: 96734 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96561 num_examples: 1935 download_size: 47834 dataset_size: 96561 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96743 num_examples: 1935 download_size: 47805 dataset_size: 96743 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97090 num_examples: 1935 download_size: 47822 dataset_size: 97090 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96738 num_examples: 1935 download_size: 47791 dataset_size: 96738 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96023 num_examples: 1935 download_size: 47635 dataset_size: 96023 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97412 num_examples: 1935 download_size: 47951 dataset_size: 97412 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111967 num_examples: 1935 download_size: 52185 dataset_size: 111967 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96117 num_examples: 1935 download_size: 47458 dataset_size: 96117 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 112415 num_examples: 1935 download_size: 51502 dataset_size: 112415 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96624 num_examples: 1935 download_size: 47790 dataset_size: 96624 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111988 num_examples: 1935 download_size: 51926 dataset_size: 111988 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 98309 num_examples: 1935 download_size: 47626 dataset_size: 98309 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 134350 num_examples: 1935 download_size: 61471 dataset_size: 134350 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 99802 num_examples: 1935 download_size: 48330 dataset_size: 99802 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 135980 num_examples: 1935 download_size: 61284 dataset_size: 135980 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 100008 num_examples: 1935 download_size: 48359 dataset_size: 100008 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 136931 num_examples: 1935 download_size: 62080 dataset_size: 136931 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96743 num_examples: 1935 download_size: 47805 dataset_size: 96743 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96689 num_examples: 1935 download_size: 47822 dataset_size: 96689 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96738 num_examples: 1935 download_size: 47791 dataset_size: 96738 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96052 num_examples: 1935 download_size: 47356 dataset_size: 96052 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - 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config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97050 num_examples: 1935 download_size: 47889 dataset_size: 97050 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 112690 num_examples: 1935 download_size: 50935 dataset_size: 112690 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96643 num_examples: 1935 download_size: 47676 dataset_size: 96643 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 113898 num_examples: 1935 download_size: 52185 dataset_size: 113898 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 98979 num_examples: 1935 download_size: 47482 dataset_size: 98979 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 136835 num_examples: 1935 download_size: 61929 dataset_size: 136835 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - 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config_name: '{''do_sample''=False, ''beams''=10}' data_files: - split: train path: '{''do_sample''=False, ''beams''=10}/train-' - config_name: '{''do_sample''=False, ''beams''=1}' data_files: - split: train path: '{''do_sample''=False, ''beams''=1}/train-' - config_name: '{''do_sample''=False, ''beams''=5}' data_files: - split: train path: '{''do_sample''=False, ''beams''=5}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}/train-' - 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split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}/train-' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}/train-*' ---
open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large	--- pretty_name: Evaluation run of LordNoah/Alpaca_spin_tuned_gpt2_large dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [LordNoah/Alpaca_spin_tuned_gpt2_large](https://huggingface.co/LordNoah/Alpaca_spin_tuned_gpt2_large)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-22T13:42:11.763277](https://huggingface.co/datasets/open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large/blob/main/results_2024-01-22T13-42-11.763277.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.27225604584142943,\n\ \ \"acc_stderr\": 0.03141590282455585,\n \"acc_norm\": 0.27399653003630087,\n\ \ \"acc_norm_stderr\": 0.03221603447267582,\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757449,\n \"mc2\": 0.39429285512218326,\n\ \ \"mc2_stderr\": 0.01421822540176183\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.2568259385665529,\n \"acc_stderr\": 0.0127669237941168,\n\ \ \"acc_norm\": 0.2790102389078498,\n \"acc_norm_stderr\": 0.013106784883601341\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.36297550288787095,\n\ \ \"acc_stderr\": 0.004798751281560822,\n \"acc_norm\": 0.45120493925512845,\n\ \ \"acc_norm_stderr\": 0.004965963647210318\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.24444444444444444,\n\ \ \"acc_stderr\": 0.037125378336148665,\n \"acc_norm\": 0.24444444444444444,\n\ \ \"acc_norm_stderr\": 0.037125378336148665\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.3026315789473684,\n \"acc_stderr\": 0.03738520676119667,\n\ \ \"acc_norm\": 0.3026315789473684,\n \"acc_norm_stderr\": 0.03738520676119667\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.24,\n\ \ \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.24,\n \ \ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.3433962264150943,\n \"acc_stderr\": 0.02922452646912479,\n\ \ \"acc_norm\": 0.3433962264150943,\n \"acc_norm_stderr\": 0.02922452646912479\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2569444444444444,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.2569444444444444,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.15,\n \"acc_stderr\": 0.03588702812826368,\n \ \ \"acc_norm\": 0.15,\n \"acc_norm_stderr\": 0.03588702812826368\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.34,\n \"acc_stderr\": 0.04760952285695236,\n \"acc_norm\": 0.34,\n\ \ \"acc_norm_stderr\": 0.04760952285695236\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.24277456647398843,\n\ \ \"acc_stderr\": 0.0326926380614177,\n \"acc_norm\": 0.24277456647398843,\n\ \ \"acc_norm_stderr\": 0.0326926380614177\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.042801058373643966,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.042801058373643966\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n\ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.30638297872340425,\n \"acc_stderr\": 0.030135906478517563,\n\ \ \"acc_norm\": 0.30638297872340425,\n \"acc_norm_stderr\": 0.030135906478517563\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.21929824561403508,\n\ \ \"acc_stderr\": 0.03892431106518753,\n \"acc_norm\": 0.21929824561403508,\n\ \ \"acc_norm_stderr\": 0.03892431106518753\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.30344827586206896,\n \"acc_stderr\": 0.038312260488503336,\n\ \ \"acc_norm\": 0.30344827586206896,\n \"acc_norm_stderr\": 0.038312260488503336\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2777777777777778,\n \"acc_stderr\": 0.023068188848261107,\n \"\ acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.023068188848261107\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.2619047619047619,\n\ \ \"acc_stderr\": 0.03932537680392871,\n \"acc_norm\": 0.2619047619047619,\n\ \ \"acc_norm_stderr\": 0.03932537680392871\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.25806451612903225,\n\ \ \"acc_stderr\": 0.02489246917246284,\n \"acc_norm\": 0.25806451612903225,\n\ \ \"acc_norm_stderr\": 0.02489246917246284\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.30049261083743845,\n \"acc_stderr\": 0.03225799476233484,\n\ \ \"acc_norm\": 0.30049261083743845,\n \"acc_norm_stderr\": 0.03225799476233484\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.30303030303030304,\n \"acc_stderr\": 0.035886248000917075,\n\ \ \"acc_norm\": 0.30303030303030304,\n \"acc_norm_stderr\": 0.035886248000917075\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.35858585858585856,\n \"acc_stderr\": 0.03416903640391521,\n \"\ acc_norm\": 0.35858585858585856,\n \"acc_norm_stderr\": 0.03416903640391521\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.31088082901554404,\n \"acc_stderr\": 0.033403619062765885,\n\ \ \"acc_norm\": 0.31088082901554404,\n \"acc_norm_stderr\": 0.033403619062765885\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.358974358974359,\n \"acc_stderr\": 0.024321738484602357,\n \ \ \"acc_norm\": 0.358974358974359,\n \"acc_norm_stderr\": 0.024321738484602357\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.26296296296296295,\n \"acc_stderr\": 0.02684205787383371,\n \ \ \"acc_norm\": 0.26296296296296295,\n \"acc_norm_stderr\": 0.02684205787383371\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.2184873949579832,\n \"acc_stderr\": 0.026841514322958955,\n\ \ \"acc_norm\": 0.2184873949579832,\n \"acc_norm_stderr\": 0.026841514322958955\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.03631329803969653,\n \"acc_norm\"\ : 0.271523178807947,\n \"acc_norm_stderr\": 0.03631329803969653\n },\n\ \ \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\": 0.3339449541284404,\n\ \ \"acc_stderr\": 0.020220554196736403,\n \"acc_norm\": 0.3339449541284404,\n\ \ \"acc_norm_stderr\": 0.020220554196736403\n },\n \"harness\|hendrycksTest-high_school_statistics\|5\"\ : {\n \"acc\": 0.2824074074074074,\n \"acc_stderr\": 0.030701372111510927,\n\ \ \"acc_norm\": 0.2824074074074074,\n \"acc_norm_stderr\": 0.030701372111510927\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.25980392156862747,\n \"acc_stderr\": 0.030778554678693264,\n \"\ acc_norm\": 0.25980392156862747,\n \"acc_norm_stderr\": 0.030778554678693264\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n \ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.1031390134529148,\n\ \ \"acc_stderr\": 0.020412564289839272,\n \"acc_norm\": 0.1031390134529148,\n\ \ \"acc_norm_stderr\": 0.020412564289839272\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.2366412213740458,\n \"acc_stderr\": 0.037276735755969174,\n\ \ \"acc_norm\": 0.2366412213740458,\n \"acc_norm_stderr\": 0.037276735755969174\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.35537190082644626,\n \"acc_stderr\": 0.04369236326573981,\n \"\ acc_norm\": 0.35537190082644626,\n \"acc_norm_stderr\": 0.04369236326573981\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.2883435582822086,\n \"acc_stderr\": 0.035590395316173425,\n\ \ \"acc_norm\": 0.2883435582822086,\n \"acc_norm_stderr\": 0.035590395316173425\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.23214285714285715,\n\ \ \"acc_stderr\": 0.04007341809755807,\n \"acc_norm\": 0.23214285714285715,\n\ \ \"acc_norm_stderr\": 0.04007341809755807\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.3786407766990291,\n \"acc_stderr\": 0.04802694698258972,\n\ \ \"acc_norm\": 0.3786407766990291,\n \"acc_norm_stderr\": 0.04802694698258972\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.2606837606837607,\n\ \ \"acc_stderr\": 0.028760348956523414,\n \"acc_norm\": 0.2606837606837607,\n\ \ \"acc_norm_stderr\": 0.028760348956523414\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.19,\n \"acc_stderr\": 0.03942772444036623,\n \ \ \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.03942772444036623\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.20434227330779056,\n\ \ \"acc_stderr\": 0.0144191239809319,\n \"acc_norm\": 0.20434227330779056,\n\ \ \"acc_norm_stderr\": 0.0144191239809319\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.2976878612716763,\n \"acc_stderr\": 0.024617055388677,\n\ \ \"acc_norm\": 0.2976878612716763,\n \"acc_norm_stderr\": 0.024617055388677\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217889,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217889\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.25163398692810457,\n \"acc_stderr\": 0.024848018263875195,\n\ \ \"acc_norm\": 0.25163398692810457,\n \"acc_norm_stderr\": 0.024848018263875195\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.3247588424437299,\n\ \ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.3247588424437299,\n\ \ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.023132376234543346,\n\ \ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.023132376234543346\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.2624113475177305,\n \"acc_stderr\": 0.026244920349843014,\n \ \ \"acc_norm\": 0.2624113475177305,\n \"acc_norm_stderr\": 0.026244920349843014\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.24445893089960888,\n\ \ \"acc_stderr\": 0.010976425013113893,\n \"acc_norm\": 0.24445893089960888,\n\ \ \"acc_norm_stderr\": 0.010976425013113893\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.26838235294117646,\n \"acc_stderr\": 0.02691748122437722,\n\ \ \"acc_norm\": 0.26838235294117646,\n \"acc_norm_stderr\": 0.02691748122437722\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.2434640522875817,\n \"acc_stderr\": 0.017362473762146623,\n \ \ \"acc_norm\": 0.2434640522875817,\n \"acc_norm_stderr\": 0.017362473762146623\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.2,\n\ \ \"acc_stderr\": 0.03831305140884603,\n \"acc_norm\": 0.2,\n \ \ \"acc_norm_stderr\": 0.03831305140884603\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.3224489795918367,\n \"acc_stderr\": 0.029923100563683903,\n\ \ \"acc_norm\": 0.3224489795918367,\n \"acc_norm_stderr\": 0.029923100563683903\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.24378109452736318,\n\ \ \"acc_stderr\": 0.03036049015401465,\n \"acc_norm\": 0.24378109452736318,\n\ \ \"acc_norm_stderr\": 0.03036049015401465\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.21686746987951808,\n\ \ \"acc_stderr\": 0.03208284450356365,\n \"acc_norm\": 0.21686746987951808,\n\ \ \"acc_norm_stderr\": 0.03208284450356365\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.29239766081871343,\n \"acc_stderr\": 0.034886477134579215,\n\ \ \"acc_norm\": 0.29239766081871343,\n \"acc_norm_stderr\": 0.034886477134579215\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757449,\n \"mc2\": 0.39429285512218326,\n\ \ \"mc2_stderr\": 0.01421822540176183\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.5461720599842147,\n \"acc_stderr\": 0.013992441563707063\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.006065200909780136,\n \ \ \"acc_stderr\": 0.00213867030146048\n }\n}\n```" repo_url: https://huggingface.co/LordNoah/Alpaca_spin_tuned_gpt2_large leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|arc:challenge\|25_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-22T13-42-11.763277.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|gsm8k\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hellaswag\|10_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T13-42-11.763277.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-22T13-42-11.763277.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '/details_harness\|winogrande\|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-22T13-42-11.763277.parquet' - config_name: results data_files: - split: 2024_01_22T13_42_11.763277 path: - results_2024-01-22T13-42-11.763277.parquet - split: latest path: - results_2024-01-22T13-42-11.763277.parquet --- # Dataset Card for Evaluation run of LordNoah/Alpaca_spin_tuned_gpt2_large <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [LordNoah/Alpaca_spin_tuned_gpt2_large](https://huggingface.co/LordNoah/Alpaca_spin_tuned_gpt2_large) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-22T13:42:11.763277](https://huggingface.co/datasets/open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large/blob/main/results_2024-01-22T13-42-11.763277.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.27225604584142943, "acc_stderr": 0.03141590282455585, "acc_norm": 0.27399653003630087, "acc_norm_stderr": 0.03221603447267582, "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757449, "mc2": 0.39429285512218326, "mc2_stderr": 0.01421822540176183 }, "harness\|arc:challenge\|25": { "acc": 0.2568259385665529, "acc_stderr": 0.0127669237941168, "acc_norm": 0.2790102389078498, "acc_norm_stderr": 0.013106784883601341 }, "harness\|hellaswag\|10": { "acc": 0.36297550288787095, "acc_stderr": 0.004798751281560822, "acc_norm": 0.45120493925512845, "acc_norm_stderr": 0.004965963647210318 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.24444444444444444, "acc_stderr": 0.037125378336148665, "acc_norm": 0.24444444444444444, "acc_norm_stderr": 0.037125378336148665 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.3026315789473684, "acc_stderr": 0.03738520676119667, "acc_norm": 0.3026315789473684, "acc_norm_stderr": 0.03738520676119667 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.3433962264150943, "acc_stderr": 0.02922452646912479, "acc_norm": 0.3433962264150943, "acc_norm_stderr": 0.02922452646912479 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.15, "acc_stderr": 0.03588702812826368, "acc_norm": 0.15, "acc_norm_stderr": 0.03588702812826368 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.24277456647398843, "acc_stderr": 0.0326926380614177, "acc_norm": 0.24277456647398843, "acc_norm_stderr": 0.0326926380614177 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.042801058373643966, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.042801058373643966 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.30638297872340425, "acc_stderr": 0.030135906478517563, "acc_norm": 0.30638297872340425, "acc_norm_stderr": 0.030135906478517563 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.21929824561403508, "acc_stderr": 0.03892431106518753, "acc_norm": 0.21929824561403508, "acc_norm_stderr": 0.03892431106518753 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.30344827586206896, "acc_stderr": 0.038312260488503336, "acc_norm": 0.30344827586206896, "acc_norm_stderr": 0.038312260488503336 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.023068188848261107, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.023068188848261107 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.2619047619047619, "acc_stderr": 0.03932537680392871, "acc_norm": 0.2619047619047619, "acc_norm_stderr": 0.03932537680392871 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.25806451612903225, "acc_stderr": 0.02489246917246284, "acc_norm": 0.25806451612903225, "acc_norm_stderr": 0.02489246917246284 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.30049261083743845, "acc_stderr": 0.03225799476233484, "acc_norm": 0.30049261083743845, "acc_norm_stderr": 0.03225799476233484 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.30303030303030304, "acc_stderr": 0.035886248000917075, "acc_norm": 0.30303030303030304, "acc_norm_stderr": 0.035886248000917075 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.35858585858585856, "acc_stderr": 0.03416903640391521, "acc_norm": 0.35858585858585856, "acc_norm_stderr": 0.03416903640391521 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.31088082901554404, "acc_stderr": 0.033403619062765885, "acc_norm": 0.31088082901554404, "acc_norm_stderr": 0.033403619062765885 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.358974358974359, "acc_stderr": 0.024321738484602357, "acc_norm": 0.358974358974359, "acc_norm_stderr": 0.024321738484602357 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.26296296296296295, "acc_stderr": 0.02684205787383371, "acc_norm": 0.26296296296296295, "acc_norm_stderr": 0.02684205787383371 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.2184873949579832, "acc_stderr": 0.026841514322958955, "acc_norm": 0.2184873949579832, "acc_norm_stderr": 0.026841514322958955 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.271523178807947, "acc_stderr": 0.03631329803969653, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.03631329803969653 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.3339449541284404, "acc_stderr": 0.020220554196736403, "acc_norm": 0.3339449541284404, "acc_norm_stderr": 0.020220554196736403 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.2824074074074074, "acc_stderr": 0.030701372111510927, "acc_norm": 0.2824074074074074, "acc_norm_stderr": 0.030701372111510927 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.25980392156862747, "acc_stderr": 0.030778554678693264, "acc_norm": 0.25980392156862747, "acc_norm_stderr": 0.030778554678693264 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.1031390134529148, "acc_stderr": 0.020412564289839272, "acc_norm": 0.1031390134529148, "acc_norm_stderr": 0.020412564289839272 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.2366412213740458, "acc_stderr": 0.037276735755969174, "acc_norm": 0.2366412213740458, "acc_norm_stderr": 0.037276735755969174 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.35537190082644626, "acc_stderr": 0.04369236326573981, "acc_norm": 0.35537190082644626, "acc_norm_stderr": 0.04369236326573981 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.25, "acc_stderr": 0.04186091791394607, "acc_norm": 0.25, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.2883435582822086, "acc_stderr": 0.035590395316173425, "acc_norm": 0.2883435582822086, "acc_norm_stderr": 0.035590395316173425 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.23214285714285715, "acc_stderr": 0.04007341809755807, "acc_norm": 0.23214285714285715, "acc_norm_stderr": 0.04007341809755807 }, "harness\|hendrycksTest-management\|5": { "acc": 0.3786407766990291, "acc_stderr": 0.04802694698258972, "acc_norm": 0.3786407766990291, "acc_norm_stderr": 0.04802694698258972 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.2606837606837607, "acc_stderr": 0.028760348956523414, "acc_norm": 0.2606837606837607, "acc_norm_stderr": 0.028760348956523414 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.19, "acc_stderr": 0.03942772444036623, "acc_norm": 0.19, "acc_norm_stderr": 0.03942772444036623 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.20434227330779056, "acc_stderr": 0.0144191239809319, "acc_norm": 0.20434227330779056, "acc_norm_stderr": 0.0144191239809319 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.2976878612716763, "acc_stderr": 0.024617055388677, "acc_norm": 0.2976878612716763, "acc_norm_stderr": 0.024617055388677 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2424581005586592, "acc_stderr": 0.014333522059217889, "acc_norm": 0.2424581005586592, "acc_norm_stderr": 0.014333522059217889 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.25163398692810457, "acc_stderr": 0.024848018263875195, "acc_norm": 0.25163398692810457, "acc_norm_stderr": 0.024848018263875195 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.3247588424437299, "acc_stderr": 0.026596782287697043, "acc_norm": 0.3247588424437299, "acc_norm_stderr": 0.026596782287697043 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.2222222222222222, "acc_stderr": 0.023132376234543346, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.023132376234543346 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.2624113475177305, "acc_stderr": 0.026244920349843014, "acc_norm": 0.2624113475177305, "acc_norm_stderr": 0.026244920349843014 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.24445893089960888, "acc_stderr": 0.010976425013113893, "acc_norm": 0.24445893089960888, "acc_norm_stderr": 0.010976425013113893 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.26838235294117646, "acc_stderr": 0.02691748122437722, "acc_norm": 0.26838235294117646, "acc_norm_stderr": 0.02691748122437722 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.2434640522875817, "acc_stderr": 0.017362473762146623, "acc_norm": 0.2434640522875817, "acc_norm_stderr": 0.017362473762146623 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.2, "acc_stderr": 0.03831305140884603, "acc_norm": 0.2, "acc_norm_stderr": 0.03831305140884603 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.3224489795918367, "acc_stderr": 0.029923100563683903, "acc_norm": 0.3224489795918367, "acc_norm_stderr": 0.029923100563683903 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.24378109452736318, "acc_stderr": 0.03036049015401465, "acc_norm": 0.24378109452736318, "acc_norm_stderr": 0.03036049015401465 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.21686746987951808, "acc_stderr": 0.03208284450356365, "acc_norm": 0.21686746987951808, "acc_norm_stderr": 0.03208284450356365 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.29239766081871343, "acc_stderr": 0.034886477134579215, "acc_norm": 0.29239766081871343, "acc_norm_stderr": 0.034886477134579215 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757449, "mc2": 0.39429285512218326, "mc2_stderr": 0.01421822540176183 }, "harness\|winogrande\|5": { "acc": 0.5461720599842147, "acc_stderr": 0.013992441563707063 }, "harness\|gsm8k\|5": { "acc": 0.006065200909780136, "acc_stderr": 0.00213867030146048 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. 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open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B	--- pretty_name: Evaluation run of vicgalleorg/TruthfulQwen1.5-1.8B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [vicgalleorg/TruthfulQwen1.5-1.8B](https://huggingface.co/vicgalleorg/TruthfulQwen1.5-1.8B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-04T13:58:06.789352](https://huggingface.co/datasets/open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B/blob/main/results_2024-03-04T13-58-06.789352.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.4680075333485934,\n\ \ \"acc_stderr\": 0.03457829883276736,\n \"acc_norm\": 0.4708825754058936,\n\ \ \"acc_norm_stderr\": 0.03529767780244664,\n \"mc1\": 0.2766217870257038,\n\ \ \"mc1_stderr\": 0.015659605755326923,\n \"mc2\": 0.4058019851571796,\n\ \ \"mc2_stderr\": 0.014539846563223038\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.36006825938566556,\n \"acc_stderr\": 0.014027516814585184,\n\ \ \"acc_norm\": 0.3873720136518771,\n \"acc_norm_stderr\": 0.014235872487909872\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.4622585142401912,\n\ \ \"acc_stderr\": 0.00497554601895068,\n \"acc_norm\": 0.6135232025492929,\n\ \ \"acc_norm_stderr\": 0.004859467984155279\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.43703703703703706,\n\ \ \"acc_stderr\": 0.04284958639753399,\n \"acc_norm\": 0.43703703703703706,\n\ \ \"acc_norm_stderr\": 0.04284958639753399\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.47368421052631576,\n \"acc_stderr\": 0.04063302731486671,\n\ \ \"acc_norm\": 0.47368421052631576,\n \"acc_norm_stderr\": 0.04063302731486671\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.52,\n\ \ \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n \ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.5358490566037736,\n \"acc_stderr\": 0.030693675018458006,\n\ \ \"acc_norm\": 0.5358490566037736,\n \"acc_norm_stderr\": 0.030693675018458006\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.4236111111111111,\n\ \ \"acc_stderr\": 0.041321250197233685,\n \"acc_norm\": 0.4236111111111111,\n\ \ \"acc_norm_stderr\": 0.041321250197233685\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.46,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.4161849710982659,\n\ \ \"acc_stderr\": 0.03758517775404947,\n \"acc_norm\": 0.4161849710982659,\n\ \ \"acc_norm_stderr\": 0.03758517775404947\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.27450980392156865,\n \"acc_stderr\": 0.044405219061793275,\n\ \ \"acc_norm\": 0.27450980392156865,\n \"acc_norm_stderr\": 0.044405219061793275\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.59,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.59,\n\ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.4085106382978723,\n \"acc_stderr\": 0.03213418026701576,\n\ \ \"acc_norm\": 0.4085106382978723,\n \"acc_norm_stderr\": 0.03213418026701576\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2982456140350877,\n\ \ \"acc_stderr\": 0.04303684033537314,\n \"acc_norm\": 0.2982456140350877,\n\ \ \"acc_norm_stderr\": 0.04303684033537314\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.4896551724137931,\n \"acc_stderr\": 0.041657747757287644,\n\ \ \"acc_norm\": 0.4896551724137931,\n \"acc_norm_stderr\": 0.041657747757287644\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.36243386243386244,\n \"acc_stderr\": 0.02475747390275205,\n \"\ acc_norm\": 0.36243386243386244,\n \"acc_norm_stderr\": 0.02475747390275205\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.23809523809523808,\n\ \ \"acc_stderr\": 0.03809523809523812,\n \"acc_norm\": 0.23809523809523808,\n\ \ \"acc_norm_stderr\": 0.03809523809523812\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.5419354838709678,\n\ \ \"acc_stderr\": 0.028343787250540632,\n \"acc_norm\": 0.5419354838709678,\n\ \ \"acc_norm_stderr\": 0.028343787250540632\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.3645320197044335,\n \"acc_stderr\": 0.033864057460620905,\n\ \ \"acc_norm\": 0.3645320197044335,\n \"acc_norm_stderr\": 0.033864057460620905\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \"acc_norm\"\ : 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6,\n \"acc_stderr\": 0.038254602783800246,\n \ \ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.038254602783800246\n \ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.5555555555555556,\n \"acc_stderr\": 0.035402943770953675,\n \"\ acc_norm\": 0.5555555555555556,\n \"acc_norm_stderr\": 0.035402943770953675\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.5647668393782384,\n \"acc_stderr\": 0.03578038165008586,\n\ \ \"acc_norm\": 0.5647668393782384,\n \"acc_norm_stderr\": 0.03578038165008586\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.4256410256410256,\n \"acc_stderr\": 0.02506909438729654,\n \ \ \"acc_norm\": 0.4256410256410256,\n \"acc_norm_stderr\": 0.02506909438729654\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.31851851851851853,\n \"acc_stderr\": 0.028406533090608463,\n \ \ \"acc_norm\": 0.31851851851851853,\n \"acc_norm_stderr\": 0.028406533090608463\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.39915966386554624,\n \"acc_stderr\": 0.03181110032413925,\n\ \ \"acc_norm\": 0.39915966386554624,\n \"acc_norm_stderr\": 0.03181110032413925\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360384,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360384\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.5944954128440367,\n \"acc_stderr\": 0.021050997991896837,\n \"\ acc_norm\": 0.5944954128440367,\n \"acc_norm_stderr\": 0.021050997991896837\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.2824074074074074,\n \"acc_stderr\": 0.030701372111510923,\n \"\ acc_norm\": 0.2824074074074074,\n \"acc_norm_stderr\": 0.030701372111510923\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.5049019607843137,\n \"acc_stderr\": 0.03509143375606786,\n \"\ acc_norm\": 0.5049019607843137,\n \"acc_norm_stderr\": 0.03509143375606786\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.6075949367088608,\n \"acc_stderr\": 0.03178471874564729,\n \ \ \"acc_norm\": 0.6075949367088608,\n \"acc_norm_stderr\": 0.03178471874564729\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.5336322869955157,\n\ \ \"acc_stderr\": 0.03348180017060306,\n \"acc_norm\": 0.5336322869955157,\n\ \ \"acc_norm_stderr\": 0.03348180017060306\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.5725190839694656,\n \"acc_stderr\": 0.04338920305792401,\n\ \ \"acc_norm\": 0.5725190839694656,\n \"acc_norm_stderr\": 0.04338920305792401\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7107438016528925,\n \"acc_stderr\": 0.041391127276354626,\n \"\ acc_norm\": 0.7107438016528925,\n \"acc_norm_stderr\": 0.041391127276354626\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.5092592592592593,\n\ \ \"acc_stderr\": 0.04832853553437056,\n \"acc_norm\": 0.5092592592592593,\n\ \ \"acc_norm_stderr\": 0.04832853553437056\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.4601226993865031,\n \"acc_stderr\": 0.03915857291436972,\n\ \ \"acc_norm\": 0.4601226993865031,\n \"acc_norm_stderr\": 0.03915857291436972\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.32142857142857145,\n\ \ \"acc_stderr\": 0.04432804055291519,\n \"acc_norm\": 0.32142857142857145,\n\ \ \"acc_norm_stderr\": 0.04432804055291519\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.6504854368932039,\n \"acc_stderr\": 0.047211885060971716,\n\ \ \"acc_norm\": 0.6504854368932039,\n \"acc_norm_stderr\": 0.047211885060971716\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.7649572649572649,\n\ \ \"acc_stderr\": 0.027778835904935444,\n \"acc_norm\": 0.7649572649572649,\n\ \ \"acc_norm_stderr\": 0.027778835904935444\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.55,\n \"acc_stderr\": 0.04999999999999998,\n \ \ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.04999999999999998\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.6181353767560664,\n\ \ \"acc_stderr\": 0.017373732736677583,\n \"acc_norm\": 0.6181353767560664,\n\ \ \"acc_norm_stderr\": 0.017373732736677583\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.5289017341040463,\n \"acc_stderr\": 0.026874085883518348,\n\ \ \"acc_norm\": 0.5289017341040463,\n \"acc_norm_stderr\": 0.026874085883518348\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217892,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217892\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.5849673202614379,\n \"acc_stderr\": 0.028213504177824103,\n\ \ \"acc_norm\": 0.5849673202614379,\n \"acc_norm_stderr\": 0.028213504177824103\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.49517684887459806,\n\ \ \"acc_stderr\": 0.02839677044411129,\n \"acc_norm\": 0.49517684887459806,\n\ \ \"acc_norm_stderr\": 0.02839677044411129\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.4691358024691358,\n \"acc_stderr\": 0.027767689606833925,\n\ \ \"acc_norm\": 0.4691358024691358,\n \"acc_norm_stderr\": 0.027767689606833925\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.37943262411347517,\n \"acc_stderr\": 0.028947338851614105,\n \ \ \"acc_norm\": 0.37943262411347517,\n \"acc_norm_stderr\": 0.028947338851614105\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.3683181225554107,\n\ \ \"acc_stderr\": 0.012319403369564637,\n \"acc_norm\": 0.3683181225554107,\n\ \ \"acc_norm_stderr\": 0.012319403369564637\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.39705882352941174,\n \"acc_stderr\": 0.02972215209928007,\n\ \ \"acc_norm\": 0.39705882352941174,\n \"acc_norm_stderr\": 0.02972215209928007\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.42483660130718953,\n \"acc_stderr\": 0.019997973035458333,\n \ \ \"acc_norm\": 0.42483660130718953,\n \"acc_norm_stderr\": 0.019997973035458333\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6,\n\ \ \"acc_stderr\": 0.0469237132203465,\n \"acc_norm\": 0.6,\n \ \ \"acc_norm_stderr\": 0.0469237132203465\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.49795918367346936,\n \"acc_stderr\": 0.0320089533497105,\n\ \ \"acc_norm\": 0.49795918367346936,\n \"acc_norm_stderr\": 0.0320089533497105\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.6169154228855721,\n\ \ \"acc_stderr\": 0.0343751933733825,\n \"acc_norm\": 0.6169154228855721,\n\ \ \"acc_norm_stderr\": 0.0343751933733825\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.42771084337349397,\n\ \ \"acc_stderr\": 0.038515976837185335,\n \"acc_norm\": 0.42771084337349397,\n\ \ \"acc_norm_stderr\": 0.038515976837185335\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.5847953216374269,\n \"acc_stderr\": 0.03779275945503201,\n\ \ \"acc_norm\": 0.5847953216374269,\n \"acc_norm_stderr\": 0.03779275945503201\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.2766217870257038,\n\ \ \"mc1_stderr\": 0.015659605755326923,\n \"mc2\": 0.4058019851571796,\n\ \ \"mc2_stderr\": 0.014539846563223038\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6037884767166535,\n \"acc_stderr\": 0.013746404157154946\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.3411675511751327,\n \ \ \"acc_stderr\": 0.01305911193583148\n }\n}\n```" repo_url: https://huggingface.co/vicgalleorg/TruthfulQwen1.5-1.8B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|arc:challenge\|25_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-04T13-58-06.789352.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|gsm8k\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hellaswag\|10_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-04T13-58-06.789352.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-04T13-58-06.789352.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '/details_harness\|winogrande\|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-04T13-58-06.789352.parquet' - config_name: results data_files: - split: 2024_03_04T13_58_06.789352 path: - results_2024-03-04T13-58-06.789352.parquet - split: latest path: - results_2024-03-04T13-58-06.789352.parquet --- # Dataset Card for Evaluation run of vicgalleorg/TruthfulQwen1.5-1.8B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [vicgalleorg/TruthfulQwen1.5-1.8B](https://huggingface.co/vicgalleorg/TruthfulQwen1.5-1.8B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-04T13:58:06.789352](https://huggingface.co/datasets/open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B/blob/main/results_2024-03-04T13-58-06.789352.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.4680075333485934, "acc_stderr": 0.03457829883276736, "acc_norm": 0.4708825754058936, "acc_norm_stderr": 0.03529767780244664, "mc1": 0.2766217870257038, "mc1_stderr": 0.015659605755326923, "mc2": 0.4058019851571796, "mc2_stderr": 0.014539846563223038 }, "harness\|arc:challenge\|25": { "acc": 0.36006825938566556, "acc_stderr": 0.014027516814585184, "acc_norm": 0.3873720136518771, "acc_norm_stderr": 0.014235872487909872 }, "harness\|hellaswag\|10": { "acc": 0.4622585142401912, "acc_stderr": 0.00497554601895068, "acc_norm": 0.6135232025492929, "acc_norm_stderr": 0.004859467984155279 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.43703703703703706, "acc_stderr": 0.04284958639753399, "acc_norm": 0.43703703703703706, "acc_norm_stderr": 0.04284958639753399 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.47368421052631576, "acc_stderr": 0.04063302731486671, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.04063302731486671 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.5358490566037736, "acc_stderr": 0.030693675018458006, "acc_norm": 0.5358490566037736, "acc_norm_stderr": 0.030693675018458006 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.4236111111111111, "acc_stderr": 0.041321250197233685, "acc_norm": 0.4236111111111111, "acc_norm_stderr": 0.041321250197233685 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.4161849710982659, "acc_stderr": 0.03758517775404947, "acc_norm": 0.4161849710982659, "acc_norm_stderr": 0.03758517775404947 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.27450980392156865, "acc_stderr": 0.044405219061793275, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.044405219061793275 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.4085106382978723, "acc_stderr": 0.03213418026701576, "acc_norm": 0.4085106382978723, "acc_norm_stderr": 0.03213418026701576 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2982456140350877, "acc_stderr": 0.04303684033537314, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.04303684033537314 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.4896551724137931, "acc_stderr": 0.041657747757287644, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.041657747757287644 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.36243386243386244, "acc_stderr": 0.02475747390275205, "acc_norm": 0.36243386243386244, "acc_norm_stderr": 0.02475747390275205 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.23809523809523808, "acc_stderr": 0.03809523809523812, "acc_norm": 0.23809523809523808, "acc_norm_stderr": 0.03809523809523812 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.5419354838709678, "acc_stderr": 0.028343787250540632, "acc_norm": 0.5419354838709678, "acc_norm_stderr": 0.028343787250540632 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.3645320197044335, "acc_stderr": 0.033864057460620905, "acc_norm": 0.3645320197044335, "acc_norm_stderr": 0.033864057460620905 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6, "acc_stderr": 0.038254602783800246, "acc_norm": 0.6, "acc_norm_stderr": 0.038254602783800246 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.5555555555555556, "acc_stderr": 0.035402943770953675, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.035402943770953675 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.5647668393782384, "acc_stderr": 0.03578038165008586, "acc_norm": 0.5647668393782384, "acc_norm_stderr": 0.03578038165008586 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.4256410256410256, "acc_stderr": 0.02506909438729654, "acc_norm": 0.4256410256410256, "acc_norm_stderr": 0.02506909438729654 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.31851851851851853, "acc_stderr": 0.028406533090608463, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.028406533090608463 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.39915966386554624, "acc_stderr": 0.03181110032413925, "acc_norm": 0.39915966386554624, "acc_norm_stderr": 0.03181110032413925 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.26490066225165565, "acc_stderr": 0.03603038545360384, "acc_norm": 0.26490066225165565, "acc_norm_stderr": 0.03603038545360384 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.5944954128440367, "acc_stderr": 0.021050997991896837, "acc_norm": 0.5944954128440367, "acc_norm_stderr": 0.021050997991896837 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.2824074074074074, "acc_stderr": 0.030701372111510923, "acc_norm": 0.2824074074074074, "acc_norm_stderr": 0.030701372111510923 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.5049019607843137, "acc_stderr": 0.03509143375606786, "acc_norm": 0.5049019607843137, "acc_norm_stderr": 0.03509143375606786 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.6075949367088608, "acc_stderr": 0.03178471874564729, "acc_norm": 0.6075949367088608, "acc_norm_stderr": 0.03178471874564729 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.5336322869955157, "acc_stderr": 0.03348180017060306, "acc_norm": 0.5336322869955157, "acc_norm_stderr": 0.03348180017060306 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.5725190839694656, "acc_stderr": 0.04338920305792401, "acc_norm": 0.5725190839694656, "acc_norm_stderr": 0.04338920305792401 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7107438016528925, "acc_stderr": 0.041391127276354626, "acc_norm": 0.7107438016528925, "acc_norm_stderr": 0.041391127276354626 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.5092592592592593, "acc_stderr": 0.04832853553437056, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.04832853553437056 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.4601226993865031, "acc_stderr": 0.03915857291436972, "acc_norm": 0.4601226993865031, "acc_norm_stderr": 0.03915857291436972 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.32142857142857145, "acc_stderr": 0.04432804055291519, "acc_norm": 0.32142857142857145, "acc_norm_stderr": 0.04432804055291519 }, "harness\|hendrycksTest-management\|5": { "acc": 0.6504854368932039, "acc_stderr": 0.047211885060971716, "acc_norm": 0.6504854368932039, "acc_norm_stderr": 0.047211885060971716 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.7649572649572649, "acc_stderr": 0.027778835904935444, "acc_norm": 0.7649572649572649, "acc_norm_stderr": 0.027778835904935444 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.55, "acc_stderr": 0.04999999999999998, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999998 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.6181353767560664, "acc_stderr": 0.017373732736677583, "acc_norm": 0.6181353767560664, "acc_norm_stderr": 0.017373732736677583 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.5289017341040463, "acc_stderr": 0.026874085883518348, "acc_norm": 0.5289017341040463, "acc_norm_stderr": 0.026874085883518348 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2424581005586592, "acc_stderr": 0.014333522059217892, "acc_norm": 0.2424581005586592, "acc_norm_stderr": 0.014333522059217892 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.5849673202614379, "acc_stderr": 0.028213504177824103, "acc_norm": 0.5849673202614379, "acc_norm_stderr": 0.028213504177824103 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.49517684887459806, "acc_stderr": 0.02839677044411129, "acc_norm": 0.49517684887459806, "acc_norm_stderr": 0.02839677044411129 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.4691358024691358, "acc_stderr": 0.027767689606833925, "acc_norm": 0.4691358024691358, "acc_norm_stderr": 0.027767689606833925 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.37943262411347517, "acc_stderr": 0.028947338851614105, "acc_norm": 0.37943262411347517, "acc_norm_stderr": 0.028947338851614105 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.3683181225554107, "acc_stderr": 0.012319403369564637, "acc_norm": 0.3683181225554107, "acc_norm_stderr": 0.012319403369564637 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.39705882352941174, "acc_stderr": 0.02972215209928007, "acc_norm": 0.39705882352941174, "acc_norm_stderr": 0.02972215209928007 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.42483660130718953, "acc_stderr": 0.019997973035458333, "acc_norm": 0.42483660130718953, "acc_norm_stderr": 0.019997973035458333 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6, "acc_stderr": 0.0469237132203465, "acc_norm": 0.6, "acc_norm_stderr": 0.0469237132203465 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.49795918367346936, "acc_stderr": 0.0320089533497105, "acc_norm": 0.49795918367346936, "acc_norm_stderr": 0.0320089533497105 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.6169154228855721, "acc_stderr": 0.0343751933733825, "acc_norm": 0.6169154228855721, "acc_norm_stderr": 0.0343751933733825 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.42771084337349397, "acc_stderr": 0.038515976837185335, "acc_norm": 0.42771084337349397, "acc_norm_stderr": 0.038515976837185335 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.5847953216374269, "acc_stderr": 0.03779275945503201, "acc_norm": 0.5847953216374269, "acc_norm_stderr": 0.03779275945503201 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.2766217870257038, "mc1_stderr": 0.015659605755326923, "mc2": 0.4058019851571796, "mc2_stderr": 0.014539846563223038 }, "harness\|winogrande\|5": { "acc": 0.6037884767166535, "acc_stderr": 0.013746404157154946 }, "harness\|gsm8k\|5": { "acc": 0.3411675511751327, "acc_stderr": 0.01305911193583148 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
luna-code/sqlmodel	--- dataset_info: features: - name: prompt dtype: string - name: completion dtype: string - name: api dtype: string splits: - name: train num_bytes: 2894322 num_examples: 1663 - name: test num_bytes: 92483 num_examples: 44 download_size: 450555 dataset_size: 2986805 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
huggingartists/booker	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/booker" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.782002 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/fb0d7cebfd97c76d99f1015b6ddc0e55.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/booker"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Booker</div> <a href="https://genius.com/artists/booker"> <div style="text-align: center; font-size: 14px;">@booker</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/booker). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/booker") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|196\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/booker") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)
blabble-io/libritts	--- license: cc-by-4.0 task_categories: - text-to-speech language: - en size_categories: - 10K<n<100K configs: - config_name: dev data_files: - split: dev.clean path: "data/dev.clean/dev.clean.parquet" - config_name: clean data_files: - split: dev.clean path: "data/dev.clean/dev.clean.parquet" - split: test.clean path: "data/test.clean/test.clean.parquet" - split: train.clean.100 path: "data/train.clean.100/train.clean.100.parquet" - split: train.clean.360 path: "data/train.clean.360/train.clean.360.parquet" - config_name: other data_files: - split: dev.other path: "data/dev.other/dev.other.parquet" - split: test.other path: "data/test.other/test.other.parquet" - split: train.other.500 path: "data/train.other.500/train.other.500.parquet" - config_name: all data_files: - split: dev.clean path: "data/dev.clean/dev.clean.parquet" - split: dev.other path: "data/dev.other/dev.other.parquet" - split: test.clean path: "data/test.clean/test.clean.parquet" - split: test.other path: "data/test.other/test.other.parquet" - split: train.clean.100 path: "data/train.clean.100/train.clean.100.parquet" - split: train.clean.360 path: "data/train.clean.360/train.clean.360.parquet" - split: train.other.500 path: "data/train.other.500/train.other.500.parquet" --- # Dataset Card for LibriTTS <!-- Provide a quick summary of the dataset. --> LibriTTS is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz sampling rate, prepared by Heiga Zen with the assistance of Google Speech and Google Brain team members. The LibriTTS corpus is designed for TTS research. It is derived from the original materials (mp3 audio files from LibriVox and text files from Project Gutenberg) of the LibriSpeech corpus. ## Overview This is the LibriTTS dataset, adapted for the `datasets` library. ## Usage ### Splits There are 7 splits (dots replace dashes from the original dataset, to comply with hf naming requirements): - dev.clean - dev.other - test.clean - test.other - train.clean.100 - train.clean.360 - train.other.500 ### Configurations There are 3 configurations, each which limits the splits the `load_dataset()` function will download. The default configuration is "all". - "dev": only the "dev.clean" split (good for testing the dataset quickly) - "clean": contains only "clean" splits - "other": contains only "other" splits - "all": contains only "all" splits ### Example Loading the `clean` config with only the `train.clean.360` split. ``` load_dataset("blabble-io/libritts", "clean", split="train.clean.100") ``` Streaming is also supported. ``` load_dataset("blabble-io/libritts", streaming=True) ``` ### Columns ``` { "audio": datasets.Audio(sampling_rate=24_000), "text_normalized": datasets.Value("string"), "text_original": datasets.Value("string"), "speaker_id": datasets.Value("string"), "path": datasets.Value("string"), "chapter_id": datasets.Value("string"), "id": datasets.Value("string"), } ``` ### Example Row ``` { 'audio': { 'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/5551a515e85b9e463062524539c2e1cb52ba32affe128dffd866db0205248bdd/LibriTTS/dev-clean/3081/166546/3081_166546_000028_000002.wav', 'array': ..., 'sampling_rate': 24000 }, 'text_normalized': 'How quickly he disappeared!"', 'text_original': 'How quickly he disappeared!"', 'speaker_id': '3081', 'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/5551a515e85b9e463062524539c2e1cb52ba32affe128dffd866db0205248bdd/LibriTTS/dev-clean/3081/166546/3081_166546_000028_000002.wav', 'chapter_id': '166546', 'id': '3081_166546_000028_000002' } ``` ## Dataset Details ### Dataset Description - License:* CC BY 4.0 ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Homepage: https://www.openslr.org/60/ - Paper: https://arxiv.org/abs/1904.02882 ## Citation <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> ``` @ARTICLE{Zen2019-kz, title = "{LibriTTS}: A corpus derived from {LibriSpeech} for text-to-speech", author = "Zen, Heiga and Dang, Viet and Clark, Rob and Zhang, Yu and Weiss, Ron J and Jia, Ye and Chen, Zhifeng and Wu, Yonghui", abstract = "This paper introduces a new speech corpus called ``LibriTTS'' designed for text-to-speech use. It is derived from the original audio and text materials of the LibriSpeech corpus, which has been used for training and evaluating automatic speech recognition systems. The new corpus inherits desired properties of the LibriSpeech corpus while addressing a number of issues which make LibriSpeech less than ideal for text-to-speech work. The released corpus consists of 585 hours of speech data at 24kHz sampling rate from 2,456 speakers and the corresponding texts. Experimental results show that neural end-to-end TTS models trained from the LibriTTS corpus achieved above 4.0 in mean opinion scores in naturalness in five out of six evaluation speakers. The corpus is freely available for download from http://www.openslr.org/60/.", month = apr, year = 2019, copyright = "http://arxiv.org/licenses/nonexclusive-distrib/1.0/", archivePrefix = "arXiv", primaryClass = "cs.SD", eprint = "1904.02882" } ```
BangumiBase/jigokushoujo	--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Jigoku Shoujo This is the image base of bangumi Jigoku Shoujo, we detected 89 characters, 6611 images in total. The full dataset is [here](all.zip). Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: \| # \| Images \| Download \| Preview 1 \| Preview 2 \| Preview 3 \| Preview 4 \| Preview 5 \| Preview 6 \| Preview 7 \| Preview 8 \| \|:------\|---------:\|:---------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\| \| 0 \| 538 \| [Download](0/dataset.zip) \| ![preview 1](0/preview_1.png) \| ![preview 2](0/preview_2.png) \| ![preview 3](0/preview_3.png) \| ![preview 4](0/preview_4.png) \| ![preview 5](0/preview_5.png) \| ![preview 6](0/preview_6.png) \| ![preview 7](0/preview_7.png) \| ![preview 8](0/preview_8.png) \| \| 1 \| 26 \| [Download](1/dataset.zip) \| ![preview 1](1/preview_1.png) \| ![preview 2](1/preview_2.png) \| ![preview 3](1/preview_3.png) \| ![preview 4](1/preview_4.png) \| ![preview 5](1/preview_5.png) \| ![preview 6](1/preview_6.png) \| ![preview 7](1/preview_7.png) \| ![preview 8](1/preview_8.png) \| \| 2 \| 26 \| [Download](2/dataset.zip) \| ![preview 1](2/preview_1.png) \| ![preview 2](2/preview_2.png) \| ![preview 3](2/preview_3.png) \| ![preview 4](2/preview_4.png) \| ![preview 5](2/preview_5.png) \| ![preview 6](2/preview_6.png) \| ![preview 7](2/preview_7.png) \| ![preview 8](2/preview_8.png) \| \| 3 \| 102 \| [Download](3/dataset.zip) \| ![preview 1](3/preview_1.png) \| ![preview 2](3/preview_2.png) \| ![preview 3](3/preview_3.png) \| ![preview 4](3/preview_4.png) \| ![preview 5](3/preview_5.png) \| ![preview 6](3/preview_6.png) \| ![preview 7](3/preview_7.png) \| ![preview 8](3/preview_8.png) \| \| 4 \| 52 \| [Download](4/dataset.zip) \| ![preview 1](4/preview_1.png) \| ![preview 2](4/preview_2.png) \| ![preview 3](4/preview_3.png) \| ![preview 4](4/preview_4.png) \| ![preview 5](4/preview_5.png) \| ![preview 6](4/preview_6.png) \| ![preview 7](4/preview_7.png) \| ![preview 8](4/preview_8.png) \| \| 5 \| 434 \| [Download](5/dataset.zip) \| ![preview 1](5/preview_1.png) \| ![preview 2](5/preview_2.png) \| ![preview 3](5/preview_3.png) \| ![preview 4](5/preview_4.png) \| ![preview 5](5/preview_5.png) \| ![preview 6](5/preview_6.png) \| ![preview 7](5/preview_7.png) \| ![preview 8](5/preview_8.png) \| \| 6 \| 637 \| [Download](6/dataset.zip) \| ![preview 1](6/preview_1.png) \| ![preview 2](6/preview_2.png) \| ![preview 3](6/preview_3.png) \| ![preview 4](6/preview_4.png) \| ![preview 5](6/preview_5.png) \| ![preview 6](6/preview_6.png) \| ![preview 7](6/preview_7.png) \| ![preview 8](6/preview_8.png) \| \| 7 \| 703 \| [Download](7/dataset.zip) \| ![preview 1](7/preview_1.png) \| ![preview 2](7/preview_2.png) \| ![preview 3](7/preview_3.png) \| ![preview 4](7/preview_4.png) \| ![preview 5](7/preview_5.png) \| ![preview 6](7/preview_6.png) \| ![preview 7](7/preview_7.png) \| ![preview 8](7/preview_8.png) \| \| 8 \| 102 \| [Download](8/dataset.zip) \| ![preview 1](8/preview_1.png) \| ![preview 2](8/preview_2.png) \| ![preview 3](8/preview_3.png) \| ![preview 4](8/preview_4.png) \| ![preview 5](8/preview_5.png) \| ![preview 6](8/preview_6.png) \| ![preview 7](8/preview_7.png) \| ![preview 8](8/preview_8.png) \| \| 9 \| 56 \| [Download](9/dataset.zip) \| ![preview 1](9/preview_1.png) \| ![preview 2](9/preview_2.png) \| ![preview 3](9/preview_3.png) \| ![preview 4](9/preview_4.png) \| ![preview 5](9/preview_5.png) \| ![preview 6](9/preview_6.png) \| ![preview 7](9/preview_7.png) \| ![preview 8](9/preview_8.png) \| \| 10 \| 50 \| [Download](10/dataset.zip) \| ![preview 1](10/preview_1.png) \| ![preview 2](10/preview_2.png) \| ![preview 3](10/preview_3.png) \| ![preview 4](10/preview_4.png) \| ![preview 5](10/preview_5.png) \| ![preview 6](10/preview_6.png) \| ![preview 7](10/preview_7.png) \| ![preview 8](10/preview_8.png) \| \| 11 \| 73 \| [Download](11/dataset.zip) \| ![preview 1](11/preview_1.png) \| ![preview 2](11/preview_2.png) \| ![preview 3](11/preview_3.png) \| ![preview 4](11/preview_4.png) \| ![preview 5](11/preview_5.png) \| ![preview 6](11/preview_6.png) \| ![preview 7](11/preview_7.png) \| ![preview 8](11/preview_8.png) \| \| 12 \| 35 \| [Download](12/dataset.zip) \| ![preview 1](12/preview_1.png) \| ![preview 2](12/preview_2.png) \| ![preview 3](12/preview_3.png) \| ![preview 4](12/preview_4.png) \| ![preview 5](12/preview_5.png) \| ![preview 6](12/preview_6.png) \| ![preview 7](12/preview_7.png) \| ![preview 8](12/preview_8.png) \| \| 13 \| 109 \| [Download](13/dataset.zip) \| ![preview 1](13/preview_1.png) \| ![preview 2](13/preview_2.png) \| ![preview 3](13/preview_3.png) \| ![preview 4](13/preview_4.png) \| ![preview 5](13/preview_5.png) \| ![preview 6](13/preview_6.png) \| ![preview 7](13/preview_7.png) \| ![preview 8](13/preview_8.png) \| \| 14 \| 211 \| [Download](14/dataset.zip) \| ![preview 1](14/preview_1.png) \| ![preview 2](14/preview_2.png) \| ![preview 3](14/preview_3.png) \| ![preview 4](14/preview_4.png) \| ![preview 5](14/preview_5.png) \| ![preview 6](14/preview_6.png) \| ![preview 7](14/preview_7.png) \| ![preview 8](14/preview_8.png) \| \| 15 \| 127 \| [Download](15/dataset.zip) \| ![preview 1](15/preview_1.png) \| ![preview 2](15/preview_2.png) \| ![preview 3](15/preview_3.png) \| ![preview 4](15/preview_4.png) \| ![preview 5](15/preview_5.png) \| ![preview 6](15/preview_6.png) \| ![preview 7](15/preview_7.png) \| ![preview 8](15/preview_8.png) \| \| 16 \| 25 \| [Download](16/dataset.zip) \| ![preview 1](16/preview_1.png) \| ![preview 2](16/preview_2.png) \| ![preview 3](16/preview_3.png) \| ![preview 4](16/preview_4.png) \| ![preview 5](16/preview_5.png) \| ![preview 6](16/preview_6.png) \| ![preview 7](16/preview_7.png) \| ![preview 8](16/preview_8.png) \| \| 17 \| 81 \| [Download](17/dataset.zip) \| ![preview 1](17/preview_1.png) \| ![preview 2](17/preview_2.png) \| ![preview 3](17/preview_3.png) \| ![preview 4](17/preview_4.png) \| ![preview 5](17/preview_5.png) \| ![preview 6](17/preview_6.png) \| ![preview 7](17/preview_7.png) \| ![preview 8](17/preview_8.png) \| \| 18 \| 18 \| [Download](18/dataset.zip) \| ![preview 1](18/preview_1.png) \| ![preview 2](18/preview_2.png) \| ![preview 3](18/preview_3.png) \| ![preview 4](18/preview_4.png) \| ![preview 5](18/preview_5.png) \| ![preview 6](18/preview_6.png) \| ![preview 7](18/preview_7.png) \| ![preview 8](18/preview_8.png) \| \| 19 \| 31 \| [Download](19/dataset.zip) \| ![preview 1](19/preview_1.png) \| ![preview 2](19/preview_2.png) \| ![preview 3](19/preview_3.png) \| ![preview 4](19/preview_4.png) \| ![preview 5](19/preview_5.png) \| ![preview 6](19/preview_6.png) \| ![preview 7](19/preview_7.png) \| ![preview 8](19/preview_8.png) \| \| 20 \| 51 \| [Download](20/dataset.zip) \| ![preview 1](20/preview_1.png) \| ![preview 2](20/preview_2.png) \| ![preview 3](20/preview_3.png) \| ![preview 4](20/preview_4.png) \| ![preview 5](20/preview_5.png) \| ![preview 6](20/preview_6.png) \| ![preview 7](20/preview_7.png) \| ![preview 8](20/preview_8.png) \| \| 21 \| 109 \| [Download](21/dataset.zip) \| ![preview 1](21/preview_1.png) \| ![preview 2](21/preview_2.png) \| ![preview 3](21/preview_3.png) \| ![preview 4](21/preview_4.png) \| ![preview 5](21/preview_5.png) \| ![preview 6](21/preview_6.png) \| ![preview 7](21/preview_7.png) \| ![preview 8](21/preview_8.png) \| \| 22 \| 46 \| [Download](22/dataset.zip) \| ![preview 1](22/preview_1.png) \| ![preview 2](22/preview_2.png) \| ![preview 3](22/preview_3.png) \| ![preview 4](22/preview_4.png) \| ![preview 5](22/preview_5.png) \| ![preview 6](22/preview_6.png) \| ![preview 7](22/preview_7.png) \| ![preview 8](22/preview_8.png) \| \| 23 \| 42 \| [Download](23/dataset.zip) \| ![preview 1](23/preview_1.png) \| ![preview 2](23/preview_2.png) \| ![preview 3](23/preview_3.png) \| ![preview 4](23/preview_4.png) \| ![preview 5](23/preview_5.png) \| ![preview 6](23/preview_6.png) \| ![preview 7](23/preview_7.png) \| ![preview 8](23/preview_8.png) \| \| 24 \| 78 \| [Download](24/dataset.zip) \| ![preview 1](24/preview_1.png) \| ![preview 2](24/preview_2.png) \| ![preview 3](24/preview_3.png) \| ![preview 4](24/preview_4.png) \| ![preview 5](24/preview_5.png) \| ![preview 6](24/preview_6.png) \| ![preview 7](24/preview_7.png) \| ![preview 8](24/preview_8.png) \| \| 25 \| 31 \| [Download](25/dataset.zip) \| ![preview 1](25/preview_1.png) \| ![preview 2](25/preview_2.png) \| ![preview 3](25/preview_3.png) \| ![preview 4](25/preview_4.png) \| ![preview 5](25/preview_5.png) \| ![preview 6](25/preview_6.png) \| ![preview 7](25/preview_7.png) \| ![preview 8](25/preview_8.png) \| \| 26 \| 136 \| [Download](26/dataset.zip) \| ![preview 1](26/preview_1.png) \| ![preview 2](26/preview_2.png) \| ![preview 3](26/preview_3.png) \| ![preview 4](26/preview_4.png) \| ![preview 5](26/preview_5.png) \| ![preview 6](26/preview_6.png) \| ![preview 7](26/preview_7.png) \| ![preview 8](26/preview_8.png) \| \| 27 \| 48 \| [Download](27/dataset.zip) \| ![preview 1](27/preview_1.png) \| ![preview 2](27/preview_2.png) \| ![preview 3](27/preview_3.png) \| ![preview 4](27/preview_4.png) \| ![preview 5](27/preview_5.png) \| ![preview 6](27/preview_6.png) \| ![preview 7](27/preview_7.png) \| ![preview 8](27/preview_8.png) \| \| 28 \| 30 \| [Download](28/dataset.zip) \| ![preview 1](28/preview_1.png) \| ![preview 2](28/preview_2.png) \| ![preview 3](28/preview_3.png) \| ![preview 4](28/preview_4.png) \| ![preview 5](28/preview_5.png) \| ![preview 6](28/preview_6.png) \| ![preview 7](28/preview_7.png) \| ![preview 8](28/preview_8.png) \| \| 29 \| 49 \| [Download](29/dataset.zip) \| ![preview 1](29/preview_1.png) \| ![preview 2](29/preview_2.png) \| ![preview 3](29/preview_3.png) \| ![preview 4](29/preview_4.png) \| ![preview 5](29/preview_5.png) \| ![preview 6](29/preview_6.png) \| ![preview 7](29/preview_7.png) \| ![preview 8](29/preview_8.png) \| \| 30 \| 27 \| [Download](30/dataset.zip) \| ![preview 1](30/preview_1.png) \| ![preview 2](30/preview_2.png) \| ![preview 3](30/preview_3.png) \| ![preview 4](30/preview_4.png) \| ![preview 5](30/preview_5.png) \| ![preview 6](30/preview_6.png) \| ![preview 7](30/preview_7.png) \| ![preview 8](30/preview_8.png) \| \| 31 \| 29 \| [Download](31/dataset.zip) \| ![preview 1](31/preview_1.png) \| ![preview 2](31/preview_2.png) \| ![preview 3](31/preview_3.png) \| ![preview 4](31/preview_4.png) \| ![preview 5](31/preview_5.png) \| ![preview 6](31/preview_6.png) \| ![preview 7](31/preview_7.png) \| ![preview 8](31/preview_8.png) \| \| 32 \| 44 \| [Download](32/dataset.zip) \| ![preview 1](32/preview_1.png) \| ![preview 2](32/preview_2.png) \| ![preview 3](32/preview_3.png) \| ![preview 4](32/preview_4.png) \| ![preview 5](32/preview_5.png) \| ![preview 6](32/preview_6.png) \| ![preview 7](32/preview_7.png) \| ![preview 8](32/preview_8.png) \| \| 33 \| 428 \| [Download](33/dataset.zip) \| ![preview 1](33/preview_1.png) \| ![preview 2](33/preview_2.png) \| ![preview 3](33/preview_3.png) \| ![preview 4](33/preview_4.png) \| ![preview 5](33/preview_5.png) \| ![preview 6](33/preview_6.png) \| ![preview 7](33/preview_7.png) \| ![preview 8](33/preview_8.png) \| \| 34 \| 41 \| [Download](34/dataset.zip) \| ![preview 1](34/preview_1.png) \| ![preview 2](34/preview_2.png) \| ![preview 3](34/preview_3.png) \| ![preview 4](34/preview_4.png) \| ![preview 5](34/preview_5.png) \| ![preview 6](34/preview_6.png) \| ![preview 7](34/preview_7.png) \| ![preview 8](34/preview_8.png) \| \| 35 \| 55 \| [Download](35/dataset.zip) \| ![preview 1](35/preview_1.png) \| ![preview 2](35/preview_2.png) \| ![preview 3](35/preview_3.png) \| ![preview 4](35/preview_4.png) \| ![preview 5](35/preview_5.png) \| ![preview 6](35/preview_6.png) \| ![preview 7](35/preview_7.png) \| ![preview 8](35/preview_8.png) \| \| 36 \| 40 \| [Download](36/dataset.zip) \| ![preview 1](36/preview_1.png) \| ![preview 2](36/preview_2.png) \| ![preview 3](36/preview_3.png) \| ![preview 4](36/preview_4.png) \| ![preview 5](36/preview_5.png) \| ![preview 6](36/preview_6.png) \| ![preview 7](36/preview_7.png) \| ![preview 8](36/preview_8.png) \| \| 37 \| 23 \| [Download](37/dataset.zip) \| ![preview 1](37/preview_1.png) \| ![preview 2](37/preview_2.png) \| ![preview 3](37/preview_3.png) \| ![preview 4](37/preview_4.png) \| ![preview 5](37/preview_5.png) \| ![preview 6](37/preview_6.png) \| ![preview 7](37/preview_7.png) \| ![preview 8](37/preview_8.png) \| \| 38 \| 271 \| [Download](38/dataset.zip) \| ![preview 1](38/preview_1.png) \| ![preview 2](38/preview_2.png) \| ![preview 3](38/preview_3.png) \| ![preview 4](38/preview_4.png) \| ![preview 5](38/preview_5.png) \| ![preview 6](38/preview_6.png) \| ![preview 7](38/preview_7.png) \| ![preview 8](38/preview_8.png) \| \| 39 \| 41 \| [Download](39/dataset.zip) \| ![preview 1](39/preview_1.png) \| ![preview 2](39/preview_2.png) \| ![preview 3](39/preview_3.png) \| ![preview 4](39/preview_4.png) \| ![preview 5](39/preview_5.png) \| ![preview 6](39/preview_6.png) \| ![preview 7](39/preview_7.png) \| ![preview 8](39/preview_8.png) \| \| 40 \| 42 \| [Download](40/dataset.zip) \| ![preview 1](40/preview_1.png) \| ![preview 2](40/preview_2.png) \| ![preview 3](40/preview_3.png) \| ![preview 4](40/preview_4.png) \| ![preview 5](40/preview_5.png) \| ![preview 6](40/preview_6.png) \| ![preview 7](40/preview_7.png) \| ![preview 8](40/preview_8.png) \| \| 41 \| 39 \| [Download](41/dataset.zip) \| ![preview 1](41/preview_1.png) \| ![preview 2](41/preview_2.png) \| ![preview 3](41/preview_3.png) \| ![preview 4](41/preview_4.png) \| ![preview 5](41/preview_5.png) \| ![preview 6](41/preview_6.png) \| ![preview 7](41/preview_7.png) \| ![preview 8](41/preview_8.png) \| \| 42 \| 12 \| [Download](42/dataset.zip) \| ![preview 1](42/preview_1.png) \| ![preview 2](42/preview_2.png) \| ![preview 3](42/preview_3.png) \| ![preview 4](42/preview_4.png) \| ![preview 5](42/preview_5.png) \| ![preview 6](42/preview_6.png) \| ![preview 7](42/preview_7.png) \| ![preview 8](42/preview_8.png) \| \| 43 \| 23 \| [Download](43/dataset.zip) \| ![preview 1](43/preview_1.png) \| ![preview 2](43/preview_2.png) \| ![preview 3](43/preview_3.png) \| ![preview 4](43/preview_4.png) \| ![preview 5](43/preview_5.png) \| ![preview 6](43/preview_6.png) \| ![preview 7](43/preview_7.png) \| ![preview 8](43/preview_8.png) \| \| 44 \| 26 \| [Download](44/dataset.zip) \| ![preview 1](44/preview_1.png) \| ![preview 2](44/preview_2.png) \| ![preview 3](44/preview_3.png) \| ![preview 4](44/preview_4.png) \| ![preview 5](44/preview_5.png) \| ![preview 6](44/preview_6.png) \| ![preview 7](44/preview_7.png) \| ![preview 8](44/preview_8.png) \| \| 45 \| 68 \| [Download](45/dataset.zip) \| ![preview 1](45/preview_1.png) \| ![preview 2](45/preview_2.png) \| ![preview 3](45/preview_3.png) \| ![preview 4](45/preview_4.png) \| ![preview 5](45/preview_5.png) \| ![preview 6](45/preview_6.png) \| ![preview 7](45/preview_7.png) \| ![preview 8](45/preview_8.png) \| \| 46 \| 47 \| [Download](46/dataset.zip) \| ![preview 1](46/preview_1.png) \| ![preview 2](46/preview_2.png) \| ![preview 3](46/preview_3.png) \| ![preview 4](46/preview_4.png) \| ![preview 5](46/preview_5.png) \| ![preview 6](46/preview_6.png) \| ![preview 7](46/preview_7.png) \| ![preview 8](46/preview_8.png) \| \| 47 \| 53 \| [Download](47/dataset.zip) \| ![preview 1](47/preview_1.png) \| ![preview 2](47/preview_2.png) \| ![preview 3](47/preview_3.png) \| ![preview 4](47/preview_4.png) \| ![preview 5](47/preview_5.png) \| ![preview 6](47/preview_6.png) \| ![preview 7](47/preview_7.png) \| ![preview 8](47/preview_8.png) \| \| 48 \| 24 \| [Download](48/dataset.zip) \| ![preview 1](48/preview_1.png) \| ![preview 2](48/preview_2.png) \| ![preview 3](48/preview_3.png) \| ![preview 4](48/preview_4.png) \| ![preview 5](48/preview_5.png) \| ![preview 6](48/preview_6.png) \| ![preview 7](48/preview_7.png) \| ![preview 8](48/preview_8.png) \| \| 49 \| 26 \| [Download](49/dataset.zip) \| ![preview 1](49/preview_1.png) \| ![preview 2](49/preview_2.png) \| ![preview 3](49/preview_3.png) \| ![preview 4](49/preview_4.png) \| ![preview 5](49/preview_5.png) \| ![preview 6](49/preview_6.png) \| ![preview 7](49/preview_7.png) \| ![preview 8](49/preview_8.png) \| \| 50 \| 185 \| [Download](50/dataset.zip) \| ![preview 1](50/preview_1.png) \| ![preview 2](50/preview_2.png) \| ![preview 3](50/preview_3.png) \| ![preview 4](50/preview_4.png) \| ![preview 5](50/preview_5.png) \| ![preview 6](50/preview_6.png) \| ![preview 7](50/preview_7.png) \| ![preview 8](50/preview_8.png) \| \| 51 \| 46 \| [Download](51/dataset.zip) \| ![preview 1](51/preview_1.png) \| ![preview 2](51/preview_2.png) \| ![preview 3](51/preview_3.png) \| ![preview 4](51/preview_4.png) \| ![preview 5](51/preview_5.png) \| ![preview 6](51/preview_6.png) \| ![preview 7](51/preview_7.png) \| ![preview 8](51/preview_8.png) \| \| 52 \| 32 \| [Download](52/dataset.zip) \| ![preview 1](52/preview_1.png) \| ![preview 2](52/preview_2.png) \| ![preview 3](52/preview_3.png) \| ![preview 4](52/preview_4.png) \| ![preview 5](52/preview_5.png) \| ![preview 6](52/preview_6.png) \| ![preview 7](52/preview_7.png) \| ![preview 8](52/preview_8.png) \| \| 53 \| 27 \| [Download](53/dataset.zip) \| ![preview 1](53/preview_1.png) \| ![preview 2](53/preview_2.png) \| ![preview 3](53/preview_3.png) \| ![preview 4](53/preview_4.png) \| ![preview 5](53/preview_5.png) \| ![preview 6](53/preview_6.png) \| ![preview 7](53/preview_7.png) \| ![preview 8](53/preview_8.png) \| \| 54 \| 50 \| [Download](54/dataset.zip) \| ![preview 1](54/preview_1.png) \| ![preview 2](54/preview_2.png) \| ![preview 3](54/preview_3.png) \| ![preview 4](54/preview_4.png) \| ![preview 5](54/preview_5.png) \| ![preview 6](54/preview_6.png) \| ![preview 7](54/preview_7.png) \| ![preview 8](54/preview_8.png) \| \| 55 \| 40 \| [Download](55/dataset.zip) \| ![preview 1](55/preview_1.png) \| ![preview 2](55/preview_2.png) \| ![preview 3](55/preview_3.png) \| ![preview 4](55/preview_4.png) \| ![preview 5](55/preview_5.png) \| ![preview 6](55/preview_6.png) \| ![preview 7](55/preview_7.png) \| ![preview 8](55/preview_8.png) \| \| 56 \| 12 \| [Download](56/dataset.zip) \| ![preview 1](56/preview_1.png) \| ![preview 2](56/preview_2.png) \| ![preview 3](56/preview_3.png) \| ![preview 4](56/preview_4.png) \| ![preview 5](56/preview_5.png) \| ![preview 6](56/preview_6.png) \| ![preview 7](56/preview_7.png) \| ![preview 8](56/preview_8.png) \| \| 57 \| 25 \| [Download](57/dataset.zip) \| ![preview 1](57/preview_1.png) \| ![preview 2](57/preview_2.png) \| ![preview 3](57/preview_3.png) \| ![preview 4](57/preview_4.png) \| ![preview 5](57/preview_5.png) \| ![preview 6](57/preview_6.png) \| ![preview 7](57/preview_7.png) \| ![preview 8](57/preview_8.png) \| \| 58 \| 35 \| [Download](58/dataset.zip) \| ![preview 1](58/preview_1.png) \| ![preview 2](58/preview_2.png) \| ![preview 3](58/preview_3.png) \| ![preview 4](58/preview_4.png) \| ![preview 5](58/preview_5.png) \| ![preview 6](58/preview_6.png) \| ![preview 7](58/preview_7.png) \| ![preview 8](58/preview_8.png) \| \| 59 \| 17 \| [Download](59/dataset.zip) \| ![preview 1](59/preview_1.png) \| ![preview 2](59/preview_2.png) \| ![preview 3](59/preview_3.png) \| ![preview 4](59/preview_4.png) \| ![preview 5](59/preview_5.png) \| ![preview 6](59/preview_6.png) \| ![preview 7](59/preview_7.png) \| ![preview 8](59/preview_8.png) \| \| 60 \| 66 \| [Download](60/dataset.zip) \| ![preview 1](60/preview_1.png) \| ![preview 2](60/preview_2.png) \| ![preview 3](60/preview_3.png) \| ![preview 4](60/preview_4.png) \| ![preview 5](60/preview_5.png) \| ![preview 6](60/preview_6.png) \| ![preview 7](60/preview_7.png) \| ![preview 8](60/preview_8.png) \| \| 61 \| 41 \| [Download](61/dataset.zip) \| ![preview 1](61/preview_1.png) \| ![preview 2](61/preview_2.png) \| ![preview 3](61/preview_3.png) \| ![preview 4](61/preview_4.png) \| ![preview 5](61/preview_5.png) \| ![preview 6](61/preview_6.png) \| ![preview 7](61/preview_7.png) \| ![preview 8](61/preview_8.png) \| \| 62 \| 28 \| [Download](62/dataset.zip) \| ![preview 1](62/preview_1.png) \| ![preview 2](62/preview_2.png) \| ![preview 3](62/preview_3.png) \| ![preview 4](62/preview_4.png) \| ![preview 5](62/preview_5.png) \| ![preview 6](62/preview_6.png) \| ![preview 7](62/preview_7.png) \| ![preview 8](62/preview_8.png) \| \| 63 \| 21 \| [Download](63/dataset.zip) \| ![preview 1](63/preview_1.png) \| ![preview 2](63/preview_2.png) \| ![preview 3](63/preview_3.png) \| ![preview 4](63/preview_4.png) \| ![preview 5](63/preview_5.png) \| ![preview 6](63/preview_6.png) \| ![preview 7](63/preview_7.png) \| ![preview 8](63/preview_8.png) \| \| 64 \| 17 \| [Download](64/dataset.zip) \| ![preview 1](64/preview_1.png) \| ![preview 2](64/preview_2.png) \| ![preview 3](64/preview_3.png) \| ![preview 4](64/preview_4.png) \| ![preview 5](64/preview_5.png) \| ![preview 6](64/preview_6.png) \| ![preview 7](64/preview_7.png) \| ![preview 8](64/preview_8.png) \| \| 65 \| 16 \| [Download](65/dataset.zip) \| ![preview 1](65/preview_1.png) \| ![preview 2](65/preview_2.png) \| ![preview 3](65/preview_3.png) \| ![preview 4](65/preview_4.png) \| ![preview 5](65/preview_5.png) \| ![preview 6](65/preview_6.png) \| ![preview 7](65/preview_7.png) \| ![preview 8](65/preview_8.png) \| \| 66 \| 54 \| [Download](66/dataset.zip) \| ![preview 1](66/preview_1.png) \| ![preview 2](66/preview_2.png) \| ![preview 3](66/preview_3.png) \| ![preview 4](66/preview_4.png) \| ![preview 5](66/preview_5.png) \| ![preview 6](66/preview_6.png) \| ![preview 7](66/preview_7.png) \| ![preview 8](66/preview_8.png) \| \| 67 \| 22 \| [Download](67/dataset.zip) \| ![preview 1](67/preview_1.png) \| ![preview 2](67/preview_2.png) \| ![preview 3](67/preview_3.png) \| ![preview 4](67/preview_4.png) \| ![preview 5](67/preview_5.png) \| ![preview 6](67/preview_6.png) \| ![preview 7](67/preview_7.png) \| ![preview 8](67/preview_8.png) \| \| 68 \| 17 \| [Download](68/dataset.zip) \| ![preview 1](68/preview_1.png) \| ![preview 2](68/preview_2.png) \| ![preview 3](68/preview_3.png) \| ![preview 4](68/preview_4.png) \| ![preview 5](68/preview_5.png) \| ![preview 6](68/preview_6.png) \| ![preview 7](68/preview_7.png) \| ![preview 8](68/preview_8.png) \| \| 69 \| 9 \| [Download](69/dataset.zip) \| ![preview 1](69/preview_1.png) \| ![preview 2](69/preview_2.png) \| ![preview 3](69/preview_3.png) \| ![preview 4](69/preview_4.png) \| ![preview 5](69/preview_5.png) \| ![preview 6](69/preview_6.png) \| ![preview 7](69/preview_7.png) \| ![preview 8](69/preview_8.png) \| \| 70 \| 21 \| [Download](70/dataset.zip) \| ![preview 1](70/preview_1.png) \| ![preview 2](70/preview_2.png) \| ![preview 3](70/preview_3.png) \| ![preview 4](70/preview_4.png) \| ![preview 5](70/preview_5.png) \| ![preview 6](70/preview_6.png) \| ![preview 7](70/preview_7.png) \| ![preview 8](70/preview_8.png) \| \| 71 \| 30 \| [Download](71/dataset.zip) \| ![preview 1](71/preview_1.png) \| ![preview 2](71/preview_2.png) \| ![preview 3](71/preview_3.png) \| ![preview 4](71/preview_4.png) \| ![preview 5](71/preview_5.png) \| ![preview 6](71/preview_6.png) \| ![preview 7](71/preview_7.png) \| ![preview 8](71/preview_8.png) \| \| 72 \| 15 \| [Download](72/dataset.zip) \| ![preview 1](72/preview_1.png) \| ![preview 2](72/preview_2.png) \| ![preview 3](72/preview_3.png) \| ![preview 4](72/preview_4.png) \| ![preview 5](72/preview_5.png) \| ![preview 6](72/preview_6.png) \| ![preview 7](72/preview_7.png) \| ![preview 8](72/preview_8.png) \| \| 73 \| 21 \| [Download](73/dataset.zip) \| ![preview 1](73/preview_1.png) \| ![preview 2](73/preview_2.png) \| ![preview 3](73/preview_3.png) \| ![preview 4](73/preview_4.png) \| ![preview 5](73/preview_5.png) \| ![preview 6](73/preview_6.png) \| ![preview 7](73/preview_7.png) \| ![preview 8](73/preview_8.png) \| \| 74 \| 19 \| [Download](74/dataset.zip) \| ![preview 1](74/preview_1.png) \| ![preview 2](74/preview_2.png) \| ![preview 3](74/preview_3.png) \| ![preview 4](74/preview_4.png) \| ![preview 5](74/preview_5.png) \| ![preview 6](74/preview_6.png) \| ![preview 7](74/preview_7.png) \| ![preview 8](74/preview_8.png) \| \| 75 \| 13 \| [Download](75/dataset.zip) \| ![preview 1](75/preview_1.png) \| ![preview 2](75/preview_2.png) \| ![preview 3](75/preview_3.png) \| ![preview 4](75/preview_4.png) \| ![preview 5](75/preview_5.png) \| ![preview 6](75/preview_6.png) \| ![preview 7](75/preview_7.png) \| ![preview 8](75/preview_8.png) \| \| 76 \| 17 \| [Download](76/dataset.zip) \| ![preview 1](76/preview_1.png) \| ![preview 2](76/preview_2.png) \| ![preview 3](76/preview_3.png) \| ![preview 4](76/preview_4.png) \| ![preview 5](76/preview_5.png) \| ![preview 6](76/preview_6.png) \| ![preview 7](76/preview_7.png) \| ![preview 8](76/preview_8.png) \| \| 77 \| 13 \| [Download](77/dataset.zip) \| ![preview 1](77/preview_1.png) \| ![preview 2](77/preview_2.png) \| ![preview 3](77/preview_3.png) \| ![preview 4](77/preview_4.png) \| ![preview 5](77/preview_5.png) \| ![preview 6](77/preview_6.png) \| ![preview 7](77/preview_7.png) \| ![preview 8](77/preview_8.png) \| \| 78 \| 101 \| [Download](78/dataset.zip) \| ![preview 1](78/preview_1.png) \| ![preview 2](78/preview_2.png) \| ![preview 3](78/preview_3.png) \| ![preview 4](78/preview_4.png) \| ![preview 5](78/preview_5.png) \| ![preview 6](78/preview_6.png) \| ![preview 7](78/preview_7.png) \| ![preview 8](78/preview_8.png) \| \| 79 \| 17 \| [Download](79/dataset.zip) \| ![preview 1](79/preview_1.png) \| ![preview 2](79/preview_2.png) \| ![preview 3](79/preview_3.png) \| ![preview 4](79/preview_4.png) \| ![preview 5](79/preview_5.png) \| ![preview 6](79/preview_6.png) \| ![preview 7](79/preview_7.png) \| ![preview 8](79/preview_8.png) \| \| 80 \| 23 \| [Download](80/dataset.zip) \| ![preview 1](80/preview_1.png) \| ![preview 2](80/preview_2.png) \| ![preview 3](80/preview_3.png) \| ![preview 4](80/preview_4.png) \| ![preview 5](80/preview_5.png) \| ![preview 6](80/preview_6.png) \| ![preview 7](80/preview_7.png) \| ![preview 8](80/preview_8.png) \| \| 81 \| 23 \| [Download](81/dataset.zip) \| ![preview 1](81/preview_1.png) \| ![preview 2](81/preview_2.png) \| ![preview 3](81/preview_3.png) \| ![preview 4](81/preview_4.png) \| ![preview 5](81/preview_5.png) \| ![preview 6](81/preview_6.png) \| ![preview 7](81/preview_7.png) \| ![preview 8](81/preview_8.png) \| \| 82 \| 7 \| [Download](82/dataset.zip) \| ![preview 1](82/preview_1.png) \| ![preview 2](82/preview_2.png) \| ![preview 3](82/preview_3.png) \| ![preview 4](82/preview_4.png) \| ![preview 5](82/preview_5.png) \| ![preview 6](82/preview_6.png) \| ![preview 7](82/preview_7.png) \| N/A \| \| 83 \| 7 \| [Download](83/dataset.zip) \| ![preview 1](83/preview_1.png) \| ![preview 2](83/preview_2.png) \| ![preview 3](83/preview_3.png) \| ![preview 4](83/preview_4.png) \| ![preview 5](83/preview_5.png) \| ![preview 6](83/preview_6.png) \| ![preview 7](83/preview_7.png) \| N/A \| \| 84 \| 29 \| [Download](84/dataset.zip) \| ![preview 1](84/preview_1.png) \| ![preview 2](84/preview_2.png) \| ![preview 3](84/preview_3.png) \| ![preview 4](84/preview_4.png) \| ![preview 5](84/preview_5.png) \| ![preview 6](84/preview_6.png) \| ![preview 7](84/preview_7.png) \| ![preview 8](84/preview_8.png) \| \| 85 \| 14 \| [Download](85/dataset.zip) \| ![preview 1](85/preview_1.png) \| ![preview 2](85/preview_2.png) \| ![preview 3](85/preview_3.png) \| ![preview 4](85/preview_4.png) \| ![preview 5](85/preview_5.png) \| ![preview 6](85/preview_6.png) \| ![preview 7](85/preview_7.png) \| ![preview 8](85/preview_8.png) \| \| 86 \| 5 \| [Download](86/dataset.zip) \| ![preview 1](86/preview_1.png) \| ![preview 2](86/preview_2.png) \| ![preview 3](86/preview_3.png) \| ![preview 4](86/preview_4.png) \| ![preview 5](86/preview_5.png) \| N/A \| N/A \| N/A \| \| 87 \| 7 \| [Download](87/dataset.zip) \| ![preview 1](87/preview_1.png) \| ![preview 2](87/preview_2.png) \| ![preview 3](87/preview_3.png) \| ![preview 4](87/preview_4.png) \| ![preview 5](87/preview_5.png) \| ![preview 6](87/preview_6.png) \| ![preview 7](87/preview_7.png) \| N/A \| \| noise \| 54 \| [Download](-1/dataset.zip) \| ![preview 1](-1/preview_1.png) \| ![preview 2](-1/preview_2.png) \| ![preview 3](-1/preview_3.png) \| ![preview 4](-1/preview_4.png) \| ![preview 5](-1/preview_5.png) \| ![preview 6](-1/preview_6.png) \| ![preview 7](-1/preview_7.png) \| ![preview 8](-1/preview_8.png) \|
maghwa/OpenHermes-2-AR-10K-38-820k-830k	--- dataset_info: features: - name: model_name dtype: 'null' - name: idx dtype: 'null' - name: language dtype: 'null' - name: skip_prompt_formatting dtype: 'null' - name: custom_instruction dtype: 'null' - name: conversations dtype: string - name: system_prompt dtype: 'null' - name: id dtype: 'null' - name: model dtype: 'null' - name: category dtype: 'null' - name: hash dtype: 'null' - name: avatarUrl dtype: 'null' - name: source dtype: string - name: topic dtype: 'null' - name: views dtype: float64 - name: title dtype: 'null' splits: - name: train num_bytes: 25256647 num_examples: 10001 download_size: 11400617 dataset_size: 25256647 configs: - config_name: default data_files: - split: train path: data/train-* ---
delphi-suite/v0-next-logprobs-llama2-1.6m	--- dataset_info: features: - name: logprobs sequence: float64 splits: - name: validation num_bytes: 45818277 num_examples: 10982 download_size: 37795921 dataset_size: 45818277 configs: - config_name: default data_files: - split: validation path: data/validation-* ---
MaryLux/banking_sentiment	--- dataset_info: features: - name: text dtype: string - name: inputs struct: - name: text dtype: string - name: prediction list: - name: label dtype: string - name: score dtype: float64 - name: prediction_agent dtype: string - name: annotation dtype: 'null' - name: annotation_agent dtype: 'null' - name: vectors dtype: 'null' - name: multi_label dtype: bool - name: explanation dtype: 'null' - name: id dtype: string - name: metadata struct: - name: category dtype: int64 - name: status dtype: string - name: event_timestamp dtype: timestamp[us] - name: metrics dtype: 'null' splits: - name: train num_bytes: 1445808 num_examples: 5001 download_size: 672079 dataset_size: 1445808 --- # Dataset Card for "banking_sentiment" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Dahoas/prompted_svamp	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 1179345 num_examples: 700 - name: test num_bytes: 499449 num_examples: 300 download_size: 702499 dataset_size: 1678794 --- # Dataset Card for "prompted_svamp" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
HuggingFaceM4/imagenet1k_support_5k_query_sets_part_1	Invalid username or password.
Svenni551/questions	--- dataset_info: features: - name: asker dtype: string - name: question dtype: string splits: - name: train num_bytes: 27697 num_examples: 318 download_size: 9920 dataset_size: 27697 configs: - config_name: default data_files: - split: train path: data/train-* ---
jack008/TTR	--- license: unknown ---
Weni/LLM_Base_2.0.3_SFT	--- dataset_info: features: - name: prompt dtype: string - name: question dtype: string - name: answer dtype: string - name: context dtype: string - name: correct_ans dtype: int64 splits: - name: train num_bytes: 73736965 num_examples: 39345 download_size: 25677022 dataset_size: 73736965 configs: - config_name: default data_files: - split: train path: data/train-* ---
realfolkcode/open-music-dataset-demo	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: audio dtype: audio - name: caption dtype: string splits: - name: train num_bytes: 387155570.0 num_examples: 8 download_size: 386530208 dataset_size: 387155570.0 --- # Dataset Card for "open-music-dataset-demo" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Maxis47/Irons	--- license: unlicense task_categories: - text-to-image language: - en tags: - art size_categories: - 1M<n<10M ---
NobodyExistsOnTheInternet/ToxicQAtextFiltered	--- license: mit tags: - not-for-all-audiences --- This is the TEXT filtered version of TOXICQA with all the semi-refusals (e.g. Remember, killing is bad) This is a work in progress. Use only for Alignment research. NOETI is not responsible for what you might do with it.
el2e10/aya-paraphrase-malayalam	--- language: - ml license: cc size_categories: - n<1K source_datasets: - extended\|ai4bharat/IndicXParaphrase task_categories: - text-generation pretty_name: Aya Paraphrase Malayalam dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: template_lang dtype: string - name: template_id dtype: int64 splits: - name: train num_bytes: 710999 num_examples: 1001 download_size: 255190 dataset_size: 710999 configs: - config_name: default data_files: - split: train path: data/train-* --- ### Description This dataset is derived from the already existing dataset made by AI4Bharat. We have used the [IndicXParaphrase](https://huggingface.co/datasets/ai4bharat/IndicXParaphrase) dataset of AI4Bharat to create this instruction style dataset. We have used the malayalam split of the above mentioned dataset to create this one. This was created as part of [Aya Open Science Initiative](https://sites.google.com/cohere.com/aya-en/home) from Cohere For AI. IndicXParaphrase is multilingual, and n-way parallel dataset for paraphrase detection in 10 Indic languages. The original dataset(IndicXParaphrase) was made available under the cc-0 license. ### Template The following templates(Malayalam) where used for converting the original dataset: ``` #Template 1 prompt: ഇനിപ്പറയുന്ന വാചകം വ്യത്യസ്ത വാക്കുകളിൽ എഴുതുക: "{original_sentence}" completion: {paraphrased_sentence} ``` ``` #Template 2 prompt: ഇനിപ്പറയുന്ന വാചകം മറ്റൊരു രീതിയിൽ എഴുതുക: "{original_sentence}" completion: {paraphrased_sentence} ``` ``` #Template 3 prompt: താഴെപ്പറയുന്ന വാചകം പരാവർത്തനം ചെയ്യുക: "{original_sentence}" completion: {paraphrased_sentence} ```
open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1	--- pretty_name: Evaluation run of cloudyu/mistral_18B_instruct_v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [cloudyu/mistral_18B_instruct_v0.1](https://huggingface.co/cloudyu/mistral_18B_instruct_v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-05T02:39:44.844538](https://huggingface.co/datasets/open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1/blob/main/results_2024-03-05T02-39-44.844538.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6039258028692152,\n\ \ \"acc_stderr\": 0.03320637767752478,\n \"acc_norm\": 0.6081395694844028,\n\ \ \"acc_norm_stderr\": 0.03388517114573973,\n \"mc1\": 0.4663402692778458,\n\ \ \"mc1_stderr\": 0.017463793867168106,\n \"mc2\": 0.6484634670784011,\n\ \ \"mc2_stderr\": 0.015219765533463015\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5477815699658704,\n \"acc_stderr\": 0.01454451988063383,\n\ \ \"acc_norm\": 0.5691126279863481,\n \"acc_norm_stderr\": 0.014471133392642466\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6204939255128461,\n\ \ \"acc_stderr\": 0.004842723234022032,\n \"acc_norm\": 0.8135829516032663,\n\ \ \"acc_norm_stderr\": 0.0038864693752987305\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6074074074074074,\n\ \ \"acc_stderr\": 0.04218506215368879,\n \"acc_norm\": 0.6074074074074074,\n\ \ \"acc_norm_stderr\": 0.04218506215368879\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6578947368421053,\n \"acc_stderr\": 0.03860731599316092,\n\ \ \"acc_norm\": 0.6578947368421053,\n \"acc_norm_stderr\": 0.03860731599316092\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6754716981132075,\n \"acc_stderr\": 0.02881561571343211,\n\ \ \"acc_norm\": 0.6754716981132075,\n \"acc_norm_stderr\": 0.02881561571343211\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6597222222222222,\n\ \ \"acc_stderr\": 0.039621355734862175,\n \"acc_norm\": 0.6597222222222222,\n\ \ \"acc_norm_stderr\": 0.039621355734862175\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\": 0.51,\n\ \ \"acc_stderr\": 0.05024183937956911,\n \"acc_norm\": 0.51,\n \ \ \"acc_norm_stderr\": 0.05024183937956911\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6069364161849711,\n\ \ \"acc_stderr\": 0.03724249595817731,\n \"acc_norm\": 0.6069364161849711,\n\ \ \"acc_norm_stderr\": 0.03724249595817731\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.04784060704105654,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.04784060704105654\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.71,\n \"acc_stderr\": 0.04560480215720684,\n \"acc_norm\": 0.71,\n\ \ \"acc_norm_stderr\": 0.04560480215720684\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5446808510638298,\n \"acc_stderr\": 0.03255525359340355,\n\ \ \"acc_norm\": 0.5446808510638298,\n \"acc_norm_stderr\": 0.03255525359340355\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.41228070175438597,\n\ \ \"acc_stderr\": 0.04630653203366595,\n \"acc_norm\": 0.41228070175438597,\n\ \ \"acc_norm_stderr\": 0.04630653203366595\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6,\n \"acc_stderr\": 0.04082482904638629,\n \ \ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.04082482904638629\n },\n\ \ \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\": 0.3862433862433862,\n\ \ \"acc_stderr\": 0.025075981767601684,\n \"acc_norm\": 0.3862433862433862,\n\ \ \"acc_norm_stderr\": 0.025075981767601684\n },\n \"harness\|hendrycksTest-formal_logic\|5\"\ : {\n \"acc\": 0.40476190476190477,\n \"acc_stderr\": 0.04390259265377562,\n\ \ \"acc_norm\": 0.40476190476190477,\n \"acc_norm_stderr\": 0.04390259265377562\n\ \ },\n \"harness\|hendrycksTest-global_facts\|5\": {\n \"acc\": 0.34,\n\ \ \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n \ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness\|hendrycksTest-high_school_biology\|5\"\ : {\n \"acc\": 0.5645161290322581,\n \"acc_stderr\": 0.02820622559150274,\n\ \ \"acc_norm\": 0.5645161290322581,\n \"acc_norm_stderr\": 0.02820622559150274\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.5024630541871922,\n \"acc_stderr\": 0.03517945038691063,\n \"\ acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7212121212121212,\n \"acc_stderr\": 0.03501438706296781,\n\ \ \"acc_norm\": 0.7212121212121212,\n \"acc_norm_stderr\": 0.03501438706296781\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7727272727272727,\n \"acc_stderr\": 0.029857515673386417,\n \"\ acc_norm\": 0.7727272727272727,\n \"acc_norm_stderr\": 0.029857515673386417\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8393782383419689,\n \"acc_stderr\": 0.02649905770139746,\n\ \ \"acc_norm\": 0.8393782383419689,\n \"acc_norm_stderr\": 0.02649905770139746\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5794871794871795,\n \"acc_stderr\": 0.025028610276710862,\n\ \ \"acc_norm\": 0.5794871794871795,\n \"acc_norm_stderr\": 0.025028610276710862\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.32592592592592595,\n \"acc_stderr\": 0.028578348365473082,\n \ \ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.028578348365473082\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.030868682604121626,\n\ \ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.030868682604121626\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.39072847682119205,\n \"acc_stderr\": 0.03983798306659807,\n \"\ acc_norm\": 0.39072847682119205,\n \"acc_norm_stderr\": 0.03983798306659807\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8,\n \"acc_stderr\": 0.01714985851425095,\n \"acc_norm\": 0.8,\n\ \ \"acc_norm_stderr\": 0.01714985851425095\n },\n \"harness\|hendrycksTest-high_school_statistics\|5\"\ : {\n \"acc\": 0.4861111111111111,\n \"acc_stderr\": 0.03408655867977748,\n\ \ \"acc_norm\": 0.4861111111111111,\n \"acc_norm_stderr\": 0.03408655867977748\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7303921568627451,\n \"acc_stderr\": 0.031145570659486782,\n \"\ acc_norm\": 0.7303921568627451,\n \"acc_norm_stderr\": 0.031145570659486782\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7426160337552743,\n \"acc_stderr\": 0.02845882099146031,\n \ \ \"acc_norm\": 0.7426160337552743,\n \"acc_norm_stderr\": 0.02845882099146031\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6591928251121076,\n\ \ \"acc_stderr\": 0.031811497470553604,\n \"acc_norm\": 0.6591928251121076,\n\ \ \"acc_norm_stderr\": 0.031811497470553604\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7251908396946565,\n \"acc_stderr\": 0.03915345408847837,\n\ \ \"acc_norm\": 0.7251908396946565,\n \"acc_norm_stderr\": 0.03915345408847837\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.754601226993865,\n \"acc_stderr\": 0.03380939813943354,\n\ \ \"acc_norm\": 0.754601226993865,\n \"acc_norm_stderr\": 0.03380939813943354\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.45535714285714285,\n\ \ \"acc_stderr\": 0.04726835553719099,\n \"acc_norm\": 0.45535714285714285,\n\ \ \"acc_norm_stderr\": 0.04726835553719099\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7184466019417476,\n \"acc_stderr\": 0.04453254836326466,\n\ \ \"acc_norm\": 0.7184466019417476,\n \"acc_norm_stderr\": 0.04453254836326466\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8461538461538461,\n\ \ \"acc_stderr\": 0.0236368733174893,\n \"acc_norm\": 0.8461538461538461,\n\ \ \"acc_norm_stderr\": 0.0236368733174893\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7854406130268199,\n\ \ \"acc_stderr\": 0.014680033956893346,\n \"acc_norm\": 0.7854406130268199,\n\ \ \"acc_norm_stderr\": 0.014680033956893346\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6791907514450867,\n \"acc_stderr\": 0.025131000233647893,\n\ \ \"acc_norm\": 0.6791907514450867,\n \"acc_norm_stderr\": 0.025131000233647893\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.3642458100558659,\n\ \ \"acc_stderr\": 0.016094338768474596,\n \"acc_norm\": 0.3642458100558659,\n\ \ \"acc_norm_stderr\": 0.016094338768474596\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.026787453111906497,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.026787453111906497\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6881028938906752,\n\ \ \"acc_stderr\": 0.02631185807185416,\n \"acc_norm\": 0.6881028938906752,\n\ \ \"acc_norm_stderr\": 0.02631185807185416\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6820987654320988,\n \"acc_stderr\": 0.02591006352824088,\n\ \ \"acc_norm\": 0.6820987654320988,\n \"acc_norm_stderr\": 0.02591006352824088\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.450354609929078,\n \"acc_stderr\": 0.02968010556502904,\n \ \ \"acc_norm\": 0.450354609929078,\n \"acc_norm_stderr\": 0.02968010556502904\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4041720990873533,\n\ \ \"acc_stderr\": 0.012533504046491362,\n \"acc_norm\": 0.4041720990873533,\n\ \ \"acc_norm_stderr\": 0.012533504046491362\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6397058823529411,\n \"acc_stderr\": 0.029163128570670733,\n\ \ \"acc_norm\": 0.6397058823529411,\n \"acc_norm_stderr\": 0.029163128570670733\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6143790849673203,\n \"acc_stderr\": 0.019691459052354025,\n \ \ \"acc_norm\": 0.6143790849673203,\n \"acc_norm_stderr\": 0.019691459052354025\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7,\n\ \ \"acc_stderr\": 0.04389311454644287,\n \"acc_norm\": 0.7,\n \ \ \"acc_norm_stderr\": 0.04389311454644287\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.710204081632653,\n \"acc_stderr\": 0.02904308868330433,\n\ \ \"acc_norm\": 0.710204081632653,\n \"acc_norm_stderr\": 0.02904308868330433\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.6915422885572139,\n\ \ \"acc_stderr\": 0.03265819588512698,\n \"acc_norm\": 0.6915422885572139,\n\ \ \"acc_norm_stderr\": 0.03265819588512698\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.4879518072289157,\n\ \ \"acc_stderr\": 0.03891364495835821,\n \"acc_norm\": 0.4879518072289157,\n\ \ \"acc_norm_stderr\": 0.03891364495835821\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.02954774168764004,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.02954774168764004\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.4663402692778458,\n\ \ \"mc1_stderr\": 0.017463793867168106,\n \"mc2\": 0.6484634670784011,\n\ \ \"mc2_stderr\": 0.015219765533463015\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7703235990528808,\n \"acc_stderr\": 0.011821645601838232\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.40333586050037906,\n \ \ \"acc_stderr\": 0.013512654781814694\n }\n}\n```" repo_url: https://huggingface.co/cloudyu/mistral_18B_instruct_v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|arc:challenge\|25_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-05T02-39-44.844538.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|gsm8k\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hellaswag\|10_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-05T02-39-44.844538.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-05T02-39-44.844538.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '/details_harness\|winogrande\|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-05T02-39-44.844538.parquet' - config_name: results data_files: - split: 2024_03_05T02_39_44.844538 path: - results_2024-03-05T02-39-44.844538.parquet - split: latest path: - results_2024-03-05T02-39-44.844538.parquet --- # Dataset Card for Evaluation run of cloudyu/mistral_18B_instruct_v0.1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [cloudyu/mistral_18B_instruct_v0.1](https://huggingface.co/cloudyu/mistral_18B_instruct_v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-05T02:39:44.844538](https://huggingface.co/datasets/open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1/blob/main/results_2024-03-05T02-39-44.844538.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6039258028692152, "acc_stderr": 0.03320637767752478, "acc_norm": 0.6081395694844028, "acc_norm_stderr": 0.03388517114573973, "mc1": 0.4663402692778458, "mc1_stderr": 0.017463793867168106, "mc2": 0.6484634670784011, "mc2_stderr": 0.015219765533463015 }, "harness\|arc:challenge\|25": { "acc": 0.5477815699658704, "acc_stderr": 0.01454451988063383, "acc_norm": 0.5691126279863481, "acc_norm_stderr": 0.014471133392642466 }, "harness\|hellaswag\|10": { "acc": 0.6204939255128461, "acc_stderr": 0.004842723234022032, "acc_norm": 0.8135829516032663, "acc_norm_stderr": 0.0038864693752987305 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6074074074074074, "acc_stderr": 0.04218506215368879, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.04218506215368879 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6578947368421053, "acc_stderr": 0.03860731599316092, "acc_norm": 0.6578947368421053, "acc_norm_stderr": 0.03860731599316092 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6754716981132075, "acc_stderr": 0.02881561571343211, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.02881561571343211 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6597222222222222, "acc_stderr": 0.039621355734862175, "acc_norm": 0.6597222222222222, "acc_norm_stderr": 0.039621355734862175 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6069364161849711, "acc_stderr": 0.03724249595817731, "acc_norm": 0.6069364161849711, "acc_norm_stderr": 0.03724249595817731 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105654, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105654 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.71, "acc_stderr": 0.04560480215720684, "acc_norm": 0.71, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.41228070175438597, "acc_stderr": 0.04630653203366595, "acc_norm": 0.41228070175438597, "acc_norm_stderr": 0.04630653203366595 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6, "acc_stderr": 0.04082482904638629, "acc_norm": 0.6, "acc_norm_stderr": 0.04082482904638629 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3862433862433862, "acc_stderr": 0.025075981767601684, "acc_norm": 0.3862433862433862, "acc_norm_stderr": 0.025075981767601684 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.40476190476190477, "acc_stderr": 0.04390259265377562, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.04390259265377562 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.5645161290322581, "acc_stderr": 0.02820622559150274, "acc_norm": 0.5645161290322581, "acc_norm_stderr": 0.02820622559150274 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5024630541871922, "acc_stderr": 0.03517945038691063, "acc_norm": 0.5024630541871922, "acc_norm_stderr": 0.03517945038691063 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7212121212121212, "acc_stderr": 0.03501438706296781, "acc_norm": 0.7212121212121212, "acc_norm_stderr": 0.03501438706296781 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7727272727272727, "acc_stderr": 0.029857515673386417, "acc_norm": 0.7727272727272727, "acc_norm_stderr": 0.029857515673386417 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8393782383419689, "acc_stderr": 0.02649905770139746, "acc_norm": 0.8393782383419689, "acc_norm_stderr": 0.02649905770139746 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5794871794871795, "acc_stderr": 0.025028610276710862, "acc_norm": 0.5794871794871795, "acc_norm_stderr": 0.025028610276710862 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.32592592592592595, "acc_stderr": 0.028578348365473082, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.028578348365473082 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6554621848739496, "acc_stderr": 0.030868682604121626, "acc_norm": 0.6554621848739496, "acc_norm_stderr": 0.030868682604121626 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.39072847682119205, "acc_stderr": 0.03983798306659807, "acc_norm": 0.39072847682119205, "acc_norm_stderr": 0.03983798306659807 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8, "acc_stderr": 0.01714985851425095, "acc_norm": 0.8, "acc_norm_stderr": 0.01714985851425095 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4861111111111111, "acc_stderr": 0.03408655867977748, "acc_norm": 0.4861111111111111, "acc_norm_stderr": 0.03408655867977748 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7303921568627451, "acc_stderr": 0.031145570659486782, "acc_norm": 0.7303921568627451, "acc_norm_stderr": 0.031145570659486782 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7426160337552743, "acc_stderr": 0.02845882099146031, "acc_norm": 0.7426160337552743, "acc_norm_stderr": 0.02845882099146031 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6591928251121076, "acc_stderr": 0.031811497470553604, "acc_norm": 0.6591928251121076, "acc_norm_stderr": 0.031811497470553604 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7251908396946565, "acc_stderr": 0.03915345408847837, "acc_norm": 0.7251908396946565, "acc_norm_stderr": 0.03915345408847837 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228732, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228732 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.754601226993865, "acc_stderr": 0.03380939813943354, "acc_norm": 0.754601226993865, "acc_norm_stderr": 0.03380939813943354 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.45535714285714285, "acc_stderr": 0.04726835553719099, "acc_norm": 0.45535714285714285, "acc_norm_stderr": 0.04726835553719099 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7184466019417476, "acc_stderr": 0.04453254836326466, "acc_norm": 0.7184466019417476, "acc_norm_stderr": 0.04453254836326466 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8461538461538461, "acc_stderr": 0.0236368733174893, "acc_norm": 0.8461538461538461, "acc_norm_stderr": 0.0236368733174893 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7854406130268199, "acc_stderr": 0.014680033956893346, "acc_norm": 0.7854406130268199, "acc_norm_stderr": 0.014680033956893346 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6791907514450867, "acc_stderr": 0.025131000233647893, "acc_norm": 0.6791907514450867, "acc_norm_stderr": 0.025131000233647893 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.3642458100558659, "acc_stderr": 0.016094338768474596, "acc_norm": 0.3642458100558659, "acc_norm_stderr": 0.016094338768474596 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6764705882352942, "acc_stderr": 0.026787453111906497, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.026787453111906497 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6881028938906752, "acc_stderr": 0.02631185807185416, "acc_norm": 0.6881028938906752, "acc_norm_stderr": 0.02631185807185416 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6820987654320988, "acc_stderr": 0.02591006352824088, "acc_norm": 0.6820987654320988, "acc_norm_stderr": 0.02591006352824088 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.450354609929078, "acc_stderr": 0.02968010556502904, "acc_norm": 0.450354609929078, "acc_norm_stderr": 0.02968010556502904 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4041720990873533, "acc_stderr": 0.012533504046491362, "acc_norm": 0.4041720990873533, "acc_norm_stderr": 0.012533504046491362 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6397058823529411, "acc_stderr": 0.029163128570670733, "acc_norm": 0.6397058823529411, "acc_norm_stderr": 0.029163128570670733 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6143790849673203, "acc_stderr": 0.019691459052354025, "acc_norm": 0.6143790849673203, "acc_norm_stderr": 0.019691459052354025 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7, "acc_stderr": 0.04389311454644287, "acc_norm": 0.7, "acc_norm_stderr": 0.04389311454644287 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.710204081632653, "acc_stderr": 0.02904308868330433, "acc_norm": 0.710204081632653, "acc_norm_stderr": 0.02904308868330433 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.6915422885572139, "acc_stderr": 0.03265819588512698, "acc_norm": 0.6915422885572139, "acc_norm_stderr": 0.03265819588512698 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.4879518072289157, "acc_stderr": 0.03891364495835821, "acc_norm": 0.4879518072289157, "acc_norm_stderr": 0.03891364495835821 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8187134502923976, "acc_stderr": 0.02954774168764004, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.02954774168764004 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.4663402692778458, "mc1_stderr": 0.017463793867168106, "mc2": 0.6484634670784011, "mc2_stderr": 0.015219765533463015 }, "harness\|winogrande\|5": { "acc": 0.7703235990528808, "acc_stderr": 0.011821645601838232 }, "harness\|gsm8k\|5": { "acc": 0.40333586050037906, "acc_stderr": 0.013512654781814694 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be 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AlekseyKorshuk/sharegpt-chatml	--- dataset_info: features: - name: conversation list: - name: content dtype: string - name: do_train dtype: bool - name: role dtype: string splits: - name: train num_bytes: 628712441 num_examples: 94145 download_size: 0 dataset_size: 628712441 --- # Dataset Card for "sharegpt-chatml" Data preprocessing pipeline: https://github.com/AlekseyKorshuk/chat-data-pipeline
open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache	--- pretty_name: Evaluation run of saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache](https://huggingface.co/saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-28T18:15:46.929459](https://huggingface.co/datasets/open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache/blob/main/results_2024-01-28T18-15-46.929459.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.23209302149061675,\n\ \ \"acc_stderr\": 0.02992707807148158,\n \"acc_norm\": 0.23163380863022787,\n\ \ \"acc_norm_stderr\": 0.03071316471647595,\n \"mc1\": 0.23011015911872704,\n\ \ \"mc1_stderr\": 0.014734557959807763,\n \"mc2\": 0.48987576662324334,\n\ \ \"mc2_stderr\": 0.016135847085052512\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.2022184300341297,\n \"acc_stderr\": 0.011737454431872104,\n\ \ \"acc_norm\": 0.23037542662116042,\n \"acc_norm_stderr\": 0.01230492841874761\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.25951005775741887,\n\ \ \"acc_stderr\": 0.004374699189284863,\n \"acc_norm\": 0.25941047600079664,\n\ \ \"acc_norm_stderr\": 0.004374153847826759\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.18518518518518517,\n\ \ \"acc_stderr\": 0.03355677216313142,\n \"acc_norm\": 0.18518518518518517,\n\ \ \"acc_norm_stderr\": 0.03355677216313142\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.17763157894736842,\n \"acc_stderr\": 0.031103182383123398,\n\ \ \"acc_norm\": 0.17763157894736842,\n \"acc_norm_stderr\": 0.031103182383123398\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.21509433962264152,\n \"acc_stderr\": 0.02528839450289137,\n\ \ \"acc_norm\": 0.21509433962264152,\n \"acc_norm_stderr\": 0.02528839450289137\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2569444444444444,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.2569444444444444,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036845,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036845\n },\n\ \ \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\": 0.26,\n\ \ \"acc_stderr\": 0.0440844002276808,\n \"acc_norm\": 0.26,\n \ \ \"acc_norm_stderr\": 0.0440844002276808\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \ \ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.20809248554913296,\n\ \ \"acc_stderr\": 0.030952890217749874,\n \"acc_norm\": 0.20809248554913296,\n\ \ \"acc_norm_stderr\": 0.030952890217749874\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237654,\n\ \ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237654\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.045126085985421276\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102973,\n\ \ \"acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102973\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813365,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813365\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135302,\n\ \ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135302\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.20899470899470898,\n \"acc_stderr\": 0.02094048156533486,\n \"\ acc_norm\": 0.20899470899470898,\n \"acc_norm_stderr\": 0.02094048156533486\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.2857142857142857,\n\ \ \"acc_stderr\": 0.04040610178208841,\n \"acc_norm\": 0.2857142857142857,\n\ \ \"acc_norm_stderr\": 0.04040610178208841\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.18,\n \"acc_stderr\": 0.038612291966536934,\n \ \ \"acc_norm\": 0.18,\n \"acc_norm_stderr\": 0.038612291966536934\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.1774193548387097,\n \"acc_stderr\": 0.02173254068932927,\n \"\ acc_norm\": 0.1774193548387097,\n \"acc_norm_stderr\": 0.02173254068932927\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.15270935960591134,\n \"acc_stderr\": 0.02530890453938063,\n \"\ acc_norm\": 0.15270935960591134,\n \"acc_norm_stderr\": 0.02530890453938063\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.17676767676767677,\n \"acc_stderr\": 0.027178752639044915,\n \"\ acc_norm\": 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860664,\n\ \ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.20256410256410257,\n \"acc_stderr\": 0.020377660970371372,\n\ \ \"acc_norm\": 0.20256410256410257,\n \"acc_norm_stderr\": 0.020377660970371372\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2111111111111111,\n \"acc_stderr\": 0.024882116857655075,\n \ \ \"acc_norm\": 0.2111111111111111,\n \"acc_norm_stderr\": 0.024882116857655075\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.21008403361344538,\n \"acc_stderr\": 0.026461398717471874,\n\ \ \"acc_norm\": 0.21008403361344538,\n \"acc_norm_stderr\": 0.026461398717471874\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.1986754966887417,\n \"acc_stderr\": 0.03257847384436776,\n \"\ acc_norm\": 0.1986754966887417,\n \"acc_norm_stderr\": 0.03257847384436776\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.1926605504587156,\n \"acc_stderr\": 0.016909276884936094,\n \"\ acc_norm\": 0.1926605504587156,\n \"acc_norm_stderr\": 0.016909276884936094\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.1527777777777778,\n \"acc_stderr\": 0.024536326026134224,\n \"\ acc_norm\": 0.1527777777777778,\n \"acc_norm_stderr\": 0.024536326026134224\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.31390134529147984,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.31390134529147984,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.2595419847328244,\n \"acc_stderr\": 0.03844876139785271,\n\ \ \"acc_norm\": 0.2595419847328244,\n \"acc_norm_stderr\": 0.03844876139785271\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.25925925925925924,\n\ \ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.25925925925925924,\n\ \ \"acc_norm_stderr\": 0.042365112580946336\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.032591773927421776,\n\ \ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.17475728155339806,\n \"acc_stderr\": 0.037601780060266224,\n\ \ \"acc_norm\": 0.17475728155339806,\n \"acc_norm_stderr\": 0.037601780060266224\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.2905982905982906,\n\ \ \"acc_stderr\": 0.02974504857267404,\n \"acc_norm\": 0.2905982905982906,\n\ \ \"acc_norm_stderr\": 0.02974504857267404\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.23754789272030652,\n\ \ \"acc_stderr\": 0.015218733046150193,\n \"acc_norm\": 0.23754789272030652,\n\ \ \"acc_norm_stderr\": 0.015218733046150193\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.24855491329479767,\n \"acc_stderr\": 0.023267528432100174,\n\ \ \"acc_norm\": 0.24855491329479767,\n \"acc_norm_stderr\": 0.023267528432100174\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.023929155517351284,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.023929155517351284\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.1864951768488746,\n\ \ \"acc_stderr\": 0.02212243977248077,\n \"acc_norm\": 0.1864951768488746,\n\ \ \"acc_norm_stderr\": 0.02212243977248077\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.21604938271604937,\n \"acc_stderr\": 0.022899162918445806,\n\ \ \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.022899162918445806\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.23404255319148937,\n \"acc_stderr\": 0.025257861359432417,\n \ \ \"acc_norm\": 0.23404255319148937,\n \"acc_norm_stderr\": 0.025257861359432417\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.2457627118644068,\n\ \ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\ \ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.25,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness\|hendrycksTest-public_relations\|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03955932861795833,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03955932861795833\n\ \ },\n \"harness\|hendrycksTest-security_studies\|5\": {\n \"acc\": 0.18775510204081633,\n\ \ \"acc_stderr\": 0.02500025603954621,\n \"acc_norm\": 0.18775510204081633,\n\ \ \"acc_norm_stderr\": 0.02500025603954621\n },\n \"harness\|hendrycksTest-sociology\|5\"\ : {\n \"acc\": 0.24378109452736318,\n \"acc_stderr\": 0.03036049015401465,\n\ \ \"acc_norm\": 0.24378109452736318,\n \"acc_norm_stderr\": 0.03036049015401465\n\ \ },\n \"harness\|hendrycksTest-us_foreign_policy\|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness\|hendrycksTest-virology\|5\"\ : {\n \"acc\": 0.28313253012048195,\n \"acc_stderr\": 0.03507295431370518,\n\ \ \"acc_norm\": 0.28313253012048195,\n \"acc_norm_stderr\": 0.03507295431370518\n\ \ },\n \"harness\|hendrycksTest-world_religions\|5\": {\n \"acc\": 0.3216374269005848,\n\ \ \"acc_stderr\": 0.03582529442573122,\n \"acc_norm\": 0.3216374269005848,\n\ \ \"acc_norm_stderr\": 0.03582529442573122\n },\n \"harness\|truthfulqa:mc\|0\"\ : {\n \"mc1\": 0.23011015911872704,\n \"mc1_stderr\": 0.014734557959807763,\n\ \ \"mc2\": 0.48987576662324334,\n \"mc2_stderr\": 0.016135847085052512\n\ \ },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.5193370165745856,\n\ \ \"acc_stderr\": 0.01404197273371297\n },\n \"harness\|gsm8k\|5\": {\n\ \ \"acc\": 0.0,\n \"acc_stderr\": 0.0\n }\n}\n```" repo_url: https://huggingface.co/saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|arc:challenge\|25_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-28T18-15-46.929459.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|gsm8k\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hellaswag\|10_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-28T18-15-46.929459.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-28T18-15-46.929459.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '/details_harness\|winogrande\|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-28T18-15-46.929459.parquet' - config_name: results data_files: - split: 2024_01_28T18_15_46.929459 path: - results_2024-01-28T18-15-46.929459.parquet - split: latest path: - results_2024-01-28T18-15-46.929459.parquet --- # Dataset Card for Evaluation run of saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache](https://huggingface.co/saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-28T18:15:46.929459](https://huggingface.co/datasets/open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache/blob/main/results_2024-01-28T18-15-46.929459.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.23209302149061675, "acc_stderr": 0.02992707807148158, "acc_norm": 0.23163380863022787, "acc_norm_stderr": 0.03071316471647595, "mc1": 0.23011015911872704, "mc1_stderr": 0.014734557959807763, "mc2": 0.48987576662324334, "mc2_stderr": 0.016135847085052512 }, "harness\|arc:challenge\|25": { "acc": 0.2022184300341297, "acc_stderr": 0.011737454431872104, "acc_norm": 0.23037542662116042, "acc_norm_stderr": 0.01230492841874761 }, "harness\|hellaswag\|10": { "acc": 0.25951005775741887, "acc_stderr": 0.004374699189284863, "acc_norm": 0.25941047600079664, "acc_norm_stderr": 0.004374153847826759 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.18518518518518517, "acc_stderr": 0.03355677216313142, "acc_norm": 0.18518518518518517, "acc_norm_stderr": 0.03355677216313142 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.17763157894736842, "acc_stderr": 0.031103182383123398, "acc_norm": 0.17763157894736842, "acc_norm_stderr": 0.031103182383123398 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.21509433962264152, "acc_stderr": 0.02528839450289137, "acc_norm": 0.21509433962264152, "acc_norm_stderr": 0.02528839450289137 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.2, "acc_stderr": 0.04020151261036845, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036845 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749874, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749874 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237654, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237654 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.26382978723404255, "acc_stderr": 0.028809989854102973, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.028809989854102973 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813365, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813365 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2413793103448276, "acc_stderr": 0.03565998174135302, "acc_norm": 0.2413793103448276, "acc_norm_stderr": 0.03565998174135302 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.20899470899470898, "acc_stderr": 0.02094048156533486, "acc_norm": 0.20899470899470898, "acc_norm_stderr": 0.02094048156533486 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.2857142857142857, "acc_stderr": 0.04040610178208841, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.04040610178208841 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.18, "acc_stderr": 0.038612291966536934, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536934 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.1774193548387097, "acc_stderr": 0.02173254068932927, "acc_norm": 0.1774193548387097, "acc_norm_stderr": 0.02173254068932927 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.15270935960591134, "acc_stderr": 0.02530890453938063, "acc_norm": 0.15270935960591134, "acc_norm_stderr": 0.02530890453938063 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.17676767676767677, "acc_stderr": 0.027178752639044915, "acc_norm": 0.17676767676767677, "acc_norm_stderr": 0.027178752639044915 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.19689119170984457, "acc_stderr": 0.028697873971860664, "acc_norm": 0.19689119170984457, "acc_norm_stderr": 0.028697873971860664 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.20256410256410257, "acc_stderr": 0.020377660970371372, "acc_norm": 0.20256410256410257, "acc_norm_stderr": 0.020377660970371372 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2111111111111111, "acc_stderr": 0.024882116857655075, "acc_norm": 0.2111111111111111, "acc_norm_stderr": 0.024882116857655075 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.21008403361344538, "acc_stderr": 0.026461398717471874, "acc_norm": 0.21008403361344538, "acc_norm_stderr": 0.026461398717471874 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.1986754966887417, "acc_stderr": 0.03257847384436776, "acc_norm": 0.1986754966887417, "acc_norm_stderr": 0.03257847384436776 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.1926605504587156, "acc_stderr": 0.016909276884936094, "acc_norm": 0.1926605504587156, "acc_norm_stderr": 0.016909276884936094 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.1527777777777778, "acc_stderr": 0.024536326026134224, "acc_norm": 0.1527777777777778, "acc_norm_stderr": 0.024536326026134224 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.31390134529147984, "acc_stderr": 0.031146796482972465, "acc_norm": 0.31390134529147984, "acc_norm_stderr": 0.031146796482972465 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.2595419847328244, "acc_stderr": 0.03844876139785271, "acc_norm": 0.2595419847328244, "acc_norm_stderr": 0.03844876139785271 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.2396694214876033, "acc_stderr": 0.03896878985070417, "acc_norm": 0.2396694214876033, "acc_norm_stderr": 0.03896878985070417 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.25925925925925924, "acc_stderr": 0.042365112580946336, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.042365112580946336 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.22085889570552147, "acc_stderr": 0.032591773927421776, "acc_norm": 0.22085889570552147, "acc_norm_stderr": 0.032591773927421776 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness\|hendrycksTest-management\|5": { "acc": 0.17475728155339806, "acc_stderr": 0.037601780060266224, "acc_norm": 0.17475728155339806, "acc_norm_stderr": 0.037601780060266224 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.2905982905982906, "acc_stderr": 0.02974504857267404, "acc_norm": 0.2905982905982906, "acc_norm_stderr": 0.02974504857267404 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.23754789272030652, "acc_stderr": 0.015218733046150193, "acc_norm": 0.23754789272030652, "acc_norm_stderr": 0.015218733046150193 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.24855491329479767, "acc_stderr": 0.023267528432100174, "acc_norm": 0.24855491329479767, "acc_norm_stderr": 0.023267528432100174 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.22549019607843138, "acc_stderr": 0.023929155517351284, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.023929155517351284 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.1864951768488746, "acc_stderr": 0.02212243977248077, "acc_norm": 0.1864951768488746, "acc_norm_stderr": 0.02212243977248077 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.21604938271604937, "acc_stderr": 0.022899162918445806, "acc_norm": 0.21604938271604937, "acc_norm_stderr": 0.022899162918445806 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.23404255319148937, "acc_stderr": 0.025257861359432417, "acc_norm": 0.23404255319148937, "acc_norm_stderr": 0.025257861359432417 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.2457627118644068, "acc_stderr": 0.010996156635142692, "acc_norm": 0.2457627118644068, "acc_norm_stderr": 0.010996156635142692 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.25, "acc_stderr": 0.01751781884501444, "acc_norm": 0.25, "acc_norm_stderr": 0.01751781884501444 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03955932861795833, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03955932861795833 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.18775510204081633, "acc_stderr": 0.02500025603954621, "acc_norm": 0.18775510204081633, "acc_norm_stderr": 0.02500025603954621 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.24378109452736318, "acc_stderr": 0.03036049015401465, "acc_norm": 0.24378109452736318, "acc_norm_stderr": 0.03036049015401465 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.28313253012048195, "acc_stderr": 0.03507295431370518, "acc_norm": 0.28313253012048195, "acc_norm_stderr": 0.03507295431370518 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.3216374269005848, "acc_stderr": 0.03582529442573122, "acc_norm": 0.3216374269005848, "acc_norm_stderr": 0.03582529442573122 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.23011015911872704, "mc1_stderr": 0.014734557959807763, "mc2": 0.48987576662324334, "mc2_stderr": 0.016135847085052512 }, "harness\|winogrande\|5": { "acc": 0.5193370165745856, "acc_stderr": 0.01404197273371297 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo 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open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3	--- pretty_name: Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v3 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [oh-yeontaek/llama-2-70B-LoRA-assemble-v3](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-15T17:36:30.757691](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3/blob/main/results_2023-09-15T17-36-30.757691.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6985803552112708,\n\ \ \"acc_stderr\": 0.03118492094070661,\n \"acc_norm\": 0.7024274155828159,\n\ \ \"acc_norm_stderr\": 0.031154550420018332,\n \"mc1\": 0.47980416156670747,\n\ \ \"mc1_stderr\": 0.01748921684973705,\n \"mc2\": 0.658093697491632,\n\ \ \"mc2_stderr\": 0.014747866760131165\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6860068259385665,\n \"acc_stderr\": 0.013562691224726291,\n\ \ \"acc_norm\": 0.7209897610921502,\n \"acc_norm_stderr\": 0.013106784883601334\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6820354511053575,\n\ \ \"acc_stderr\": 0.004647338877642188,\n \"acc_norm\": 0.8740290778729337,\n\ \ \"acc_norm_stderr\": 0.0033113844981586464\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.041539484047424,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.041539484047424\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7828947368421053,\n \"acc_stderr\": 0.03355045304882924,\n\ \ \"acc_norm\": 0.7828947368421053,\n \"acc_norm_stderr\": 0.03355045304882924\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.76,\n\ \ \"acc_stderr\": 0.04292346959909284,\n \"acc_norm\": 0.76,\n \ \ \"acc_norm_stderr\": 0.04292346959909284\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7547169811320755,\n \"acc_stderr\": 0.026480357179895695,\n\ \ \"acc_norm\": 0.7547169811320755,\n \"acc_norm_stderr\": 0.026480357179895695\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.8194444444444444,\n\ \ \"acc_stderr\": 0.03216600808802267,\n \"acc_norm\": 0.8194444444444444,\n\ \ \"acc_norm_stderr\": 0.03216600808802267\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.62,\n \"acc_stderr\": 0.04878317312145632,\n \"acc_norm\"\ : 0.62,\n \"acc_norm_stderr\": 0.04878317312145632\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6647398843930635,\n\ \ \"acc_stderr\": 0.03599586301247077,\n \"acc_norm\": 0.6647398843930635,\n\ \ \"acc_norm_stderr\": 0.03599586301247077\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383888,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383888\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768078,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768078\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.676595744680851,\n \"acc_stderr\": 0.03057944277361034,\n\ \ \"acc_norm\": 0.676595744680851,\n \"acc_norm_stderr\": 0.03057944277361034\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4649122807017544,\n\ \ \"acc_stderr\": 0.04692008381368909,\n \"acc_norm\": 0.4649122807017544,\n\ \ \"acc_norm_stderr\": 0.04692008381368909\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6413793103448275,\n \"acc_stderr\": 0.03996629574876719,\n\ \ \"acc_norm\": 0.6413793103448275,\n \"acc_norm_stderr\": 0.03996629574876719\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.47354497354497355,\n \"acc_stderr\": 0.025715239811346758,\n \"\ acc_norm\": 0.47354497354497355,\n \"acc_norm_stderr\": 0.025715239811346758\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.49206349206349204,\n\ \ \"acc_stderr\": 0.044715725362943486,\n \"acc_norm\": 0.49206349206349204,\n\ \ \"acc_norm_stderr\": 0.044715725362943486\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.8193548387096774,\n\ \ \"acc_stderr\": 0.02188617856717253,\n \"acc_norm\": 0.8193548387096774,\n\ \ \"acc_norm_stderr\": 0.02188617856717253\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.541871921182266,\n \"acc_stderr\": 0.03505630140785741,\n\ \ \"acc_norm\": 0.541871921182266,\n \"acc_norm_stderr\": 0.03505630140785741\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\"\ : 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8484848484848485,\n \"acc_stderr\": 0.027998073798781675,\n\ \ \"acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.027998073798781675\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8888888888888888,\n \"acc_stderr\": 0.022390787638216763,\n \"\ acc_norm\": 0.8888888888888888,\n \"acc_norm_stderr\": 0.022390787638216763\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.927461139896373,\n \"acc_stderr\": 0.018718998520678178,\n\ \ \"acc_norm\": 0.927461139896373,\n \"acc_norm_stderr\": 0.018718998520678178\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6974358974358974,\n \"acc_stderr\": 0.02329088805377272,\n \ \ \"acc_norm\": 0.6974358974358974,\n \"acc_norm_stderr\": 0.02329088805377272\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.32592592592592595,\n \"acc_stderr\": 0.028578348365473072,\n \ \ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.028578348365473072\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.773109243697479,\n \"acc_stderr\": 0.02720537153827947,\n \ \ \"acc_norm\": 0.773109243697479,\n \"acc_norm_stderr\": 0.02720537153827947\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.4966887417218543,\n \"acc_stderr\": 0.04082393379449654,\n \"\ acc_norm\": 0.4966887417218543,\n \"acc_norm_stderr\": 0.04082393379449654\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8954128440366973,\n \"acc_stderr\": 0.013120530245265586,\n \"\ acc_norm\": 0.8954128440366973,\n \"acc_norm_stderr\": 0.013120530245265586\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5833333333333334,\n \"acc_stderr\": 0.03362277436608043,\n \"\ acc_norm\": 0.5833333333333334,\n \"acc_norm_stderr\": 0.03362277436608043\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.9019607843137255,\n \"acc_stderr\": 0.020871118455552097,\n \"\ acc_norm\": 0.9019607843137255,\n \"acc_norm_stderr\": 0.020871118455552097\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.890295358649789,\n \"acc_stderr\": 0.020343400734868837,\n \ \ \"acc_norm\": 0.890295358649789,\n \"acc_norm_stderr\": 0.020343400734868837\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.7623318385650224,\n\ \ \"acc_stderr\": 0.028568079464714274,\n \"acc_norm\": 0.7623318385650224,\n\ \ \"acc_norm_stderr\": 0.028568079464714274\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8396946564885496,\n \"acc_stderr\": 0.03217829420744632,\n\ \ \"acc_norm\": 0.8396946564885496,\n \"acc_norm_stderr\": 0.03217829420744632\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8512396694214877,\n \"acc_stderr\": 0.03248470083807194,\n \"\ acc_norm\": 0.8512396694214877,\n \"acc_norm_stderr\": 0.03248470083807194\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.8282208588957055,\n \"acc_stderr\": 0.02963471727237104,\n\ \ \"acc_norm\": 0.8282208588957055,\n \"acc_norm_stderr\": 0.02963471727237104\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.48214285714285715,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.48214285714285715,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8349514563106796,\n \"acc_stderr\": 0.03675668832233188,\n\ \ \"acc_norm\": 0.8349514563106796,\n \"acc_norm_stderr\": 0.03675668832233188\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8974358974358975,\n\ \ \"acc_stderr\": 0.01987565502786745,\n \"acc_norm\": 0.8974358974358975,\n\ \ \"acc_norm_stderr\": 0.01987565502786745\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.859514687100894,\n\ \ \"acc_stderr\": 0.012426211353093448,\n \"acc_norm\": 0.859514687100894,\n\ \ \"acc_norm_stderr\": 0.012426211353093448\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7658959537572254,\n \"acc_stderr\": 0.022797110278071128,\n\ \ \"acc_norm\": 0.7658959537572254,\n \"acc_norm_stderr\": 0.022797110278071128\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.582122905027933,\n\ \ \"acc_stderr\": 0.016495400635820084,\n \"acc_norm\": 0.582122905027933,\n\ \ \"acc_norm_stderr\": 0.016495400635820084\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7483660130718954,\n \"acc_stderr\": 0.024848018263875195,\n\ \ \"acc_norm\": 0.7483660130718954,\n \"acc_norm_stderr\": 0.024848018263875195\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7427652733118971,\n\ \ \"acc_stderr\": 0.024826171289250888,\n \"acc_norm\": 0.7427652733118971,\n\ \ \"acc_norm_stderr\": 0.024826171289250888\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8117283950617284,\n \"acc_stderr\": 0.021751866060815882,\n\ \ \"acc_norm\": 0.8117283950617284,\n \"acc_norm_stderr\": 0.021751866060815882\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.574468085106383,\n \"acc_stderr\": 0.02949482760014436,\n \ \ \"acc_norm\": 0.574468085106383,\n \"acc_norm_stderr\": 0.02949482760014436\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.5788787483702738,\n\ \ \"acc_stderr\": 0.012610325733489905,\n \"acc_norm\": 0.5788787483702738,\n\ \ \"acc_norm_stderr\": 0.012610325733489905\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7242647058823529,\n \"acc_stderr\": 0.027146271936625162,\n\ \ \"acc_norm\": 0.7242647058823529,\n \"acc_norm_stderr\": 0.027146271936625162\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.7565359477124183,\n \"acc_stderr\": 0.017362473762146613,\n \ \ \"acc_norm\": 0.7565359477124183,\n \"acc_norm_stderr\": 0.017362473762146613\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7454545454545455,\n\ \ \"acc_stderr\": 0.04172343038705383,\n \"acc_norm\": 0.7454545454545455,\n\ \ \"acc_norm_stderr\": 0.04172343038705383\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7959183673469388,\n \"acc_stderr\": 0.025801283475090496,\n\ \ \"acc_norm\": 0.7959183673469388,\n \"acc_norm_stderr\": 0.025801283475090496\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8905472636815921,\n\ \ \"acc_stderr\": 0.02207632610182466,\n \"acc_norm\": 0.8905472636815921,\n\ \ \"acc_norm_stderr\": 0.02207632610182466\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.033799766898963086,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.033799766898963086\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8596491228070176,\n \"acc_stderr\": 0.0266405825391332,\n\ \ \"acc_norm\": 0.8596491228070176,\n \"acc_norm_stderr\": 0.0266405825391332\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.47980416156670747,\n\ \ \"mc1_stderr\": 0.01748921684973705,\n \"mc2\": 0.658093697491632,\n\ \ \"mc2_stderr\": 0.014747866760131165\n }\n}\n```" repo_url: https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|arc:challenge\|25_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hellaswag\|10_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T17-36-30.757691.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T17_36_30.757691 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-15T17-36-30.757691.parquet' - config_name: results data_files: - split: 2023_09_15T17_36_30.757691 path: - results_2023-09-15T17-36-30.757691.parquet - split: latest path: - results_2023-09-15T17-36-30.757691.parquet --- # Dataset Card for Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v3 ## Dataset Description - Homepage: - Repository: https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [oh-yeontaek/llama-2-70B-LoRA-assemble-v3](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-15T17:36:30.757691](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3/blob/main/results_2023-09-15T17-36-30.757691.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6985803552112708, "acc_stderr": 0.03118492094070661, "acc_norm": 0.7024274155828159, "acc_norm_stderr": 0.031154550420018332, "mc1": 0.47980416156670747, "mc1_stderr": 0.01748921684973705, "mc2": 0.658093697491632, "mc2_stderr": 0.014747866760131165 }, "harness\|arc:challenge\|25": { "acc": 0.6860068259385665, "acc_stderr": 0.013562691224726291, "acc_norm": 0.7209897610921502, "acc_norm_stderr": 0.013106784883601334 }, "harness\|hellaswag\|10": { "acc": 0.6820354511053575, "acc_stderr": 0.004647338877642188, "acc_norm": 0.8740290778729337, "acc_norm_stderr": 0.0033113844981586464 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6370370370370371, "acc_stderr": 0.041539484047424, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.041539484047424 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7828947368421053, "acc_stderr": 0.03355045304882924, "acc_norm": 0.7828947368421053, "acc_norm_stderr": 0.03355045304882924 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.76, "acc_stderr": 0.04292346959909284, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909284 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7547169811320755, "acc_stderr": 0.026480357179895695, "acc_norm": 0.7547169811320755, "acc_norm_stderr": 0.026480357179895695 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.8194444444444444, "acc_stderr": 0.03216600808802267, "acc_norm": 0.8194444444444444, "acc_norm_stderr": 0.03216600808802267 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6647398843930635, "acc_stderr": 0.03599586301247077, "acc_norm": 0.6647398843930635, "acc_norm_stderr": 0.03599586301247077 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383888, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383888 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.74, "acc_stderr": 0.04408440022768078, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768078 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.676595744680851, "acc_stderr": 0.03057944277361034, "acc_norm": 0.676595744680851, "acc_norm_stderr": 0.03057944277361034 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4649122807017544, "acc_stderr": 0.04692008381368909, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.04692008381368909 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6413793103448275, "acc_stderr": 0.03996629574876719, "acc_norm": 0.6413793103448275, "acc_norm_stderr": 0.03996629574876719 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.47354497354497355, "acc_stderr": 0.025715239811346758, "acc_norm": 0.47354497354497355, "acc_norm_stderr": 0.025715239811346758 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.49206349206349204, "acc_stderr": 0.044715725362943486, "acc_norm": 0.49206349206349204, "acc_norm_stderr": 0.044715725362943486 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8193548387096774, "acc_stderr": 0.02188617856717253, "acc_norm": 0.8193548387096774, "acc_norm_stderr": 0.02188617856717253 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.541871921182266, "acc_stderr": 0.03505630140785741, "acc_norm": 0.541871921182266, "acc_norm_stderr": 0.03505630140785741 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8484848484848485, "acc_stderr": 0.027998073798781675, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.027998073798781675 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8888888888888888, "acc_stderr": 0.022390787638216763, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.022390787638216763 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.927461139896373, "acc_stderr": 0.018718998520678178, "acc_norm": 0.927461139896373, "acc_norm_stderr": 0.018718998520678178 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6974358974358974, "acc_stderr": 0.02329088805377272, "acc_norm": 0.6974358974358974, "acc_norm_stderr": 0.02329088805377272 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.32592592592592595, "acc_stderr": 0.028578348365473072, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.028578348365473072 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.773109243697479, "acc_stderr": 0.02720537153827947, "acc_norm": 0.773109243697479, "acc_norm_stderr": 0.02720537153827947 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.4966887417218543, "acc_stderr": 0.04082393379449654, "acc_norm": 0.4966887417218543, "acc_norm_stderr": 0.04082393379449654 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8954128440366973, "acc_stderr": 0.013120530245265586, "acc_norm": 0.8954128440366973, "acc_norm_stderr": 0.013120530245265586 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5833333333333334, "acc_stderr": 0.03362277436608043, "acc_norm": 0.5833333333333334, "acc_norm_stderr": 0.03362277436608043 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.9019607843137255, "acc_stderr": 0.020871118455552097, "acc_norm": 0.9019607843137255, "acc_norm_stderr": 0.020871118455552097 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.890295358649789, "acc_stderr": 0.020343400734868837, "acc_norm": 0.890295358649789, "acc_norm_stderr": 0.020343400734868837 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.7623318385650224, "acc_stderr": 0.028568079464714274, "acc_norm": 0.7623318385650224, "acc_norm_stderr": 0.028568079464714274 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.8396946564885496, "acc_stderr": 0.03217829420744632, "acc_norm": 0.8396946564885496, "acc_norm_stderr": 0.03217829420744632 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8512396694214877, "acc_stderr": 0.03248470083807194, "acc_norm": 0.8512396694214877, "acc_norm_stderr": 0.03248470083807194 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8333333333333334, "acc_stderr": 0.03602814176392645, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.03602814176392645 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.8282208588957055, "acc_stderr": 0.02963471727237104, "acc_norm": 0.8282208588957055, "acc_norm_stderr": 0.02963471727237104 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.48214285714285715, "acc_stderr": 0.047427623612430116, "acc_norm": 0.48214285714285715, "acc_norm_stderr": 0.047427623612430116 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8349514563106796, "acc_stderr": 0.03675668832233188, "acc_norm": 0.8349514563106796, "acc_norm_stderr": 0.03675668832233188 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8974358974358975, "acc_stderr": 0.01987565502786745, "acc_norm": 0.8974358974358975, "acc_norm_stderr": 0.01987565502786745 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.859514687100894, "acc_stderr": 0.012426211353093448, "acc_norm": 0.859514687100894, "acc_norm_stderr": 0.012426211353093448 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7658959537572254, "acc_stderr": 0.022797110278071128, "acc_norm": 0.7658959537572254, "acc_norm_stderr": 0.022797110278071128 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.582122905027933, "acc_stderr": 0.016495400635820084, "acc_norm": 0.582122905027933, "acc_norm_stderr": 0.016495400635820084 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7483660130718954, "acc_stderr": 0.024848018263875195, "acc_norm": 0.7483660130718954, "acc_norm_stderr": 0.024848018263875195 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7427652733118971, "acc_stderr": 0.024826171289250888, "acc_norm": 0.7427652733118971, "acc_norm_stderr": 0.024826171289250888 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.8117283950617284, "acc_stderr": 0.021751866060815882, "acc_norm": 0.8117283950617284, "acc_norm_stderr": 0.021751866060815882 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.574468085106383, "acc_stderr": 0.02949482760014436, "acc_norm": 0.574468085106383, "acc_norm_stderr": 0.02949482760014436 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.5788787483702738, "acc_stderr": 0.012610325733489905, "acc_norm": 0.5788787483702738, "acc_norm_stderr": 0.012610325733489905 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.7242647058823529, "acc_stderr": 0.027146271936625162, "acc_norm": 0.7242647058823529, "acc_norm_stderr": 0.027146271936625162 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.7565359477124183, "acc_stderr": 0.017362473762146613, "acc_norm": 0.7565359477124183, "acc_norm_stderr": 0.017362473762146613 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7454545454545455, "acc_stderr": 0.04172343038705383, "acc_norm": 0.7454545454545455, "acc_norm_stderr": 0.04172343038705383 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7959183673469388, "acc_stderr": 0.025801283475090496, "acc_norm": 0.7959183673469388, "acc_norm_stderr": 0.025801283475090496 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8905472636815921, "acc_stderr": 0.02207632610182466, "acc_norm": 0.8905472636815921, "acc_norm_stderr": 0.02207632610182466 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.87, "acc_stderr": 0.033799766898963086, "acc_norm": 0.87, "acc_norm_stderr": 0.033799766898963086 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5120481927710844, "acc_stderr": 0.03891364495835817, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.03891364495835817 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8596491228070176, "acc_stderr": 0.0266405825391332, "acc_norm": 0.8596491228070176, "acc_norm_stderr": 0.0266405825391332 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.47980416156670747, "mc1_stderr": 0.01748921684973705, "mc2": 0.658093697491632, "mc2_stderr": 0.014747866760131165 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]
AdapterOcean/med_alpaca_standardized_cluster_33_std	--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 15881902 num_examples: 31912 download_size: 7840649 dataset_size: 15881902 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_33_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
siddharthjadhav6565/vedas	--- license: openrail ---
ASR-HypR/AISHELL1_withoutLM	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: dev path: data/dev-* dataset_info: features: - name: ref dtype: string - name: hyps sequence: string - name: ctc_score sequence: float64 - name: att_score sequence: float64 - name: utt_id dtype: string - name: score sequence: float64 splits: - name: train num_bytes: 520539152 num_examples: 120098 - name: test num_bytes: 31358088 num_examples: 7176 - name: dev num_bytes: 61833418 num_examples: 14326 download_size: 283530745 dataset_size: 613730658 --- # Dataset Card for "AISHELL1_withoutLM" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
316usman/thematic5e-pw-embed-part5	--- dataset_info: features: - name: text dtype: string - name: document_url dtype: string - name: source_url dtype: string - name: country dtype: string splits: - name: train num_bytes: 269487465 num_examples: 405601 download_size: 105797465 dataset_size: 269487465 configs: - config_name: default data_files: - split: train path: data/train-* ---
joey234/mmlu-high_school_microeconomics	--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string - name: neg_question dtype: string - name: fewshot_context dtype: string - name: fewshot_context_neg dtype: string splits: - name: dev num_bytes: 4194 num_examples: 5 - name: test num_bytes: 839869 num_examples: 238 download_size: 104401 dataset_size: 844063 configs: - config_name: default data_files: - split: dev path: data/dev-* - split: test path: data/test-* --- # Dataset Card for "mmlu-high_school_microeconomics" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
convaiinnovations/llama2-new	--- license: mit ---
Jingkang/PVSG	--- license: mit --- We carefully collect 400 videos, each featuring dynamic scenes and rich in logical reasoning content. On average, these videos are 76.5 seconds long (5 FPS). The collection comprises 289 videos from VidOR, 55 videos from EpicKitchen, and 56 videos from Ego4D. Please `git clone` https://github.com/LilyDaytoy/OpenPVSG and organize your files according to the structure below. You can put the HF dataset in `data_zip` directory. ``` ├── assets ├── checkpoints ├── configs ├── data ├── data_zip │ ├── Ego4D │ │ ├── ego4d_masks.zip │ │ └── ego4d_videos.zip │ ├── EpicKitchen │ │ ├── epic_kitchen_masks.zip │ │ └── epic_kitchen_videos.zip │ ├── VidOR │ │ ├── vidor_masks.zip │ │ └── vidor_videos.zip │ └── pvsg.json ├── datasets ├── models ├── scripts ├── tools ├── utils ├── .gitignore ├── environment.yml └── README.md ``` Please run unzip_and_extract.py to unzip the files and extract frames from the videos. If you use zip, make sure to use `unzip -j xxx.zip` to remove junk paths. You should have your data directory looks like this: ``` data ├── ego4d │ ├── frames │ ├── masks │ └── videos ├── epic_kitchen │ ├── frames │ ├── masks │ └── videos ├── vidor │ ├── frames │ ├── masks │ └── videos └── pvsg.json ``` We suggest our users to play with `./notebooks/Visualize_Dataset.ipynb` to quickly get familiar with PVSG dataset. ## Citation For more information about the methods used in this dataset, please refer to the following paper: [Panoptic Video Scene Graph Generation](https://arxiv.org/abs/2310.15166), arXiv:2310.15166.
edbeeching/prj_gia_dataset_atari_2B_atari_zaxxon_1111	--- library_name: gia tags: - deep-reinforcement-learning - reinforcement-learning - gia - multi-task - multi-modal - imitation-learning - offline-reinforcement-learning --- An imitation learning environment for the atari_zaxxon environment, sample for the policy atari_2B_atari_zaxxon_1111 This environment was created as part of the Generally Intelligent Agents project gia: https://github.com/huggingface/gia
LIKirin/klonetai-prompts	--- license: mit ---
zakcroft/test_lamini_docs	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 4054.5 num_examples: 5 - name: test num_bytes: 4054.5 num_examples: 5 download_size: 12911 dataset_size: 8109.0 --- # Dataset Card for "test_lamini_docs" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ahmadSiddiqi/t5-qrels	--- dataset_info: features: - name: qid dtype: string - name: pid dtype: string - name: score dtype: int64 splits: - name: dev num_bytes: 24384 num_examples: 1061 download_size: 7749 dataset_size: 24384 configs: - config_name: default data_files: - split: dev path: data/dev-* ---
mtkinit/mtkinit_test_xyz_aaa	--- pretty_name: mtkinit/test_xyz_aaa --- # mtkinit/test_xyz_aaa Created from AIOD platform
muhammadravi251001/squadid-nli	--- annotations_creators: - machine-generated - manual-partial-validation language_creators: - expert-generated language: - id license: unknown multilinguality: - monolingual size_categories: - 100K<n<1M source_datasets: - SQuAD-ID task_categories: - text-classification task_ids: - natural-language-inference pretty_name: SQuAD-ID-NLI dataset_info: features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: '0': entailment '1': neutral '2': contradiction config_name: squadid-nli splits: - name: train num_bytes: 103934750 num_examples: 236891 - name: validation num_bytes: 10831375 num_examples: 23749 - name: test num_bytes: 10969750 num_examples: 23747 download_size: 125735875 dataset_size: 284387 --- # Dataset Card for SQuAD-ID-NLI ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Repository: [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/squadid-nli) - Point of Contact: [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/squadid-nli) - Experiment: [Github](https://github.com/muhammadravi251001/multilingual-qas-with-nli) ### Dataset Summary The SQuAD-ID-NLI dataset is derived from the SQuAD-ID question answering dataset, utilizing named entity recognition (NER), chunking tags, Regex, and embedding similarity techniques to determine its contradiction sets. Collected through this process, the dataset comprises various columns beyond premise, hypothesis, and label, including properties aligned with NER and chunking tags. This dataset is designed to facilitate Natural Language Inference (NLI) tasks and contains information extracted from diverse sources to provide comprehensive coverage. Each data instance encapsulates premise, hypothesis, label, and additional properties pertinent to NLI evaluation. ### Supported Tasks and Leaderboards - Natural Language Inference for Indonesian ### Languages Indonesian ## Dataset Structure ### Data Instances An example of `test` looks as follows. ``` { "premise": "Beberapa keluarga Yunani Bizantium berasal dari tentara bayaran Norman selama periode Restorasi Comnenian, ketika kaisar Bizantium mencari prajurit Eropa Barat. Raoulii adalah keturunan dari orang Italia-Norman bernama Raoul, Petraliphae adalah keturunan dari Pierre d'Aulps, dan kelompok klan Albania yang dikenal sebagai Maniakate diturunkan dari Normandia yang bertugas di bawah George Maniaces dalam ekspedisi Sisilia tahun 1038.", "hypothesis": "Dari mana beberapa famili tentara bayaran Norman berasal? Yunani Bizantium", "label": 0 } ``` ### Data Fields The data fields are: - `premise`: a `string` feature - `hypothesis`: a `string` feature - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). ### Data Splits #TODO The data is split across `train`, `valid`, and `test`. \| split \| # examples \| \|----------\|-------:\| \|train\| 236891\| \|valid\| 23749\| \|test\| 23747\| ## Dataset Creation ### Curation Rationale Indonesian NLP is considered under-resourced. We need NLI dataset to fine-tuning the NLI model to utilizing them for QA models in order to improving the performance of the QA's. ### Source Data #### Initial Data Collection and Normalization We collect the data from the prominent QA dataset in Indonesian. The annotation fully by the original dataset's researcher. #### Who are the source language producers? This synthetic data was produced by machine, but the original data was produced by human. ### Personal and Sensitive Information There might be some personal information coming from Wikipedia and news, especially the information of famous/important people. ## Considerations for Using the Data ### Discussion of Biases The QA dataset (so the NLI-derived from them) is created using premise sentences taken from Wikipedia and news. These data sources may contain some bias. ### Other Known Limitations No other known limitations ## Additional Information ### Dataset Curators This dataset is the result of the collaborative work of Indonesian researchers from the University of Indonesia, Mohamed bin Zayed University of Artificial Intelligence, and the Korea Advanced Institute of Science & Technology. ### Licensing Information The license is Unknown. Please contact authors for any information on the dataset.
yuyijiong/Book_Summary_Chinese	--- license: cc-by-nc-4.0 task_categories: - text-generation language: - zh size_categories: - 1K<n<10K --- # 中文图书总结数据集每个样本包含： <font color=red> 图书的一个章节、此章节的总结、图书名字</font>，可以训练模型总结长文本的能力。\ 数据主要来自较为著名的中文版小说。
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/f1e9865c	--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 180 num_examples: 10 download_size: 1340 dataset_size: 180 --- # Dataset Card for "f1e9865c" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Swati1981/ETHICS-IN-LIFE	--- license: apache-2.0 ---
rajuptvs/English-to-hindi-podcast-translation	--- dataset_info: features: - name: video_id dtype: string - name: English subtitles dtype: string - name: Hindi subtitles dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1827416 num_examples: 11427 download_size: 784942 dataset_size: 1827416 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "en-hi" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
jinwoos/cartoonizer-dataset-640	--- dataset_info: features: - name: original_image dtype: image - name: edit_prompt dtype: string - name: cartoonized_image dtype: image splits: - name: train num_bytes: 11462200198.0 num_examples: 740 download_size: 11461609579 dataset_size: 11462200198.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
404NotF0und/MtG-json-to-ForgeScript	--- license: mit ---
Aremstrom/llama2_prompt_template_for_ChrisHayduk_Llama-2-SQL-Dataset	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 991555 num_examples: 2000 download_size: 235903 dataset_size: 991555 configs: - config_name: default data_files: - split: train path: data/train-* ---
HugNetw0rk/Ucenie02_Embedding	--- license: other ---
CyberHarem/tsukimi_eiko_paripikoumei	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Tsukimi Eiko This is the dataset of Tsukimi Eiko, containing 299 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). \| Name \| Images \| Download \| Description \| \|:------------\|---------:\|:------------------------------------\|:-------------------------------------------------------------------------\| \| raw \| 299 \| [Download](dataset-raw.zip) \| Raw data with meta information. \| \| raw-stage3 \| 719 \| [Download](dataset-raw-stage3.zip) \| 3-stage cropped raw data with meta information. \| \| 384x512 \| 299 \| [Download](dataset-384x512.zip) \| 384x512 aligned dataset. \| \| 512x512 \| 299 \| [Download](dataset-512x512.zip) \| 512x512 aligned dataset. \| \| 512x704 \| 299 \| [Download](dataset-512x704.zip) \| 512x704 aligned dataset. \| \| 640x640 \| 299 \| [Download](dataset-640x640.zip) \| 640x640 aligned dataset. \| \| 640x880 \| 299 \| [Download](dataset-640x880.zip) \| 640x880 aligned dataset. \| \| stage3-640 \| 719 \| [Download](dataset-stage3-640.zip) \| 3-stage cropped dataset with the shorter side not exceeding 640 pixels. \| \| stage3-800 \| 719 \| [Download](dataset-stage3-800.zip) \| 3-stage cropped dataset with the shorter side not exceeding 800 pixels. \| \| stage3-1200 \| 719 \| [Download](dataset-stage3-1200.zip) \| 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. \|
Nithees/complete_sherlock_holmes-book	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 3300084 num_examples: 1 download_size: 2276499 dataset_size: 3300084 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "complete_sherlock_holmes-book" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mPLUG/M-Paper	--- license: apache-2.0 ---
AlanRobotics/saiga_tokenized	--- dataset_info: features: - name: labels sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 52968582.0 num_examples: 32688 - name: test num_bytes: 5885398.0 num_examples: 3632 download_size: 20205153 dataset_size: 58853980.0 --- # Dataset Card for "saiga_tokenized" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
quocanh34/test_result_large_data_ver2	--- dataset_info: features: - name: id dtype: string - name: pred_str dtype: string - name: test_norm dtype: string splits: - name: train num_bytes: 208107 num_examples: 1299 download_size: 108997 dataset_size: 208107 --- # Dataset Card for "test_result_large_data_ver2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
MaheshMc2/petcare_sample	--- license: other ---
Sharathhebbar24/BeaverTails_unfiltered	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 185218245 num_examples: 364170 download_size: 97617848 dataset_size: 185218245 configs: - config_name: default data_files: - split: train path: data/train-* license: apache-2.0 task_categories: - text-generation language: - en size_categories: - 10K<n<100K --- # Beaver Tails This is a cleansed version of [PKU-Alignment/BeaverTails](https://huggingface.co/datasets/PKU-Alignment/BeaverTails) It has two version based on the sensitivity ## Filtered ### Usage ```python from datasets import load_dataset dataset = load_dataset("Sharathhebbar24/BeaverTails_filtered", split="train") ``` ## Unfiltered ### Usage ```python from datasets import load_dataset dataset = load_dataset("Sharathhebbar24/BeaverTails_unfiltered", split="train") ```
stauntonjr/dtic_sent	--- dataset_info: features: - name: Accession Number dtype: string - name: Title dtype: string - name: Descriptive Note dtype: string - name: Corporate Author dtype: string - name: Personal Author(s) sequence: string - name: Report Date dtype: string - name: Pagination or Media Count dtype: string - name: Descriptors sequence: string - name: Subject Categories dtype: string - name: Distribution Statement dtype: string - name: fulltext dtype: string - name: cleantext dtype: string - name: sents sequence: string splits: - name: train num_bytes: 6951041151 num_examples: 27425 download_size: 3712549813 dataset_size: 6951041151 --- # Dataset Card for "dtic_sent" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
anan-2024/twitter_dataset_1713094859	--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 134425 num_examples: 360 download_size: 80168 dataset_size: 134425 configs: - config_name: default data_files: - split: train path: data/train-* ---
Ashmal/Preprocessed_ArabicMMLU	--- dataset_info: features: - name: Question dtype: string - name: A dtype: string - name: B dtype: string - name: C dtype: string - name: D dtype: string - name: E dtype: string - name: Answer dtype: string splits: - name: train num_bytes: 3444182 num_examples: 14575 download_size: 1533096 dataset_size: 3444182 configs: - config_name: default data_files: - split: train path: data/train-* ---
Den4ikAI/russian_dialogues_2	--- license: mit task_categories: - conversational - text-generation - text2text-generation language: - ru size_categories: - 1M<n<10M --- ### Den4ikAI/russian_dialogues_2 Датасет русских диалогов для обучения диалоговых моделей. Количество диалогов - 1.6 миллиона Формат датасета: ``` { 'sample': ['Привет', 'Привет', 'Как дела?'] } ``` ### Citation: ``` @MISC{russian_instructions, author = {Denis Petrov}, title = {Russian context dialogues dataset for conversational agents}, url = {https://huggingface.co/datasets/Den4ikAI/russian_dialogues_2}, year = 2023 } ```
Apinapi/Lucas12	--- license: openrail ---
distilled-from-one-sec-cv12/chunk_176	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1282989736 num_examples: 249998 download_size: 1310567103 dataset_size: 1282989736 --- # Dataset Card for "chunk_176" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
arubenruben/brazilian_senate_speeches	--- dataset_info: features: - name: text dtype: string - name: label dtype: class_label: names: '0': pt-PT '1': pt-BR splits: - name: train num_bytes: 8433586.765427053 num_examples: 3915 - name: test num_bytes: 2108935.2345729466 num_examples: 979 download_size: 6066217 dataset_size: 10542522.0 --- # Dataset Card for "brazilian_senate_speeches_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
DragonLine/ksponspeech_03_preprocess	--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 95285021616 num_examples: 99200 - name: test num_bytes: 11910618728 num_examples: 12400 - name: valid num_bytes: 11910635984 num_examples: 12400 download_size: 23741227475 dataset_size: 119106276328 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* ---
anjelammcgraw/collegeessays	--- license: apache-2.0 ---
huggingartists/yung-plague	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/yung-plague" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.109415 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/6c0f8e02f467c694379f242ea2897efd.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/yung-plague"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Yung Plague</div> <a href="https://genius.com/artists/yung-plague"> <div style="text-align: center; font-size: 14px;">@yung-plague</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/yung-plague). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/yung-plague") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|38\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/yung-plague") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)
tinyBenchmarks/tinyHellaswag	--- dataset_info: features: - name: ind dtype: int32 - name: activity_label dtype: string - name: ctx_a dtype: string - name: ctx_b dtype: string - name: ctx dtype: string - name: endings sequence: string - name: source_id dtype: string - name: split dtype: string - name: split_type dtype: string - name: label dtype: string - name: input_formatted dtype: string splits: - name: train num_bytes: 160899446 num_examples: 39905 - name: test num_bytes: 40288101 num_examples: 10003 - name: validation num_bytes: 473652 num_examples: 100 download_size: 50109798 dataset_size: 201661199 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* language: - en pretty_name: tinyHellaswag size_categories: - n<1K multilinguality: - monolingual source_datasets: - Rowan/hellaswag language_bcp47: - en-US --- # tinyHellaswag Welcome to tinyHellaswag! This dataset serves as a concise version of the [hellaswag](https://huggingface.co/datasets/hellaswag) dataset, offering a subset of 100 data points selected from the original compilation. tinyHellaswag is designed to enable users to efficiently estimate the performance of a large language model (LLM) with reduced dataset size, saving computational resources while maintaining the essence of the hellaswag evaluation. ## Features - Compact Dataset: With only 100 data points, tinyHellaswag provides a swift and efficient way to evaluate your LLM's performance against a benchmark set, maintaining the essence of the original hellaswag dataset. - Compatibility: tinyHellaswag is compatible with evaluation using the [lm evaluation harness](https://github.com/EleutherAI/lm-evaluation-harness/), but can also be integrated into your custom pipeline. See below for more details. ## Model Evaluation Users looking to evaluate a new model with tinyHellaswag can use the [lm evaluation harness (v0.4.1 or later)](https://github.com/EleutherAI/lm-evaluation-harness/). Simply replace `dataset_path: hellaswag` with `dataset_path: tinyBenchmarks/tinyHellaswag` in the file `lm-evaluation-harness/lm_eval/tasks/hellaswag/hellaswag.yaml` and run your evaluation harness as usual, using the `--log_samples` argument: ```shell lm_eval --model hf --model_args pretrained="<your-model>" --tasks=hellaswag --batch_size=1 --num_fewshot 10 --output_path=<output_path> --log_samples ``` Alternatively, the tinyHellaswag can be integrated into any other pipeline by downloading the data via ```python from datasets import load_dataset tiny_data = load_dataset('tinyBenchmarks/tinyHellaswag')['validation'] ``` Now, `tiny_data` contains the 100 subsampled data points with the same features as the original dataset, as well as an additional field containing the preformatted data points. The preformatted data points follow the formatting used in the [open llm leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) including the respective in-context examples. When using the lm evaluation harness, you can then estimate your LLM's performance using the following code. First, ensure you have the tinyBenchmarks package installed: ```shell pip install git+https://github.com/felipemaiapolo/tinyBenchmarks ``` Then, use the code snippet below for the evaluation: ```python import numpy as np import tinyBenchmarks as tb ### Score vector y = # your original score vector ### Parameters benchmark = 'hellaswag' ### Evaluation tb.evaluate(y, benchmark) ``` This process will help you estimate the performance of your LLM against the tinyHellaswag dataset, providing a streamlined approach to benchmarking. Please be aware that evaluating on multiple GPUs can change the order of outputs in the lm evaluation harness. Ordering your score vector following the original order in tinyHellaswag will be necessary to use the tinyBenchmarks library. For more detailed instructions on evaluating new models and computing scores, please refer to the comprehensive guides available at [lm evaluation harness](https://github.com/EleutherAI/lm-evaluation-harness/) and [tinyBenchmarks GitHub](https://github.com/felipemaiapolo/tinyBenchmarks). Happy benchmarking! ## More tinyBenchmarks Open LLM leaderboard: [tiny MMLU](https://huggingface.co/datasets/tinyBenchmarks/tinyMMLU), [tiny Arc-Challenge](https://huggingface.co/datasets/tinyBenchmarks/tinyAI2_arc), [tiny Winogrande](https://huggingface.co/datasets/tinyBenchmarks/tinyWinogrande), [tiny TruthfulQA](https://huggingface.co/datasets/tinyBenchmarks/tinyTruthfulQA), [tiny GSM8k](https://huggingface.co/datasets/tinyBenchmarks/tinyGSM8k) AlpacaEval: [tiny AlpacaEval](https://huggingface.co/datasets/tinyBenchmarks/tinyAlpacaEval) HELM-lite: _work-in-progress_ ## Citation @article{polo2024tinybenchmarks, title={tinyBenchmarks: evaluating LLMs with fewer examples}, author={Felipe Maia Polo and Lucas Weber and Leshem Choshen and Yuekai Sun and Gongjun Xu and Mikhail Yurochkin}, year={2024}, eprint={2402.14992}, archivePrefix={arXiv}, primaryClass={cs.CL} } @inproceedings{zellers2019hellaswag, title={HellaSwag: Can a Machine Really Finish Your Sentence?}, author={Zellers, Rowan and Holtzman, Ari and Bisk, Yonatan and Farhadi, Ali and Choi, Yejin}, booktitle ={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics}, year={2019} }
open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1	--- pretty_name: Evaluation run of HuggingFaceH4/zephyr-7b-gemma-v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [HuggingFaceH4/zephyr-7b-gemma-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-02T04:15:22.465767](https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1/blob/main/results_2024-03-02T04-15-22.465767.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6064698705754529,\n\ \ \"acc_stderr\": 0.03312365418757596,\n \"acc_norm\": 0.6103117238998753,\n\ \ \"acc_norm_stderr\": 0.03378577550936012,\n \"mc1\": 0.3525091799265606,\n\ \ \"mc1_stderr\": 0.016724646380756547,\n \"mc2\": 0.5207310735270693,\n\ \ \"mc2_stderr\": 0.01596371997542123\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5563139931740614,\n \"acc_stderr\": 0.014518421825670444,\n\ \ \"acc_norm\": 0.5844709897610921,\n \"acc_norm_stderr\": 0.014401366641216384\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6516630153355906,\n\ \ \"acc_stderr\": 0.004754697013354955,\n \"acc_norm\": 0.8347938657637921,\n\ \ \"acc_norm_stderr\": 0.003706075184380285\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932267,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932267\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5481481481481482,\n\ \ \"acc_stderr\": 0.04299268905480864,\n \"acc_norm\": 0.5481481481481482,\n\ \ \"acc_norm_stderr\": 0.04299268905480864\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7171052631578947,\n \"acc_stderr\": 0.03665349695640767,\n\ \ \"acc_norm\": 0.7171052631578947,\n \"acc_norm_stderr\": 0.03665349695640767\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.62,\n\ \ \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n \ \ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6075471698113207,\n \"acc_stderr\": 0.03005258057955784,\n\ \ \"acc_norm\": 0.6075471698113207,\n \"acc_norm_stderr\": 0.03005258057955784\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7361111111111112,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.7361111111111112,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \ \ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.51,\n\ \ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6127167630057804,\n\ \ \"acc_stderr\": 0.03714325906302065,\n \"acc_norm\": 0.6127167630057804,\n\ \ \"acc_norm_stderr\": 0.03714325906302065\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.39215686274509803,\n \"acc_stderr\": 0.048580835742663454,\n\ \ \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.048580835742663454\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108102,\n\ \ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108102\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.40350877192982454,\n\ \ \"acc_stderr\": 0.046151869625837026,\n \"acc_norm\": 0.40350877192982454,\n\ \ \"acc_norm_stderr\": 0.046151869625837026\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6275862068965518,\n \"acc_stderr\": 0.04028731532947558,\n\ \ \"acc_norm\": 0.6275862068965518,\n \"acc_norm_stderr\": 0.04028731532947558\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.4470899470899471,\n \"acc_stderr\": 0.025606723995777028,\n \"\ acc_norm\": 0.4470899470899471,\n \"acc_norm_stderr\": 0.025606723995777028\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.7451612903225806,\n \"acc_stderr\": 0.024790118459332208,\n \"\ acc_norm\": 0.7451612903225806,\n \"acc_norm_stderr\": 0.024790118459332208\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.47783251231527096,\n \"acc_stderr\": 0.035145285621750094,\n \"\ acc_norm\": 0.47783251231527096,\n \"acc_norm_stderr\": 0.035145285621750094\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\"\ : 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7151515151515152,\n \"acc_stderr\": 0.03524390844511781,\n\ \ \"acc_norm\": 0.7151515151515152,\n \"acc_norm_stderr\": 0.03524390844511781\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8131313131313131,\n \"acc_stderr\": 0.027772533334218964,\n \"\ acc_norm\": 0.8131313131313131,\n \"acc_norm_stderr\": 0.027772533334218964\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8497409326424871,\n \"acc_stderr\": 0.02578772318072388,\n\ \ \"acc_norm\": 0.8497409326424871,\n \"acc_norm_stderr\": 0.02578772318072388\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5897435897435898,\n \"acc_stderr\": 0.02493931390694079,\n \ \ \"acc_norm\": 0.5897435897435898,\n \"acc_norm_stderr\": 0.02493931390694079\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.362962962962963,\n \"acc_stderr\": 0.029318203645206868,\n \ \ \"acc_norm\": 0.362962962962963,\n \"acc_norm_stderr\": 0.029318203645206868\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6134453781512605,\n \"acc_stderr\": 0.0316314580755238,\n \ \ \"acc_norm\": 0.6134453781512605,\n \"acc_norm_stderr\": 0.0316314580755238\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.039291117812427424,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.039291117812427424\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8146788990825689,\n \"acc_stderr\": 0.016659279700295827,\n \"\ acc_norm\": 0.8146788990825689,\n \"acc_norm_stderr\": 0.016659279700295827\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7696078431372549,\n \"acc_stderr\": 0.029554292605695066,\n \"\ acc_norm\": 0.7696078431372549,\n \"acc_norm_stderr\": 0.029554292605695066\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7974683544303798,\n \"acc_stderr\": 0.026160568246601436,\n \ \ \"acc_norm\": 0.7974683544303798,\n \"acc_norm_stderr\": 0.026160568246601436\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6816143497757847,\n\ \ \"acc_stderr\": 0.03126580522513713,\n \"acc_norm\": 0.6816143497757847,\n\ \ \"acc_norm_stderr\": 0.03126580522513713\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.5801526717557252,\n \"acc_stderr\": 0.043285772152629715,\n\ \ \"acc_norm\": 0.5801526717557252,\n \"acc_norm_stderr\": 0.043285772152629715\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7314814814814815,\n\ \ \"acc_stderr\": 0.042844679680521934,\n \"acc_norm\": 0.7314814814814815,\n\ \ \"acc_norm_stderr\": 0.042844679680521934\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7239263803680982,\n \"acc_stderr\": 0.035123852837050475,\n\ \ \"acc_norm\": 0.7239263803680982,\n \"acc_norm_stderr\": 0.035123852837050475\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4375,\n\ \ \"acc_stderr\": 0.04708567521880525,\n \"acc_norm\": 0.4375,\n \ \ \"acc_norm_stderr\": 0.04708567521880525\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.03989139859531771,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.03989139859531771\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8589743589743589,\n\ \ \"acc_stderr\": 0.022801382534597542,\n \"acc_norm\": 0.8589743589743589,\n\ \ \"acc_norm_stderr\": 0.022801382534597542\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7790549169859514,\n\ \ \"acc_stderr\": 0.014836205167333562,\n \"acc_norm\": 0.7790549169859514,\n\ \ \"acc_norm_stderr\": 0.014836205167333562\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6242774566473989,\n \"acc_stderr\": 0.02607431485165708,\n\ \ \"acc_norm\": 0.6242774566473989,\n \"acc_norm_stderr\": 0.02607431485165708\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.22569832402234638,\n\ \ \"acc_stderr\": 0.013981395058455066,\n \"acc_norm\": 0.22569832402234638,\n\ \ \"acc_norm_stderr\": 0.013981395058455066\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6568627450980392,\n \"acc_stderr\": 0.027184498909941616,\n\ \ \"acc_norm\": 0.6568627450980392,\n \"acc_norm_stderr\": 0.027184498909941616\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6495176848874598,\n\ \ \"acc_stderr\": 0.02709865262130175,\n \"acc_norm\": 0.6495176848874598,\n\ \ \"acc_norm_stderr\": 0.02709865262130175\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7006172839506173,\n \"acc_stderr\": 0.025483115601195448,\n\ \ \"acc_norm\": 0.7006172839506173,\n \"acc_norm_stderr\": 0.025483115601195448\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.450354609929078,\n \"acc_stderr\": 0.029680105565029036,\n \ \ \"acc_norm\": 0.450354609929078,\n \"acc_norm_stderr\": 0.029680105565029036\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.470013037809648,\n\ \ \"acc_stderr\": 0.012747248967079051,\n \"acc_norm\": 0.470013037809648,\n\ \ \"acc_norm_stderr\": 0.012747248967079051\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5735294117647058,\n \"acc_stderr\": 0.03004261583271486,\n\ \ \"acc_norm\": 0.5735294117647058,\n \"acc_norm_stderr\": 0.03004261583271486\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6111111111111112,\n \"acc_stderr\": 0.01972205893961807,\n \ \ \"acc_norm\": 0.6111111111111112,\n \"acc_norm_stderr\": 0.01972205893961807\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.689795918367347,\n \"acc_stderr\": 0.029613459872484375,\n\ \ \"acc_norm\": 0.689795918367347,\n \"acc_norm_stderr\": 0.029613459872484375\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.7412935323383084,\n\ \ \"acc_stderr\": 0.030965903123573026,\n \"acc_norm\": 0.7412935323383084,\n\ \ \"acc_norm_stderr\": 0.030965903123573026\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.8,\n \"acc_stderr\": 0.04020151261036843,\n \ \ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.04020151261036843\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7953216374269005,\n \"acc_stderr\": 0.030944459778533207,\n\ \ \"acc_norm\": 0.7953216374269005,\n \"acc_norm_stderr\": 0.030944459778533207\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3525091799265606,\n\ \ \"mc1_stderr\": 0.016724646380756547,\n \"mc2\": 0.5207310735270693,\n\ \ \"mc2_stderr\": 0.01596371997542123\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7419100236779794,\n \"acc_stderr\": 0.012298278833972387\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.45564821834723274,\n \ \ \"acc_stderr\": 0.013718194542485596\n }\n}\n```" repo_url: https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|arc:challenge\|25_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|arc:challenge\|25_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-02T04-15-22.465767.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|gsm8k\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|gsm8k\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hellaswag\|10_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hellaswag\|10_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-02T00-16-56.064220.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-02T04-15-22.465767.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-02T04-15-22.465767.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '/details_harness\|winogrande\|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '/details_harness\|winogrande\|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-02T04-15-22.465767.parquet' - config_name: results data_files: - split: 2024_03_02T00_16_56.064220 path: - results_2024-03-02T00-16-56.064220.parquet - split: 2024_03_02T04_15_22.465767 path: - results_2024-03-02T04-15-22.465767.parquet - split: latest path: - results_2024-03-02T04-15-22.465767.parquet --- # Dataset Card for Evaluation run of HuggingFaceH4/zephyr-7b-gemma-v0.1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [HuggingFaceH4/zephyr-7b-gemma-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-02T04:15:22.465767](https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1/blob/main/results_2024-03-02T04-15-22.465767.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6064698705754529, "acc_stderr": 0.03312365418757596, "acc_norm": 0.6103117238998753, "acc_norm_stderr": 0.03378577550936012, "mc1": 0.3525091799265606, "mc1_stderr": 0.016724646380756547, "mc2": 0.5207310735270693, "mc2_stderr": 0.01596371997542123 }, "harness\|arc:challenge\|25": { "acc": 0.5563139931740614, "acc_stderr": 0.014518421825670444, "acc_norm": 0.5844709897610921, "acc_norm_stderr": 0.014401366641216384 }, "harness\|hellaswag\|10": { "acc": 0.6516630153355906, "acc_stderr": 0.004754697013354955, "acc_norm": 0.8347938657637921, "acc_norm_stderr": 0.003706075184380285 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.22, "acc_stderr": 0.04163331998932267, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932267 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5481481481481482, "acc_stderr": 0.04299268905480864, "acc_norm": 0.5481481481481482, "acc_norm_stderr": 0.04299268905480864 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7171052631578947, "acc_stderr": 0.03665349695640767, "acc_norm": 0.7171052631578947, "acc_norm_stderr": 0.03665349695640767 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6075471698113207, "acc_stderr": 0.03005258057955784, "acc_norm": 0.6075471698113207, "acc_norm_stderr": 0.03005258057955784 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7361111111111112, "acc_stderr": 0.03685651095897532, "acc_norm": 0.7361111111111112, "acc_norm_stderr": 0.03685651095897532 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6127167630057804, "acc_stderr": 0.03714325906302065, "acc_norm": 0.6127167630057804, "acc_norm_stderr": 0.03714325906302065 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.39215686274509803, "acc_stderr": 0.048580835742663454, "acc_norm": 0.39215686274509803, "acc_norm_stderr": 0.048580835742663454 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5617021276595745, "acc_stderr": 0.03243618636108102, "acc_norm": 0.5617021276595745, "acc_norm_stderr": 0.03243618636108102 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.40350877192982454, "acc_stderr": 0.046151869625837026, "acc_norm": 0.40350877192982454, "acc_norm_stderr": 0.046151869625837026 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6275862068965518, "acc_stderr": 0.04028731532947558, "acc_norm": 0.6275862068965518, "acc_norm_stderr": 0.04028731532947558 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4470899470899471, "acc_stderr": 0.025606723995777028, "acc_norm": 0.4470899470899471, "acc_norm_stderr": 0.025606723995777028 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7451612903225806, "acc_stderr": 0.024790118459332208, "acc_norm": 0.7451612903225806, "acc_norm_stderr": 0.024790118459332208 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.47783251231527096, "acc_stderr": 0.035145285621750094, "acc_norm": 0.47783251231527096, "acc_norm_stderr": 0.035145285621750094 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7151515151515152, "acc_stderr": 0.03524390844511781, "acc_norm": 0.7151515151515152, "acc_norm_stderr": 0.03524390844511781 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8131313131313131, "acc_stderr": 0.027772533334218964, "acc_norm": 0.8131313131313131, "acc_norm_stderr": 0.027772533334218964 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8497409326424871, "acc_stderr": 0.02578772318072388, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.02578772318072388 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5897435897435898, "acc_stderr": 0.02493931390694079, "acc_norm": 0.5897435897435898, "acc_norm_stderr": 0.02493931390694079 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.362962962962963, "acc_stderr": 0.029318203645206868, "acc_norm": 0.362962962962963, "acc_norm_stderr": 0.029318203645206868 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6134453781512605, "acc_stderr": 0.0316314580755238, "acc_norm": 0.6134453781512605, "acc_norm_stderr": 0.0316314580755238 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.36423841059602646, "acc_stderr": 0.039291117812427424, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.039291117812427424 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8146788990825689, "acc_stderr": 0.016659279700295827, "acc_norm": 0.8146788990825689, "acc_norm_stderr": 0.016659279700295827 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7696078431372549, "acc_stderr": 0.029554292605695066, "acc_norm": 0.7696078431372549, "acc_norm_stderr": 0.029554292605695066 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7974683544303798, "acc_stderr": 0.026160568246601436, "acc_norm": 0.7974683544303798, "acc_norm_stderr": 0.026160568246601436 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6816143497757847, "acc_stderr": 0.03126580522513713, "acc_norm": 0.6816143497757847, "acc_norm_stderr": 0.03126580522513713 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.5801526717557252, "acc_stderr": 0.043285772152629715, "acc_norm": 0.5801526717557252, "acc_norm_stderr": 0.043285772152629715 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228732, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228732 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7314814814814815, "acc_stderr": 0.042844679680521934, "acc_norm": 0.7314814814814815, "acc_norm_stderr": 0.042844679680521934 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7239263803680982, "acc_stderr": 0.035123852837050475, "acc_norm": 0.7239263803680982, "acc_norm_stderr": 0.035123852837050475 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4375, "acc_stderr": 0.04708567521880525, "acc_norm": 0.4375, "acc_norm_stderr": 0.04708567521880525 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7961165048543689, "acc_stderr": 0.03989139859531771, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.03989139859531771 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8589743589743589, "acc_stderr": 0.022801382534597542, "acc_norm": 0.8589743589743589, "acc_norm_stderr": 0.022801382534597542 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7790549169859514, "acc_stderr": 0.014836205167333562, "acc_norm": 0.7790549169859514, "acc_norm_stderr": 0.014836205167333562 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6242774566473989, "acc_stderr": 0.02607431485165708, "acc_norm": 0.6242774566473989, "acc_norm_stderr": 0.02607431485165708 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.22569832402234638, "acc_stderr": 0.013981395058455066, "acc_norm": 0.22569832402234638, "acc_norm_stderr": 0.013981395058455066 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6568627450980392, "acc_stderr": 0.027184498909941616, "acc_norm": 0.6568627450980392, "acc_norm_stderr": 0.027184498909941616 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6495176848874598, "acc_stderr": 0.02709865262130175, "acc_norm": 0.6495176848874598, "acc_norm_stderr": 0.02709865262130175 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7006172839506173, "acc_stderr": 0.025483115601195448, "acc_norm": 0.7006172839506173, "acc_norm_stderr": 0.025483115601195448 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.450354609929078, "acc_stderr": 0.029680105565029036, "acc_norm": 0.450354609929078, "acc_norm_stderr": 0.029680105565029036 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.470013037809648, "acc_stderr": 0.012747248967079051, "acc_norm": 0.470013037809648, "acc_norm_stderr": 0.012747248967079051 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5735294117647058, "acc_stderr": 0.03004261583271486, "acc_norm": 0.5735294117647058, "acc_norm_stderr": 0.03004261583271486 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6111111111111112, "acc_stderr": 0.01972205893961807, "acc_norm": 0.6111111111111112, "acc_norm_stderr": 0.01972205893961807 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.689795918367347, "acc_stderr": 0.029613459872484375, "acc_norm": 0.689795918367347, "acc_norm_stderr": 0.029613459872484375 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.7412935323383084, "acc_stderr": 0.030965903123573026, "acc_norm": 0.7412935323383084, "acc_norm_stderr": 0.030965903123573026 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.8, "acc_stderr": 0.04020151261036843, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036843 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7953216374269005, "acc_stderr": 0.030944459778533207, "acc_norm": 0.7953216374269005, "acc_norm_stderr": 0.030944459778533207 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3525091799265606, "mc1_stderr": 0.016724646380756547, "mc2": 0.5207310735270693, "mc2_stderr": 0.01596371997542123 }, "harness\|winogrande\|5": { "acc": 0.7419100236779794, "acc_stderr": 0.012298278833972387 }, "harness\|gsm8k\|5": { "acc": 0.45564821834723274, "acc_stderr": 0.013718194542485596 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
Vageesh1/tokenized_contract_hf_selected	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: source_code dtype: string - name: success dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 1722286150 num_examples: 60000 download_size: 522906155 dataset_size: 1722286150 --- # Dataset Card for "tokenized_contract_hf_selected" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Anderson-Andre-P/text-template-to-summarize	--- license: mit task_categories: - summarization language: - pt tags: - code ---
Deivid457/Jennie	--- license: openrail ---
Codec-SUPERB/librispeech_asr_dummy_extract_unit	--- configs: - config_name: default data_files: - split: academicodec_hifi_16k_320d path: data/academicodec_hifi_16k_320d-* - split: academicodec_hifi_16k_320d_large_uni path: data/academicodec_hifi_16k_320d_large_uni-* - split: academicodec_hifi_24k_320d path: data/academicodec_hifi_24k_320d-* - split: audiodec_24k_320d path: data/audiodec_24k_320d-* - split: dac_16k path: data/dac_16k-* - split: dac_24k path: data/dac_24k-* - split: dac_44k path: data/dac_44k-* - split: encodec_24k path: data/encodec_24k-* - split: funcodec_en_libritts_16k_gr1nq32ds320 path: data/funcodec_en_libritts_16k_gr1nq32ds320-* - split: funcodec_en_libritts_16k_gr8nq32ds320 path: data/funcodec_en_libritts_16k_gr8nq32ds320-* - split: funcodec_en_libritts_16k_nq32ds320 path: data/funcodec_en_libritts_16k_nq32ds320-* - split: funcodec_en_libritts_16k_nq32ds640 path: data/funcodec_en_libritts_16k_nq32ds640-* - split: funcodec_zh_en_16k_nq32ds320 path: data/funcodec_zh_en_16k_nq32ds320-* - split: funcodec_zh_en_16k_nq32ds640 path: data/funcodec_zh_en_16k_nq32ds640-* - split: speech_tokenizer_16k path: data/speech_tokenizer_16k-* dataset_info: features: - name: id dtype: string - name: unit sequence: sequence: int64 splits: - name: academicodec_hifi_16k_320d num_bytes: 771752 num_examples: 73 - name: academicodec_hifi_16k_320d_large_uni num_bytes: 771752 num_examples: 73 - name: academicodec_hifi_24k_320d num_bytes: 1156456 num_examples: 73 - name: audiodec_24k_320d num_bytes: 2468728 num_examples: 73 - name: dac_16k num_bytes: 4813128 num_examples: 73 - name: dac_24k num_bytes: 13650008 num_examples: 73 - name: dac_44k num_bytes: 4047900 num_examples: 73 - name: encodec_24k num_bytes: 580208 num_examples: 73 - name: funcodec_en_libritts_16k_gr1nq32ds320 num_bytes: 6180696 num_examples: 73 - name: funcodec_en_libritts_16k_gr8nq32ds320 num_bytes: 6180696 num_examples: 73 - name: funcodec_en_libritts_16k_nq32ds320 num_bytes: 6179160 num_examples: 73 - name: funcodec_en_libritts_16k_nq32ds640 num_bytes: 3100504 num_examples: 73 - name: funcodec_zh_en_16k_nq32ds320 num_bytes: 6179160 num_examples: 73 - name: funcodec_zh_en_16k_nq32ds640 num_bytes: 6179160 num_examples: 73 - name: speech_tokenizer_16k num_bytes: 1546104 num_examples: 73 download_size: 10104884 dataset_size: 63805412 --- # Dataset Card for "librispeech_asr_dummy_extract_unit" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
DragonLine/ksponspeech_04	--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: transcripts dtype: string splits: - name: train num_bytes: 17609433455.2 num_examples: 99200 - name: test num_bytes: 2152518506.7 num_examples: 12400 - name: valid num_bytes: 2326954936.3 num_examples: 12400 download_size: 20778654985 dataset_size: 22088906898.2 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* ---
fathyshalab/massive_takeaway	--- dataset_info: features: - name: id dtype: string - name: label dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 14816 num_examples: 257 - name: validation num_bytes: 2450 num_examples: 44 - name: test num_bytes: 3176 num_examples: 57 download_size: 14963 dataset_size: 20442 --- # Dataset Card for "massive_takeaway" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
matejklemen/wi_locness	--- license: other dataset_info: - config_name: A features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 3847179 num_examples: 10493 - name: validation num_bytes: 392622 num_examples: 1037 download_size: 6120469 dataset_size: 4239801 - config_name: B features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 4649805 num_examples: 13032 - name: validation num_bytes: 468078 num_examples: 1290 download_size: 6120469 dataset_size: 5117883 - config_name: C features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 3765831 num_examples: 10783 - name: validation num_bytes: 390439 num_examples: 1069 download_size: 6120469 dataset_size: 4156270 - config_name: N features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: validation num_bytes: 421656 num_examples: 988 download_size: 6120469 dataset_size: 421656 - config_name: all features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 12262815 num_examples: 34308 - name: validation num_bytes: 1672795 num_examples: 4384 download_size: 6120469 dataset_size: 13935610 ---
HydraLM/partitioned_v3_standardized_026	--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: dataset_id dtype: string - name: unique_id dtype: string splits: - name: train num_bytes: 34048776.63602931 num_examples: 63321 download_size: 5555939 dataset_size: 34048776.63602931 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "partitioned_v3_standardized_026" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Naveengo/sql-create-context-5000rows	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: context dtype: string splits: - name: train num_bytes: 1104644.8706364457 num_examples: 5000 download_size: 548687 dataset_size: 1104644.8706364457 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "sql-create-context-5000rows" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
KDAI-NLP/traffy-fondue-type-only	--- license: mit dataset_info: features: - name: ticket_id dtype: string - name: type dtype: string - name: comment dtype: string - name: timestamp dtype: timestamp[ns] - name: subdistrict dtype: string - name: district dtype: string - name: province dtype: string - name: is_ไม่ระบุ dtype: int64 - name: is_ความสะอาด dtype: int64 - name: is_สายไฟ dtype: int64 - name: is_สะพาน dtype: int64 - name: is_ถนน dtype: int64 - name: is_น้ำท่วม dtype: int64 - name: is_ร้องเรียน dtype: int64 - name: is_ท่อระบายน้ำ dtype: int64 - name: is_ความปลอดภัย dtype: int64 - name: is_คลอง dtype: int64 - name: is_แสงสว่าง dtype: int64 - name: is_ทางเท้า dtype: int64 - name: is_จราจร dtype: int64 - name: is_กีดขวาง dtype: int64 - name: is_การเดินทาง dtype: int64 - name: is_เสียงรบกวน dtype: int64 - name: is_ต้นไม้ dtype: int64 - name: is_สัตว์จรจัด dtype: int64 - name: is_เสนอแนะ dtype: int64 - name: is_คนจรจัด dtype: int64 - name: is_ห้องน้ำ dtype: int64 - name: is_ป้ายจราจร dtype: int64 - name: is_สอบถาม dtype: int64 - name: is_ป้าย dtype: int64 - name: is_PM2.5 dtype: int64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 326026940 num_examples: 406266 download_size: 0 dataset_size: 326026940 configs: - config_name: default data_files: - split: train path: data/train-* ---
bashmanxx/llama45train	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 17198108 num_examples: 13649 download_size: 2106426 dataset_size: 17198108 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3	--- pretty_name: Evaluation run of nlpguy/ColorShadow-7B-v3 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [nlpguy/ColorShadow-7B-v3](https://huggingface.co/nlpguy/ColorShadow-7B-v3) on\ \ the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-04T12:00:00.400283](https://huggingface.co/datasets/open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3/blob/main/results_2024-01-04T12-00-00.400283.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6077756404899893,\n\ \ \"acc_stderr\": 0.0331406868415802,\n \"acc_norm\": 0.6110717172741464,\n\ \ \"acc_norm_stderr\": 0.03381281098512482,\n \"mc1\": 0.45532435740514077,\n\ \ \"mc1_stderr\": 0.017433490102538765,\n \"mc2\": 0.6287894376799671,\n\ \ \"mc2_stderr\": 0.015043355245179869\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6313993174061433,\n \"acc_stderr\": 0.014097810678042196,\n\ \ \"acc_norm\": 0.6757679180887372,\n \"acc_norm_stderr\": 0.013678810399518822\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6394144592710616,\n\ \ \"acc_stderr\": 0.004791890625834189,\n \"acc_norm\": 0.8504282015534754,\n\ \ \"acc_norm_stderr\": 0.0035592230156104953\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5555555555555556,\n\ \ \"acc_stderr\": 0.04292596718256981,\n \"acc_norm\": 0.5555555555555556,\n\ \ \"acc_norm_stderr\": 0.04292596718256981\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.0373852067611967,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.0373852067611967\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.54,\n\ \ \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.54,\n \ \ \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6867924528301886,\n \"acc_stderr\": 0.028544793319055326,\n\ \ \"acc_norm\": 0.6867924528301886,\n \"acc_norm_stderr\": 0.028544793319055326\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.46,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107223,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107223\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768079,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768079\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5404255319148936,\n \"acc_stderr\": 0.03257901482099835,\n\ \ \"acc_norm\": 0.5404255319148936,\n \"acc_norm_stderr\": 0.03257901482099835\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4298245614035088,\n\ \ \"acc_stderr\": 0.04657047260594963,\n \"acc_norm\": 0.4298245614035088,\n\ \ \"acc_norm_stderr\": 0.04657047260594963\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5793103448275863,\n \"acc_stderr\": 0.0411391498118926,\n\ \ \"acc_norm\": 0.5793103448275863,\n \"acc_norm_stderr\": 0.0411391498118926\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3968253968253968,\n \"acc_stderr\": 0.02519710107424648,\n \"\ acc_norm\": 0.3968253968253968,\n \"acc_norm_stderr\": 0.02519710107424648\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3888888888888889,\n\ \ \"acc_stderr\": 0.04360314860077459,\n \"acc_norm\": 0.3888888888888889,\n\ \ \"acc_norm_stderr\": 0.04360314860077459\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.6838709677419355,\n\ \ \"acc_stderr\": 0.026450874489042764,\n \"acc_norm\": 0.6838709677419355,\n\ \ \"acc_norm_stderr\": 0.026450874489042764\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4876847290640394,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.4876847290640394,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.703030303030303,\n \"acc_stderr\": 0.03567969772268049,\n\ \ \"acc_norm\": 0.703030303030303,\n \"acc_norm_stderr\": 0.03567969772268049\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7474747474747475,\n \"acc_stderr\": 0.030954055470365907,\n \"\ acc_norm\": 0.7474747474747475,\n \"acc_norm_stderr\": 0.030954055470365907\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8497409326424871,\n \"acc_stderr\": 0.025787723180723886,\n\ \ \"acc_norm\": 0.8497409326424871,\n \"acc_norm_stderr\": 0.025787723180723886\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6256410256410256,\n \"acc_stderr\": 0.024537591572830506,\n\ \ \"acc_norm\": 0.6256410256410256,\n \"acc_norm_stderr\": 0.024537591572830506\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3296296296296296,\n \"acc_stderr\": 0.028661201116524575,\n \ \ \"acc_norm\": 0.3296296296296296,\n \"acc_norm_stderr\": 0.028661201116524575\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6470588235294118,\n \"acc_stderr\": 0.031041941304059285,\n\ \ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.031041941304059285\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3509933774834437,\n \"acc_stderr\": 0.03896981964257375,\n \"\ acc_norm\": 0.3509933774834437,\n \"acc_norm_stderr\": 0.03896981964257375\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8091743119266055,\n \"acc_stderr\": 0.016847676400091095,\n \"\ acc_norm\": 0.8091743119266055,\n \"acc_norm_stderr\": 0.016847676400091095\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.44907407407407407,\n \"acc_stderr\": 0.03392238405321616,\n \"\ acc_norm\": 0.44907407407407407,\n \"acc_norm_stderr\": 0.03392238405321616\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7254901960784313,\n \"acc_stderr\": 0.03132179803083289,\n \"\ acc_norm\": 0.7254901960784313,\n \"acc_norm_stderr\": 0.03132179803083289\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7721518987341772,\n \"acc_stderr\": 0.027303484599069422,\n \ \ \"acc_norm\": 0.7721518987341772,\n \"acc_norm_stderr\": 0.027303484599069422\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7175572519083969,\n \"acc_stderr\": 0.03948406125768361,\n\ \ \"acc_norm\": 0.7175572519083969,\n \"acc_norm_stderr\": 0.03948406125768361\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7933884297520661,\n \"acc_stderr\": 0.03695980128098825,\n \"\ acc_norm\": 0.7933884297520661,\n \"acc_norm_stderr\": 0.03695980128098825\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.04236511258094633,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.04236511258094633\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7116564417177914,\n \"acc_stderr\": 0.03559039531617342,\n\ \ \"acc_norm\": 0.7116564417177914,\n \"acc_norm_stderr\": 0.03559039531617342\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.44642857142857145,\n\ \ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\ \ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7184466019417476,\n \"acc_stderr\": 0.044532548363264673,\n\ \ \"acc_norm\": 0.7184466019417476,\n \"acc_norm_stderr\": 0.044532548363264673\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406978,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406978\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7816091954022989,\n\ \ \"acc_stderr\": 0.014774358319934495,\n \"acc_norm\": 0.7816091954022989,\n\ \ \"acc_norm_stderr\": 0.014774358319934495\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7052023121387283,\n \"acc_stderr\": 0.024547617794803828,\n\ \ \"acc_norm\": 0.7052023121387283,\n \"acc_norm_stderr\": 0.024547617794803828\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.36089385474860336,\n\ \ \"acc_stderr\": 0.01606229067111047,\n \"acc_norm\": 0.36089385474860336,\n\ \ \"acc_norm_stderr\": 0.01606229067111047\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6633986928104575,\n \"acc_stderr\": 0.02705797462449438,\n\ \ \"acc_norm\": 0.6633986928104575,\n \"acc_norm_stderr\": 0.02705797462449438\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.684887459807074,\n\ \ \"acc_stderr\": 0.026385273703464496,\n \"acc_norm\": 0.684887459807074,\n\ \ \"acc_norm_stderr\": 0.026385273703464496\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6635802469135802,\n \"acc_stderr\": 0.02628973494595293,\n\ \ \"acc_norm\": 0.6635802469135802,\n \"acc_norm_stderr\": 0.02628973494595293\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \ \ \"acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.43089960886571055,\n\ \ \"acc_stderr\": 0.012647695889547228,\n \"acc_norm\": 0.43089960886571055,\n\ \ \"acc_norm_stderr\": 0.012647695889547228\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5661764705882353,\n \"acc_stderr\": 0.030105636570016633,\n\ \ \"acc_norm\": 0.5661764705882353,\n \"acc_norm_stderr\": 0.030105636570016633\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6405228758169934,\n \"acc_stderr\": 0.019412539242032168,\n \ \ \"acc_norm\": 0.6405228758169934,\n \"acc_norm_stderr\": 0.019412539242032168\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6938775510204082,\n \"acc_stderr\": 0.029504896454595957,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.029504896454595957\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.6766169154228856,\n\ \ \"acc_stderr\": 0.03307615947979033,\n \"acc_norm\": 0.6766169154228856,\n\ \ \"acc_norm_stderr\": 0.03307615947979033\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.82,\n \"acc_stderr\": 0.03861229196653693,\n \ \ \"acc_norm\": 0.82,\n \"acc_norm_stderr\": 0.03861229196653693\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5,\n \ \ \"acc_stderr\": 0.03892494720807614,\n \"acc_norm\": 0.5,\n \"\ acc_norm_stderr\": 0.03892494720807614\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.02954774168764004,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.02954774168764004\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.45532435740514077,\n\ \ \"mc1_stderr\": 0.017433490102538765,\n \"mc2\": 0.6287894376799671,\n\ \ \"mc2_stderr\": 0.015043355245179869\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8011049723756906,\n \"acc_stderr\": 0.011218629972515302\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.47536012130401817,\n \ \ \"acc_stderr\": 0.013755751352764918\n }\n}\n```" repo_url: https://huggingface.co/nlpguy/ColorShadow-7B-v3 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|arc:challenge\|25_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-04T12-00-00.400283.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|gsm8k\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hellaswag\|10_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-04T12-00-00.400283.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-04T12-00-00.400283.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '/details_harness\|winogrande\|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-04T12-00-00.400283.parquet' - config_name: results data_files: - split: 2024_01_04T12_00_00.400283 path: - results_2024-01-04T12-00-00.400283.parquet - split: latest path: - results_2024-01-04T12-00-00.400283.parquet --- # Dataset Card for Evaluation run of nlpguy/ColorShadow-7B-v3 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [nlpguy/ColorShadow-7B-v3](https://huggingface.co/nlpguy/ColorShadow-7B-v3) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-04T12:00:00.400283](https://huggingface.co/datasets/open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3/blob/main/results_2024-01-04T12-00-00.400283.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6077756404899893, "acc_stderr": 0.0331406868415802, "acc_norm": 0.6110717172741464, "acc_norm_stderr": 0.03381281098512482, "mc1": 0.45532435740514077, "mc1_stderr": 0.017433490102538765, "mc2": 0.6287894376799671, "mc2_stderr": 0.015043355245179869 }, "harness\|arc:challenge\|25": { "acc": 0.6313993174061433, "acc_stderr": 0.014097810678042196, "acc_norm": 0.6757679180887372, "acc_norm_stderr": 0.013678810399518822 }, "harness\|hellaswag\|10": { "acc": 0.6394144592710616, "acc_stderr": 0.004791890625834189, "acc_norm": 0.8504282015534754, "acc_norm_stderr": 0.0035592230156104953 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5555555555555556, "acc_stderr": 0.04292596718256981, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.04292596718256981 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6973684210526315, "acc_stderr": 0.0373852067611967, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.0373852067611967 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6867924528301886, "acc_stderr": 0.028544793319055326, "acc_norm": 0.6867924528301886, "acc_norm_stderr": 0.028544793319055326 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7222222222222222, "acc_stderr": 0.037455547914624555, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.037455547914624555 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5404255319148936, "acc_stderr": 0.03257901482099835, "acc_norm": 0.5404255319148936, "acc_norm_stderr": 0.03257901482099835 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4298245614035088, "acc_stderr": 0.04657047260594963, "acc_norm": 0.4298245614035088, "acc_norm_stderr": 0.04657047260594963 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5793103448275863, "acc_stderr": 0.0411391498118926, "acc_norm": 0.5793103448275863, "acc_norm_stderr": 0.0411391498118926 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3968253968253968, "acc_stderr": 0.02519710107424648, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.02519710107424648 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.04360314860077459, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.04360314860077459 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.6838709677419355, "acc_stderr": 0.026450874489042764, "acc_norm": 0.6838709677419355, "acc_norm_stderr": 0.026450874489042764 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4876847290640394, "acc_stderr": 0.035169204442208966, "acc_norm": 0.4876847290640394, "acc_norm_stderr": 0.035169204442208966 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.703030303030303, "acc_stderr": 0.03567969772268049, "acc_norm": 0.703030303030303, "acc_norm_stderr": 0.03567969772268049 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7474747474747475, "acc_stderr": 0.030954055470365907, "acc_norm": 0.7474747474747475, "acc_norm_stderr": 0.030954055470365907 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8497409326424871, "acc_stderr": 0.025787723180723886, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.025787723180723886 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6256410256410256, "acc_stderr": 0.024537591572830506, "acc_norm": 0.6256410256410256, "acc_norm_stderr": 0.024537591572830506 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3296296296296296, "acc_stderr": 0.028661201116524575, "acc_norm": 0.3296296296296296, "acc_norm_stderr": 0.028661201116524575 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6470588235294118, "acc_stderr": 0.031041941304059285, "acc_norm": 0.6470588235294118, "acc_norm_stderr": 0.031041941304059285 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3509933774834437, "acc_stderr": 0.03896981964257375, "acc_norm": 0.3509933774834437, "acc_norm_stderr": 0.03896981964257375 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8091743119266055, "acc_stderr": 0.016847676400091095, "acc_norm": 0.8091743119266055, "acc_norm_stderr": 0.016847676400091095 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.44907407407407407, "acc_stderr": 0.03392238405321616, "acc_norm": 0.44907407407407407, "acc_norm_stderr": 0.03392238405321616 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7254901960784313, "acc_stderr": 0.03132179803083289, "acc_norm": 0.7254901960784313, "acc_norm_stderr": 0.03132179803083289 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7721518987341772, "acc_stderr": 0.027303484599069422, "acc_norm": 0.7721518987341772, "acc_norm_stderr": 0.027303484599069422 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7175572519083969, "acc_stderr": 0.03948406125768361, "acc_norm": 0.7175572519083969, "acc_norm_stderr": 0.03948406125768361 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7933884297520661, "acc_stderr": 0.03695980128098825, "acc_norm": 0.7933884297520661, "acc_norm_stderr": 0.03695980128098825 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7407407407407407, "acc_stderr": 0.04236511258094633, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.04236511258094633 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7116564417177914, "acc_stderr": 0.03559039531617342, "acc_norm": 0.7116564417177914, "acc_norm_stderr": 0.03559039531617342 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.44642857142857145, "acc_stderr": 0.04718471485219588, "acc_norm": 0.44642857142857145, "acc_norm_stderr": 0.04718471485219588 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7184466019417476, "acc_stderr": 0.044532548363264673, "acc_norm": 0.7184466019417476, "acc_norm_stderr": 0.044532548363264673 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406978, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406978 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7816091954022989, "acc_stderr": 0.014774358319934495, "acc_norm": 0.7816091954022989, "acc_norm_stderr": 0.014774358319934495 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7052023121387283, "acc_stderr": 0.024547617794803828, "acc_norm": 0.7052023121387283, "acc_norm_stderr": 0.024547617794803828 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.36089385474860336, "acc_stderr": 0.01606229067111047, "acc_norm": 0.36089385474860336, "acc_norm_stderr": 0.01606229067111047 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6633986928104575, "acc_stderr": 0.02705797462449438, "acc_norm": 0.6633986928104575, "acc_norm_stderr": 0.02705797462449438 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.684887459807074, "acc_stderr": 0.026385273703464496, "acc_norm": 0.684887459807074, "acc_norm_stderr": 0.026385273703464496 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6635802469135802, "acc_stderr": 0.02628973494595293, "acc_norm": 0.6635802469135802, "acc_norm_stderr": 0.02628973494595293 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4787234042553192, "acc_stderr": 0.029800481645628693, "acc_norm": 0.4787234042553192, "acc_norm_stderr": 0.029800481645628693 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.43089960886571055, "acc_stderr": 0.012647695889547228, "acc_norm": 0.43089960886571055, "acc_norm_stderr": 0.012647695889547228 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5661764705882353, "acc_stderr": 0.030105636570016633, "acc_norm": 0.5661764705882353, "acc_norm_stderr": 0.030105636570016633 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6405228758169934, "acc_stderr": 0.019412539242032168, "acc_norm": 0.6405228758169934, "acc_norm_stderr": 0.019412539242032168 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6938775510204082, "acc_stderr": 0.029504896454595957, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.029504896454595957 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.6766169154228856, "acc_stderr": 0.03307615947979033, "acc_norm": 0.6766169154228856, "acc_norm_stderr": 0.03307615947979033 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.82, "acc_stderr": 0.03861229196653693, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653693 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5, "acc_stderr": 0.03892494720807614, "acc_norm": 0.5, "acc_norm_stderr": 0.03892494720807614 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8187134502923976, "acc_stderr": 0.02954774168764004, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.02954774168764004 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.45532435740514077, "mc1_stderr": 0.017433490102538765, "mc2": 0.6287894376799671, "mc2_stderr": 0.015043355245179869 }, "harness\|winogrande\|5": { "acc": 0.8011049723756906, "acc_stderr": 0.011218629972515302 }, "harness\|gsm8k\|5": { "acc": 0.47536012130401817, "acc_stderr": 0.013755751352764918 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address 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open-llm-leaderboard/details_ChavyvAkvar__habib-DPO	--- pretty_name: Evaluation run of ChavyvAkvar/habib-DPO dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [ChavyvAkvar/habib-DPO](https://huggingface.co/ChavyvAkvar/habib-DPO) on the [Open\ \ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_ChavyvAkvar__habib-DPO\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-08T14:15:05.108726](https://huggingface.co/datasets/open-llm-leaderboard/details_ChavyvAkvar__habib-DPO/blob/main/results_2024-04-08T14-15-05.108726.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6463086057955821,\n\ \ \"acc_stderr\": 0.03219641610397338,\n \"acc_norm\": 0.6470499429849053,\n\ \ \"acc_norm_stderr\": 0.0328482314699445,\n \"mc1\": 0.4847001223990208,\n\ \ \"mc1_stderr\": 0.017495304473187902,\n \"mc2\": 0.6519725385425954,\n\ \ \"mc2_stderr\": 0.015460535740302407\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6569965870307167,\n \"acc_stderr\": 0.013872423223718166,\n\ \ \"acc_norm\": 0.6868600682593856,\n \"acc_norm_stderr\": 0.01355267154362349\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6899024098785103,\n\ \ \"acc_stderr\": 0.004615880352799734,\n \"acc_norm\": 0.8670583549093805,\n\ \ \"acc_norm_stderr\": 0.003388177893268278\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6444444444444445,\n\ \ \"acc_stderr\": 0.04135176749720386,\n \"acc_norm\": 0.6444444444444445,\n\ \ \"acc_norm_stderr\": 0.04135176749720386\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6842105263157895,\n \"acc_stderr\": 0.0378272898086547,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.0378272898086547\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7245283018867924,\n \"acc_stderr\": 0.027495663683724064,\n\ \ \"acc_norm\": 0.7245283018867924,\n \"acc_norm_stderr\": 0.027495663683724064\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7430555555555556,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.7430555555555556,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness\|hendrycksTest-college_computer_science\|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness\|hendrycksTest-college_mathematics\|5\": {\n \"acc\": 0.31,\n\ \ \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.31,\n \ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-college_medicine\|5\"\ : {\n \"acc\": 0.6705202312138728,\n \"acc_stderr\": 0.03583901754736412,\n\ \ \"acc_norm\": 0.6705202312138728,\n \"acc_norm_stderr\": 0.03583901754736412\n\ \ },\n \"harness\|hendrycksTest-college_physics\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.04690650298201942,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.04690650298201942\n },\n \"harness\|hendrycksTest-computer_security\|5\"\ : {\n \"acc\": 0.76,\n \"acc_stderr\": 0.042923469599092816,\n \ \ \"acc_norm\": 0.76,\n \"acc_norm_stderr\": 0.042923469599092816\n \ \ },\n \"harness\|hendrycksTest-conceptual_physics\|5\": {\n \"acc\":\ \ 0.5957446808510638,\n \"acc_stderr\": 0.03208115750788684,\n \"\ acc_norm\": 0.5957446808510638,\n \"acc_norm_stderr\": 0.03208115750788684\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.5175438596491229,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.5175438596491229,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5793103448275863,\n \"acc_stderr\": 0.0411391498118926,\n\ \ \"acc_norm\": 0.5793103448275863,\n \"acc_norm_stderr\": 0.0411391498118926\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.42592592592592593,\n \"acc_stderr\": 0.02546714904546955,\n \"\ acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.02546714904546955\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.48412698412698413,\n\ \ \"acc_stderr\": 0.04469881854072606,\n \"acc_norm\": 0.48412698412698413,\n\ \ \"acc_norm_stderr\": 0.04469881854072606\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7741935483870968,\n\ \ \"acc_stderr\": 0.023785577884181012,\n \"acc_norm\": 0.7741935483870968,\n\ \ \"acc_norm_stderr\": 0.023785577884181012\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.49261083743842365,\n \"acc_stderr\": 0.03517603540361008,\n\ \ \"acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.03517603540361008\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7575757575757576,\n \"acc_stderr\": 0.03346409881055953,\n\ \ \"acc_norm\": 0.7575757575757576,\n \"acc_norm_stderr\": 0.03346409881055953\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.029620227874790486,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.029620227874790486\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8860103626943006,\n \"acc_stderr\": 0.022935144053919443,\n\ \ \"acc_norm\": 0.8860103626943006,\n \"acc_norm_stderr\": 0.022935144053919443\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6564102564102564,\n \"acc_stderr\": 0.024078696580635477,\n\ \ \"acc_norm\": 0.6564102564102564,\n \"acc_norm_stderr\": 0.024078696580635477\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3296296296296296,\n \"acc_stderr\": 0.028661201116524565,\n \ \ \"acc_norm\": 0.3296296296296296,\n \"acc_norm_stderr\": 0.028661201116524565\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.030388353551886793,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.030388353551886793\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8550458715596331,\n \"acc_stderr\": 0.015094215699700476,\n \"\ acc_norm\": 0.8550458715596331,\n \"acc_norm_stderr\": 0.015094215699700476\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5046296296296297,\n \"acc_stderr\": 0.03409825519163572,\n \"\ acc_norm\": 0.5046296296296297,\n \"acc_norm_stderr\": 0.03409825519163572\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8382352941176471,\n \"acc_stderr\": 0.025845017986926913,\n \"\ acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.025845017986926913\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8143459915611815,\n \"acc_stderr\": 0.025310495376944856,\n \ \ \"acc_norm\": 0.8143459915611815,\n \"acc_norm_stderr\": 0.025310495376944856\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6995515695067265,\n\ \ \"acc_stderr\": 0.030769352008229143,\n \"acc_norm\": 0.6995515695067265,\n\ \ \"acc_norm_stderr\": 0.030769352008229143\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.03641297081313729,\n\ \ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.03641297081313729\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7851239669421488,\n \"acc_stderr\": 0.037494924487096966,\n \"\ acc_norm\": 0.7851239669421488,\n \"acc_norm_stderr\": 0.037494924487096966\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7607361963190185,\n \"acc_stderr\": 0.033519538795212696,\n\ \ \"acc_norm\": 0.7607361963190185,\n \"acc_norm_stderr\": 0.033519538795212696\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\ \ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8547008547008547,\n\ \ \"acc_stderr\": 0.023086635086841403,\n \"acc_norm\": 0.8547008547008547,\n\ \ \"acc_norm_stderr\": 0.023086635086841403\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.73,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8186462324393359,\n\ \ \"acc_stderr\": 0.013778693778464074,\n \"acc_norm\": 0.8186462324393359,\n\ \ \"acc_norm_stderr\": 0.013778693778464074\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7398843930635838,\n \"acc_stderr\": 0.023618678310069356,\n\ \ \"acc_norm\": 0.7398843930635838,\n \"acc_norm_stderr\": 0.023618678310069356\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.4480446927374302,\n\ \ \"acc_stderr\": 0.016631976628930595,\n \"acc_norm\": 0.4480446927374302,\n\ \ \"acc_norm_stderr\": 0.016631976628930595\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7026143790849673,\n \"acc_stderr\": 0.02617390850671858,\n\ \ \"acc_norm\": 0.7026143790849673,\n \"acc_norm_stderr\": 0.02617390850671858\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.729903536977492,\n\ \ \"acc_stderr\": 0.02521804037341063,\n \"acc_norm\": 0.729903536977492,\n\ \ \"acc_norm_stderr\": 0.02521804037341063\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7160493827160493,\n \"acc_stderr\": 0.025089478523765137,\n\ \ \"acc_norm\": 0.7160493827160493,\n \"acc_norm_stderr\": 0.025089478523765137\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4716312056737589,\n \"acc_stderr\": 0.029779450957303062,\n \ \ \"acc_norm\": 0.4716312056737589,\n \"acc_norm_stderr\": 0.029779450957303062\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.46153846153846156,\n\ \ \"acc_stderr\": 0.01273239828619044,\n \"acc_norm\": 0.46153846153846156,\n\ \ \"acc_norm_stderr\": 0.01273239828619044\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6948529411764706,\n \"acc_stderr\": 0.027971541370170598,\n\ \ \"acc_norm\": 0.6948529411764706,\n \"acc_norm_stderr\": 0.027971541370170598\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6454248366013072,\n \"acc_stderr\": 0.0193533605475537,\n \ \ \"acc_norm\": 0.6454248366013072,\n \"acc_norm_stderr\": 0.0193533605475537\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784593,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784593\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.835820895522388,\n\ \ \"acc_stderr\": 0.026193923544454115,\n \"acc_norm\": 0.835820895522388,\n\ \ \"acc_norm_stderr\": 0.026193923544454115\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5180722891566265,\n\ \ \"acc_stderr\": 0.03889951252827216,\n \"acc_norm\": 0.5180722891566265,\n\ \ \"acc_norm_stderr\": 0.03889951252827216\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8304093567251462,\n \"acc_stderr\": 0.02878210810540171,\n\ \ \"acc_norm\": 0.8304093567251462,\n \"acc_norm_stderr\": 0.02878210810540171\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.4847001223990208,\n\ \ \"mc1_stderr\": 0.017495304473187902,\n \"mc2\": 0.6519725385425954,\n\ \ \"mc2_stderr\": 0.015460535740302407\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7947908445146015,\n \"acc_stderr\": 0.011350315707462068\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6611068991660348,\n \ \ \"acc_stderr\": 0.013037955768562507\n }\n}\n```" repo_url: https://huggingface.co/ChavyvAkvar/habib-DPO leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|arc:challenge\|25_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-04-08T14-15-05.108726.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|gsm8k\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hellaswag\|10_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-08T14-15-05.108726.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-management\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|truthfulqa:mc\|0_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-04-08T14-15-05.108726.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '/details_harness\|winogrande\|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-04-08T14-15-05.108726.parquet' - config_name: results data_files: - split: 2024_04_08T14_15_05.108726 path: - results_2024-04-08T14-15-05.108726.parquet - split: latest path: - results_2024-04-08T14-15-05.108726.parquet --- # Dataset Card for Evaluation run of ChavyvAkvar/habib-DPO <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [ChavyvAkvar/habib-DPO](https://huggingface.co/ChavyvAkvar/habib-DPO) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_ChavyvAkvar__habib-DPO", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-08T14:15:05.108726](https://huggingface.co/datasets/open-llm-leaderboard/details_ChavyvAkvar__habib-DPO/blob/main/results_2024-04-08T14-15-05.108726.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6463086057955821, "acc_stderr": 0.03219641610397338, "acc_norm": 0.6470499429849053, "acc_norm_stderr": 0.0328482314699445, "mc1": 0.4847001223990208, "mc1_stderr": 0.017495304473187902, "mc2": 0.6519725385425954, "mc2_stderr": 0.015460535740302407 }, "harness\|arc:challenge\|25": { "acc": 0.6569965870307167, "acc_stderr": 0.013872423223718166, "acc_norm": 0.6868600682593856, "acc_norm_stderr": 0.01355267154362349 }, "harness\|hellaswag\|10": { "acc": 0.6899024098785103, "acc_stderr": 0.004615880352799734, "acc_norm": 0.8670583549093805, "acc_norm_stderr": 0.003388177893268278 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6444444444444445, "acc_stderr": 0.04135176749720386, "acc_norm": 0.6444444444444445, "acc_norm_stderr": 0.04135176749720386 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6842105263157895, "acc_stderr": 0.0378272898086547, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.0378272898086547 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7245283018867924, "acc_stderr": 0.027495663683724064, "acc_norm": 0.7245283018867924, "acc_norm_stderr": 0.027495663683724064 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7430555555555556, "acc_stderr": 0.03653946969442099, "acc_norm": 0.7430555555555556, "acc_norm_stderr": 0.03653946969442099 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201942, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201942 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5957446808510638, "acc_stderr": 0.03208115750788684, "acc_norm": 0.5957446808510638, "acc_norm_stderr": 0.03208115750788684 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5793103448275863, "acc_stderr": 0.0411391498118926, "acc_norm": 0.5793103448275863, "acc_norm_stderr": 0.0411391498118926 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.42592592592592593, "acc_stderr": 0.02546714904546955, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.02546714904546955 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.48412698412698413, "acc_stderr": 0.04469881854072606, "acc_norm": 0.48412698412698413, "acc_norm_stderr": 0.04469881854072606 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7741935483870968, "acc_stderr": 0.023785577884181012, "acc_norm": 0.7741935483870968, "acc_norm_stderr": 0.023785577884181012 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.49261083743842365, "acc_stderr": 0.03517603540361008, "acc_norm": 0.49261083743842365, "acc_norm_stderr": 0.03517603540361008 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7575757575757576, "acc_stderr": 0.03346409881055953, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.03346409881055953 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.029620227874790486, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.029620227874790486 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8860103626943006, "acc_stderr": 0.022935144053919443, "acc_norm": 0.8860103626943006, "acc_norm_stderr": 0.022935144053919443 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6564102564102564, "acc_stderr": 0.024078696580635477, "acc_norm": 0.6564102564102564, "acc_norm_stderr": 0.024078696580635477 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3296296296296296, "acc_stderr": 0.028661201116524565, "acc_norm": 0.3296296296296296, "acc_norm_stderr": 0.028661201116524565 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6764705882352942, "acc_stderr": 0.030388353551886793, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.030388353551886793 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8550458715596331, "acc_stderr": 0.015094215699700476, "acc_norm": 0.8550458715596331, "acc_norm_stderr": 0.015094215699700476 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5046296296296297, "acc_stderr": 0.03409825519163572, "acc_norm": 0.5046296296296297, "acc_norm_stderr": 0.03409825519163572 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8382352941176471, "acc_stderr": 0.025845017986926913, "acc_norm": 0.8382352941176471, "acc_norm_stderr": 0.025845017986926913 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8143459915611815, "acc_stderr": 0.025310495376944856, "acc_norm": 0.8143459915611815, "acc_norm_stderr": 0.025310495376944856 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6995515695067265, "acc_stderr": 0.030769352008229143, "acc_norm": 0.6995515695067265, "acc_norm_stderr": 0.030769352008229143 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7786259541984732, "acc_stderr": 0.03641297081313729, "acc_norm": 0.7786259541984732, "acc_norm_stderr": 0.03641297081313729 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7851239669421488, "acc_stderr": 0.037494924487096966, "acc_norm": 0.7851239669421488, "acc_norm_stderr": 0.037494924487096966 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7607361963190185, "acc_stderr": 0.033519538795212696, "acc_norm": 0.7607361963190185, "acc_norm_stderr": 0.033519538795212696 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7864077669902912, "acc_stderr": 0.040580420156460344, "acc_norm": 0.7864077669902912, "acc_norm_stderr": 0.040580420156460344 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8547008547008547, "acc_stderr": 0.023086635086841403, "acc_norm": 0.8547008547008547, "acc_norm_stderr": 0.023086635086841403 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.73, "acc_stderr": 0.0446196043338474, "acc_norm": 0.73, "acc_norm_stderr": 0.0446196043338474 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8186462324393359, "acc_stderr": 0.013778693778464074, "acc_norm": 0.8186462324393359, "acc_norm_stderr": 0.013778693778464074 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7398843930635838, "acc_stderr": 0.023618678310069356, "acc_norm": 0.7398843930635838, "acc_norm_stderr": 0.023618678310069356 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.4480446927374302, "acc_stderr": 0.016631976628930595, "acc_norm": 0.4480446927374302, "acc_norm_stderr": 0.016631976628930595 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7026143790849673, "acc_stderr": 0.02617390850671858, "acc_norm": 0.7026143790849673, "acc_norm_stderr": 0.02617390850671858 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.729903536977492, "acc_stderr": 0.02521804037341063, "acc_norm": 0.729903536977492, "acc_norm_stderr": 0.02521804037341063 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7160493827160493, "acc_stderr": 0.025089478523765137, "acc_norm": 0.7160493827160493, "acc_norm_stderr": 0.025089478523765137 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4716312056737589, "acc_stderr": 0.029779450957303062, "acc_norm": 0.4716312056737589, "acc_norm_stderr": 0.029779450957303062 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.46153846153846156, "acc_stderr": 0.01273239828619044, "acc_norm": 0.46153846153846156, "acc_norm_stderr": 0.01273239828619044 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6948529411764706, "acc_stderr": 0.027971541370170598, "acc_norm": 0.6948529411764706, "acc_norm_stderr": 0.027971541370170598 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6454248366013072, "acc_stderr": 0.0193533605475537, "acc_norm": 0.6454248366013072, "acc_norm_stderr": 0.0193533605475537 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6636363636363637, "acc_stderr": 0.04525393596302506, "acc_norm": 0.6636363636363637, "acc_norm_stderr": 0.04525393596302506 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784593, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784593 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.835820895522388, "acc_stderr": 0.026193923544454115, "acc_norm": 0.835820895522388, "acc_norm_stderr": 0.026193923544454115 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5180722891566265, "acc_stderr": 0.03889951252827216, "acc_norm": 0.5180722891566265, "acc_norm_stderr": 0.03889951252827216 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8304093567251462, "acc_stderr": 0.02878210810540171, "acc_norm": 0.8304093567251462, "acc_norm_stderr": 0.02878210810540171 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.4847001223990208, "mc1_stderr": 0.017495304473187902, "mc2": 0.6519725385425954, "mc2_stderr": 0.015460535740302407 }, "harness\|winogrande\|5": { "acc": 0.7947908445146015, "acc_stderr": 0.011350315707462068 }, "harness\|gsm8k\|5": { "acc": 0.6611068991660348, "acc_stderr": 0.013037955768562507 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
Ismagopo/TradingZoo	--- license: openrail ---
JoshVictor/platypus-Jo-data	--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 2253597 num_examples: 1000 download_size: 1118629 dataset_size: 2253597 configs: - config_name: default data_files: - split: train path: data/train-* ---
pccl-org/formal-logic-simple-order-multi-token-dynamic-objects-paired-relationship-0-100	--- dataset_info: features: - name: greater_than sequence: int64 - name: less_than sequence: int64 - name: paired_example sequence: sequence: sequence: int64 - name: correct_example sequence: sequence: int64 - name: incorrect_example sequence: sequence: int64 - name: distance dtype: int64 - name: index dtype: int64 - name: index_in_distance dtype: int64 splits: - name: train num_bytes: 1397336 num_examples: 4950 download_size: 159651 dataset_size: 1397336 configs: - config_name: default data_files: - split: train path: data/train-* ---
Deojoandco/dialogturns_not_generated_val	--- dataset_info: features: - name: url dtype: string - name: id dtype: string - name: num_comments dtype: int64 - name: name dtype: string - name: title dtype: string - name: body dtype: string - name: score dtype: int64 - name: upvote_ratio dtype: float64 - name: distinguished dtype: 'null' - name: over_18 dtype: bool - name: created_utc dtype: int64 - name: comments list: - name: body dtype: string - name: created_utc dtype: float64 - name: distinguished dtype: string - name: id dtype: string - name: permalink dtype: string - name: score dtype: int64 - name: best_num_comments dtype: int64 - name: query dtype: string - name: dialog dtype: string - name: annotation_success dtype: bool - name: annotation_text dtype: string - name: turns_generated dtype: bool - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 493996 num_examples: 25 download_size: 304777 dataset_size: 493996 --- # Dataset Card for "dialogturns_not_generated_val" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
dolo650/lamini_docs_processed	--- license: apache-2.0 --- License/Credit goes to the original creators of the dataset. This is a sample dataset used for instruction fine tuning of LLMs
danielz01/BigEarthNet-S2-v1.0	--- configs: - config_name: s2-rgb data_files: - split: test path: s2-rgb/test-* - split: val path: s2-rgb/val-* - split: train path: s2-rgb/train-* dataset_info: config_name: s2-rgb features: - name: img dtype: image - name: labels sequence: string - name: coordinates struct: - name: lrx dtype: int64 - name: lry dtype: int64 - name: ulx dtype: int64 - name: uly dtype: int64 - name: projection dtype: string - name: tile_source dtype: string - name: acquisition_date dtype: string splits: - name: test num_bytes: 3453114936.75 num_examples: 125866 - name: val num_bytes: 3393628600.625 num_examples: 123723 - name: train num_bytes: 7391482704.125 num_examples: 269695 download_size: 13839792533 dataset_size: 14238226241.5 --- # Dataset Card for "BigEarthNet-S2-v1.0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mateusartur/mateusartur	--- license: openrail ---
316usman/thematic1d	--- license: bsd dataset_info: features: - name: text dtype: string - name: thematic dtype: string - name: sub-thematic dtype: string - name: country dtype: string - name: document_url dtype: string - name: source_url dtype: string splits: - name: train num_bytes: 109014361 num_examples: 147302 download_size: 32599891 dataset_size: 109014361 configs: - config_name: default data_files: - split: train path: data/train-* ---
PL-MTEB/polemo2_in	--- license: cc-by-nc-sa-4.0 ---
lishuyang/recipepairs	--- annotations_creators: no-annotation language_creators: found language: en license: gpl-3.0 multilinguality: monolingual size_categories: - 1M<n<10M source_datasets: original task_categories: - text-generation pretty_name: RecipePairs dataset_info: - config_name: 1.5.0 splits: - name: pairs num_examples: 6908697 --- RecipePairs dataset, originally from the 2022 EMNLP paper: ["SHARE: a System for Hierarchical Assistive Recipe Editing"](https://aclanthology.org/2022.emnlp-main.761/) by Shuyang Li, Yufei Li, Jianmo Ni, and Julian McAuley. This version (1.5.0) has been updated with 6.9M pairs of `base -> target` recipes, alongside their name overlap, IOU (longest common subsequence / union), and target dietary categories. These cover the 459K recipes from the original GeniusKitcen/Food.com dataset. If you would like to use this data or found it useful in your work/research, please cite the following papers: ``` @inproceedings{li-etal-2022-share, title = "{SHARE}: a System for Hierarchical Assistive Recipe Editing", author = "Li, Shuyang and Li, Yufei and Ni, Jianmo and McAuley, Julian", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, United Arab Emirates", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.emnlp-main.761", pages = "11077--11090", abstract = "The large population of home cooks with dietary restrictions is under-served by existing cooking resources and recipe generation models. To help them, we propose the task of controllable recipe editing: adapt a base recipe to satisfy a user-specified dietary constraint. This task is challenging, and cannot be adequately solved with human-written ingredient substitution rules or existing end-to-end recipe generation models. We tackle this problem with SHARE: a System for Hierarchical Assistive Recipe Editing, which performs simultaneous ingredient substitution before generating natural-language steps using the edited ingredients. By decoupling ingredient and step editing, our step generator can explicitly integrate the available ingredients. Experiments on the novel RecipePairs dataset{---}83K pairs of similar recipes where each recipe satisfies one of seven dietary constraints{---}demonstrate that SHARE produces convincing, coherent recipes that are appropriate for a target dietary constraint. We further show through human evaluations and real-world cooking trials that recipes edited by SHARE can be easily followed by home cooks to create appealing dishes.", } @inproceedings{majumder-etal-2019-generating, title = "Generating Personalized Recipes from Historical User Preferences", author = "Majumder, Bodhisattwa Prasad and Li, Shuyang and Ni, Jianmo and McAuley, Julian", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)", month = nov, year = "2019", address = "Hong Kong, China", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/D19-1613", doi = "10.18653/v1/D19-1613", pages = "5976--5982", abstract = "Existing approaches to recipe generation are unable to create recipes for users with culinary preferences but incomplete knowledge of ingredients in specific dishes. We propose a new task of personalized recipe generation to help these users: expanding a name and incomplete ingredient details into complete natural-text instructions aligned with the user{'}s historical preferences. We attend on technique- and recipe-level representations of a user{'}s previously consumed recipes, fusing these {`}user-aware{'} representations in an attention fusion layer to control recipe text generation. Experiments on a new dataset of 180K recipes and 700K interactions show our model{'}s ability to generate plausible and personalized recipes compared to non-personalized baselines.", } ```
deepghs/bangumibase_full	--- license: mit task_categories: - image-classification - zero-shot-image-classification - text-to-image language: - en tags: - art - anime - not-for-all-audiences size_categories: - 1M<n<10M annotations_creators: - no-annotation source_datasets: - bangumibase --- # BangumiBase Full Dataset This is the full dataset of [BangumiBase](https://huggingface.co/BangumiBase). And all the original images are maintained here. # Information ## Images There are 1158841 images in total. The maximum ID of these images is 1650289. Last updated at `2024-04-16 10:11:31 CST`. These are the information of recent 50 images: \| id \| filename \| width \| height \| type \| rating \| tags \| repository \| commit_id \| chid \| src_filename \| created_at \| has_face \| face_width \| face_height \| face_min \| face_max \| resolution \| face_max_ratio \| face_min_ratio \| face_width_ratio \| face_height_ratio \| face_area_ratio \| \|--------:\|:------------\|--------:\|---------:\|:----------\|:----------\|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|:-------------------------------\|:-----------------------------------------\|-------:\|:---------------\|-------------:\|:-----------\|-------------:\|--------------:\|-----------:\|-----------:\|-------------:\|-----------------:\|-----------------:\|-------------------:\|--------------------:\|------------------:\| \| 1650289 \| 1650289.png \| 1498 \| 1047 \| image/png \| sensitive \| solo open_mouth short_hair blonde_hair 1boy upper_body male_focus outdoors nude sky muscular night barrel \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 48 \| 3327.png \| 1.71312e+09 \| True \| 223 \| 220 \| 220 \| 223 \| 1080 \| 0.206481 \| 0.203704 \| 0.206481 \| 0.203704 \| 0.205088 \| \| 1650281 \| 1650281.png \| 1875 \| 1078 \| image/png \| sensitive \| solo short_hair blonde_hair 1boy upper_body male_focus muscular night muscular_male pectorals bara rope large_pectorals meme anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 48 \| 3261.png \| 1.71312e+09 \| True \| 375 \| 368 \| 368 \| 375 \| 1080 \| 0.347222 \| 0.340741 \| 0.347222 \| 0.340741 \| 0.343966 \| \| 1650263 \| 1650263.png \| 1901 \| 1079 \| image/png \| sensitive \| solo open_mouth short_hair blonde_hair 1boy upper_body male_focus sky from_side muscular night anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 48 \| 3193.png \| 1.71312e+09 \| True \| 218 \| 271 \| 218 \| 271 \| 1080 \| 0.250926 \| 0.201852 \| 0.201852 \| 0.250926 \| 0.225055 \| \| 1650242 \| 1650242.png \| 1792 \| 1067 \| image/png \| general \| solo brown_hair 1boy closed_mouth closed_eyes male_focus outdoors japanese_clothes blurry sweatdrop tree parody bandaid bandaid_on_face anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 47 \| 3025.png \| 1.71312e+09 \| True \| 496 \| 531 \| 496 \| 531 \| 1080 \| 0.491667 \| 0.459259 \| 0.459259 \| 0.491667 \| 0.475187 \| \| 1650205 \| 1650205.png \| 330 \| 609 \| image/png \| sensitive \| solo 1boy holding male_focus weapon outdoors japanese_clothes sword tree muscular night grass katana nature forest dark \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 46 \| 2679.png \| 1.71312e+09 \| True \| 43 \| 64 \| 43 \| 64 \| 1080 \| 0.0592593 \| 0.0398148 \| 0.0398148 \| 0.0592593 \| 0.0485736 \| \| 1650177 \| 1650177.png \| 1500 \| 1073 \| image/png \| general \| solo open_mouth short_hair black_hair 1boy upper_body male_focus indoors black_eyes bandages bandaged_head \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 46 \| 1854.png \| 1.71312e+09 \| True \| 247 \| 272 \| 247 \| 272 \| 1080 \| 0.251852 \| 0.228704 \| 0.228704 \| 0.251852 \| 0.239999 \| \| 1650176 \| 1650176.png \| 1230 \| 1078 \| image/png \| sensitive \| long_hair open_mouth brown_hair 1boy gloves male_focus ponytail multiple_boys japanese_clothes black_gloves 2boys parody \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8778.png \| 1.71312e+09 \| True \| 221 \| 228 \| 221 \| 228 \| 1080 \| 0.211111 \| 0.20463 \| 0.20463 \| 0.211111 \| 0.207845 \| \| 1650175 \| 1650175.png \| 1021 \| 1080 \| image/png \| sensitive \| solo long_hair brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes black_gloves clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8777.png \| 1.71312e+09 \| True \| 216 \| 235 \| 216 \| 235 \| 1080 \| 0.217593 \| 0.2 \| 0.2 \| 0.217593 \| 0.208611 \| \| 1650174 \| 1650174.png \| 1016 \| 1080 \| image/png \| sensitive \| solo long_hair brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes scar clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8775.png \| 1.71312e+09 \| True \| 190 \| 205 \| 190 \| 205 \| 1080 \| 0.189815 \| 0.175926 \| 0.175926 \| 0.189815 \| 0.182738 \| \| 1650173 \| 1650173.png \| 1172 \| 1073 \| image/png \| sensitive \| solo long_hair smile brown_hair 1boy male_focus ponytail teeth japanese_clothes grin night \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8659.png \| 1.71312e+09 \| True \| 225 \| 235 \| 225 \| 235 \| 1080 \| 0.217593 \| 0.208333 \| 0.208333 \| 0.217593 \| 0.212913 \| \| 1650172 \| 1650172.png \| 971 \| 1068 \| image/png \| sensitive \| solo long_hair smile brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes night scar sharp_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8658.png \| 1.71312e+09 \| True \| 177 \| 199 \| 177 \| 199 \| 1080 \| 0.184259 \| 0.163889 \| 0.163889 \| 0.184259 \| 0.173776 \| \| 1650171 \| 1650171.png \| 901 \| 1074 \| image/png \| sensitive \| solo long_hair brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes night clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8657.png \| 1.71312e+09 \| True \| 173 \| 188 \| 173 \| 188 \| 1080 \| 0.174074 \| 0.160185 \| 0.160185 \| 0.174074 \| 0.166985 \| \| 1650170 \| 1650170.png \| 827 \| 1069 \| image/png \| sensitive \| solo long_hair brown_hair 1boy male_focus ponytail teeth japanese_clothes night sharp_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8656.png \| 1.71312e+09 \| True \| 162 \| 189 \| 162 \| 189 \| 1080 \| 0.175 \| 0.15 \| 0.15 \| 0.175 \| 0.162019 \| \| 1650169 \| 1650169.png \| 730 \| 1071 \| image/png \| sensitive \| solo long_hair blue_eyes brown_hair 1boy male_focus ponytail teeth japanese_clothes clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8655.png \| 1.71312e+09 \| True \| 146 \| 189 \| 146 \| 189 \| 1080 \| 0.175 \| 0.135185 \| 0.135185 \| 0.175 \| 0.15381 \| \| 1650168 \| 1650168.png \| 683 \| 1075 \| image/png \| sensitive \| solo long_hair blue_eyes brown_hair 1boy male_focus ponytail teeth japanese_clothes clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8654.png \| 1.71312e+09 \| True \| 149 \| 190 \| 149 \| 190 \| 1080 \| 0.175926 \| 0.137963 \| 0.137963 \| 0.175926 \| 0.155792 \| \| 1650167 \| 1650167.png \| 620 \| 1067 \| image/png \| sensitive \| solo long_hair blue_eyes brown_hair 1boy male_focus ponytail teeth japanese_clothes scar sharp_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8653.png \| 1.71312e+09 \| True \| 145 \| 188 \| 145 \| 188 \| 1080 \| 0.174074 \| 0.134259 \| 0.134259 \| 0.174074 \| 0.152876 \| \| 1650166 \| 1650166.png \| 569 \| 1069 \| image/png \| sensitive \| solo long_hair brown_hair 1boy male_focus ponytail teeth japanese_clothes scar clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8652.png \| 1.71312e+09 \| True \| 147 \| 190 \| 147 \| 190 \| 1080 \| 0.175926 \| 0.136111 \| 0.136111 \| 0.175926 \| 0.154743 \| \| 1650165 \| 1650165.png \| 520 \| 1066 \| image/png \| sensitive \| solo long_hair blue_eyes blonde_hair brown_hair 1boy male_focus ponytail teeth japanese_clothes scar clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8651.png \| 1.71312e+09 \| True \| 149 \| 185 \| 149 \| 185 \| 1080 \| 0.171296 \| 0.137963 \| 0.137963 \| 0.171296 \| 0.153729 \| \| 1650164 \| 1650164.png \| 474 \| 1064 \| image/png \| sensitive \| solo long_hair open_mouth blonde_hair brown_hair 1boy male_focus ponytail japanese_clothes scar \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8650.png \| 1.71312e+09 \| True \| 143 \| 187 \| 143 \| 187 \| 1080 \| 0.173148 \| 0.132407 \| 0.132407 \| 0.173148 \| 0.151414 \| \| 1650163 \| 1650163.png \| 413 \| 1064 \| image/png \| sensitive \| solo long_hair open_mouth blue_eyes blonde_hair brown_hair 1boy male_focus ponytail japanese_clothes scar \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8649.png \| 1.71312e+09 \| True \| 142 \| 184 \| 142 \| 184 \| 1080 \| 0.17037 \| 0.131481 \| 0.131481 \| 0.17037 \| 0.149668 \| \| 1650137 \| 1650137.png \| 1910 \| 1080 \| image/png \| general \| solo long_hair blonde_hair 1boy male_focus outdoors sweat teeth parody grass portrait clenched_teeth anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8263.png \| 1.71312e+09 \| True \| 868 \| 696 \| 696 \| 868 \| 1080 \| 0.803704 \| 0.644444 \| 0.803704 \| 0.644444 \| 0.719682 \| \| 1650130 \| 1650130.png \| 1916 \| 1079 \| image/png \| general \| solo long_hair looking_at_viewer smile brown_hair 1boy male_focus ponytail outdoors teeth japanese_clothes grin scar chain parody \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8252.png \| 1.71312e+09 \| True \| 799 \| 739 \| 739 \| 799 \| 1080 \| 0.739815 \| 0.684259 \| 0.739815 \| 0.684259 \| 0.711495 \| \| 1650124 \| 1650124.png \| 1916 \| 1080 \| image/png \| general \| solo open_mouth brown_hair 1boy male_focus ponytail teeth makeup parody eyeshadow \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 8219.png \| 1.71312e+09 \| True \| 778 \| 729 \| 729 \| 778 \| 1080 \| 0.72037 \| 0.675 \| 0.72037 \| 0.675 \| 0.697316 \| \| 1650119 \| 1650119.png \| 1528 \| 1080 \| image/png \| general \| solo 1boy red_eyes grey_hair male_focus indoors scarf profile headband portrait candle ninja purple_scarf anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 2451.png \| 1.71312e+09 \| True \| 449 \| 648 \| 449 \| 648 \| 1080 \| 0.6 \| 0.415741 \| 0.415741 \| 0.6 \| 0.499444 \| \| 1650118 \| 1650118.png \| 1915 \| 1078 \| image/png \| sensitive \| solo looking_at_viewer smile blonde_hair 1boy red_eyes hat male_focus teeth sky cloud grin facial_mark portrait evil_smile evil_grin \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 2363.png \| 1.71312e+09 \| True \| 663 \| 599 \| 599 \| 663 \| 1080 \| 0.613889 \| 0.55463 \| 0.613889 \| 0.55463 \| 0.583507 \| \| 1650117 \| 1650117.png \| 1916 \| 1079 \| image/png \| sensitive \| solo looking_at_viewer smile blonde_hair 1boy red_eyes hat male_focus teeth sky cloud grin evil_smile evil_grin \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 45 \| 2362.png \| 1.71312e+09 \| True \| 660 \| 575 \| 575 \| 660 \| 1080 \| 0.611111 \| 0.532407 \| 0.611111 \| 0.532407 \| 0.570403 \| \| 1650115 \| 1650115.png \| 1915 \| 1079 \| image/png \| general \| solo looking_at_viewer short_hair 1boy closed_mouth male_focus indoors facial_hair parody portrait bookshelf monocle \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 7699.png \| 1.71312e+09 \| True \| 836 \| 1011 \| 836 \| 1011 \| 1080 \| 0.936111 \| 0.774074 \| 0.774074 \| 0.936111 \| 0.851246 \| \| 1650114 \| 1650114.png \| 1039 \| 1080 \| image/png \| general \| short_hair brown_hair black_hair male_focus outdoors multiple_boys sky japanese_clothes 2boys kimono from_behind night bandaid night_sky bandaid_on_face green_kimono anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 7001.png \| 1.71312e+09 \| True \| 139 \| 205 \| 139 \| 205 \| 1080 \| 0.189815 \| 0.128704 \| 0.128704 \| 0.189815 \| 0.156301 \| \| 1650113 \| 1650113.png \| 1877 \| 1080 \| image/png \| general \| solo open_mouth brown_hair 1boy upper_body male_focus weapon teeth sky japanese_clothes glasses cloud sword kimono parody katana head_out_of_frame haori opaque_glasses \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6625.png \| 1.71312e+09 \| True \| 356 \| 304 \| 304 \| 356 \| 1080 \| 0.32963 \| 0.281481 \| 0.32963 \| 0.281481 \| 0.304606 \| \| 1650112 \| 1650112.png \| 1851 \| 1080 \| image/png \| general \| solo smile 1boy upper_body male_focus weapon sky japanese_clothes cloud sword kimono katana sheath head_out_of_frame black_kimono haori \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6624.png \| 1.71312e+09 \| True \| 373 \| 148 \| 148 \| 373 \| 1080 \| 0.34537 \| 0.137037 \| 0.34537 \| 0.137037 \| 0.217551 \| \| 1650111 \| 1650111.png \| 1912 \| 1079 \| image/png \| general \| solo long_hair black_hair 1boy male_focus outdoors teeth dark_skin from_behind night dark-skinned_male clenched_teeth nature forest head_out_of_frame anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6523.png \| 1.71312e+09 \| True \| 588 \| 410 \| 410 \| 588 \| 1080 \| 0.544444 \| 0.37963 \| 0.544444 \| 0.37963 \| 0.454629 \| \| 1650109 \| 1650109.png \| 1850 \| 1076 \| image/png \| general \| solo shirt black_hair 1boy holding upper_body grey_hair male_focus ponytail weapon teeth multiple_boys sword 2boys holding_weapon muscular holding_sword katana spiked_hair clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6436.png \| 1.71312e+09 \| True \| 261 \| 337 \| 261 \| 337 \| 1080 \| 0.312037 \| 0.241667 \| 0.241667 \| 0.312037 \| 0.274607 \| \| 1650108 \| 1650108.png \| 1897 \| 1080 \| image/png \| sensitive \| solo 1boy collarbone male_focus teeth japanese_clothes night clenched_teeth nature forest head_out_of_frame anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6423.png \| 1.71312e+09 \| True \| 840 \| 608 \| 608 \| 840 \| 1080 \| 0.777778 \| 0.562963 \| 0.777778 \| 0.562963 \| 0.66171 \| \| 1650107 \| 1650107.png \| 1185 \| 1078 \| image/png \| general \| solo brown_hair 1boy male_focus weapon outdoors japanese_clothes day sword kimono tree katana sheath haori brown_kimono samurai \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6019.png \| 1.71312e+09 \| True \| 259 \| 249 \| 249 \| 259 \| 1080 \| 0.239815 \| 0.230556 \| 0.239815 \| 0.230556 \| 0.23514 \| \| 1650106 \| 1650106.png \| 1345 \| 1080 \| image/png \| general \| solo brown_hair 1boy closed_mouth male_focus weapon outdoors japanese_clothes sword kimono tree katana sheath hakama haori samurai \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6018.png \| 1.71312e+09 \| True \| 238 \| 244 \| 238 \| 244 \| 1080 \| 0.225926 \| 0.22037 \| 0.22037 \| 0.225926 \| 0.223131 \| \| 1650105 \| 1650105.png \| 709 \| 1032 \| image/png \| general \| solo skirt brown_hair 1boy male_focus weapon outdoors sky japanese_clothes day cloud sword kimono katana hakama hakama_skirt haori \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6014.png \| 1.71312e+09 \| True \| 134 \| 172 \| 134 \| 172 \| 1080 \| 0.159259 \| 0.124074 \| 0.124074 \| 0.159259 \| 0.14057 \| \| 1650104 \| 1650104.png \| 1547 \| 1079 \| image/png \| general \| solo brown_hair 1boy closed_mouth brown_eyes male_focus outdoors sky day cloud tree thick_eyebrows parody portrait style_parody \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 6012.png \| 1.71312e+09 \| True \| 914 \| 945 \| 914 \| 945 \| 1080 \| 0.875 \| 0.846296 \| 0.846296 \| 0.875 \| 0.860528 \| \| 1650103 \| 1650103.png \| 1874 \| 1079 \| image/png \| general \| solo shirt blonde_hair 1boy yellow_eyes male_focus teeth coat fur_trim thick_eyebrows parody clenched_teeth \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5981.png \| 1.71312e+09 \| True \| 861 \| 887 \| 861 \| 887 \| 1080 \| 0.821296 \| 0.797222 \| 0.797222 \| 0.821296 \| 0.80917 \| \| 1650102 \| 1650102.png \| 1919 \| 1080 \| image/png \| general \| solo looking_at_viewer open_mouth brown_hair 1boy brown_eyes male_focus outdoors japanese_clothes thick_eyebrows parody portrait close-up style_parody official_style anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5968.png \| 1.71312e+09 \| True \| 1136 \| 1068 \| 1068 \| 1136 \| 1080 \| 1.05185 \| 0.988889 \| 1.05185 \| 0.988889 \| 1.01988 \| \| 1650101 \| 1650101.png \| 1909 \| 1080 \| image/png \| general \| solo blonde_hair 1boy yellow_eyes male_focus outdoors sky day cloud blurry blue_sky parody close-up sanpaku \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5951.png \| 1.71312e+09 \| True \| 1172 \| 1022 \| 1022 \| 1172 \| 1080 \| 1.08519 \| 0.946296 \| 1.08519 \| 0.946296 \| 1.01336 \| \| 1650100 \| 1650100.png \| 1709 \| 1079 \| image/png \| general \| solo looking_at_viewer open_mouth brown_hair 1boy brown_eyes male_focus outdoors teeth sky day cloud blue_sky thick_eyebrows parody portrait style_parody official_style anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5949.png \| 1.71312e+09 \| True \| 931 \| 1045 \| 931 \| 1045 \| 1080 \| 0.967593 \| 0.862037 \| 0.862037 \| 0.967593 \| 0.913291 \| \| 1650099 \| 1650099.png \| 1893 \| 1080 \| image/png \| general \| solo open_mouth short_hair blonde_hair 1boy brown_eyes upper_body male_focus weapon teeth sky japanese_clothes day cloud sword kimono blue_sky parody katana haori \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5947.png \| 1.71312e+09 \| True \| 375 \| 387 \| 375 \| 387 \| 1080 \| 0.358333 \| 0.347222 \| 0.347222 \| 0.358333 \| 0.352734 \| \| 1650098 \| 1650098.png \| 1857 \| 1080 \| image/png \| general \| solo open_mouth 1boy upper_body male_focus weapon teeth sky japanese_clothes day cloud sword kimono blue_sky parody katana sheath head_out_of_frame haori anime_coloring \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5946.png \| 1.71312e+09 \| True \| 353 \| 227 \| 227 \| 353 \| 1080 \| 0.326852 \| 0.210185 \| 0.326852 \| 0.210185 \| 0.262106 \| \| 1650097 \| 1650097.png \| 1913 \| 903 \| image/png \| general \| solo short_hair brown_hair 1boy hat brown_eyes male_focus teeth facial_hair thick_eyebrows portrait clenched_teeth close-up stubble straw_hat \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5835.png \| 1.71312e+09 \| True \| 768 \| 656 \| 656 \| 768 \| 1080 \| 0.711111 \| 0.607407 \| 0.711111 \| 0.607407 \| 0.657217 \| \| 1650095 \| 1650095.png \| 1915 \| 1080 \| image/png \| general \| solo short_hair brown_hair 1boy hat brown_eyes male_focus teeth facial_hair thick_eyebrows portrait clenched_teeth close-up mature_male stubble straw_hat \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5833.png \| 1.71312e+09 \| True \| 765 \| 656 \| 656 \| 765 \| 1080 \| 0.708333 \| 0.607407 \| 0.708333 \| 0.607407 \| 0.655932 \| \| 1650094 \| 1650094.png \| 1915 \| 1080 \| image/png \| general \| solo smile short_hair brown_hair 1boy hat brown_eyes male_focus teeth facial_hair scar clenched_teeth scar_on_face close-up stubble straw_hat \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5832.png \| 1.71312e+09 \| True \| 824 \| 472 \| 472 \| 824 \| 1080 \| 0.762963 \| 0.437037 \| 0.762963 \| 0.437037 \| 0.577445 \| \| 1650093 \| 1650093.png \| 1917 \| 1078 \| image/png \| general \| solo smile brown_hair 1boy hat collarbone male_focus teeth japanese_clothes facial_hair clenched_teeth close-up stubble straw_hat head_out_of_frame \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5831.png \| 1.71312e+09 \| True \| 776 \| 349 \| 349 \| 776 \| 1080 \| 0.718519 \| 0.323148 \| 0.718519 \| 0.323148 \| 0.481859 \| \| 1650092 \| 1650092.png \| 1357 \| 1073 \| image/png \| sensitive \| open_mouth blonde_hair grey_hair male_focus weapon multiple_boys indoors sword 2boys cape facial_hair beard mustache old old_man \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5719.png \| 1.71312e+09 \| True \| 155 \| 232 \| 155 \| 232 \| 1080 \| 0.214815 \| 0.143519 \| 0.143519 \| 0.214815 \| 0.175584 \| \| 1650091 \| 1650091.png \| 1769 \| 1078 \| image/png \| general \| solo looking_at_viewer short_hair brown_hair 1boy upper_body male_focus japanese_clothes indoors looking_back from_behind fur_trim facial_hair thick_eyebrows stubble \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5697.png \| 1.71312e+09 \| True \| 314 \| 387 \| 314 \| 387 \| 1080 \| 0.358333 \| 0.290741 \| 0.290741 \| 0.358333 \| 0.322773 \| \| 1650090 \| 1650090.png \| 791 \| 900 \| image/png \| sensitive \| short_hair blonde_hair 1boy male_focus multiple_boys solo_focus indoors looking_back from_behind fur_trim \| BangumiBase/rurounikenshin2023 \| 651168aec3cb7ba5aae9a3e718cccc12156a524c \| 44 \| 5659.png \| 1.71312e+09 \| True \| 145 \| 99 \| 99 \| 145 \| 1080 \| 0.134259 \| 0.0916667 \| 0.134259 \| 0.0916667 \| 0.110937 \| ## Tags There are 8061 tags in total. These are the top 30 tags (1235 tags in total) of type `character`: \| tag \| type \| count \| \|:---------------------------------\|:----------\|--------:\| \| oumae_kumiko \| character \| 6518 \| \| misaka_mikoto \| character \| 5199 \| \| kinomoto_sakura \| character \| 4578 \| \| hirasawa_yui \| character \| 4321 \| \| sakata_gintoki \| character \| 4094 \| \| kirito \| character \| 3975 \| \| kamijou_touma \| character \| 3708 \| \| midoriya_izuku \| character \| 3589 \| \| natsuki_subaru \| character \| 3512 \| \| tainaka_ritsu \| character \| 3484 \| \| akiyama_mio \| character \| 3418 \| \| kurosaki_ichigo \| character \| 3350 \| \| nakano_azusa \| character \| 3245 \| \| lucy_heartfilia \| character \| 3019 \| \| monkey_d._luffy \| character \| 2980 \| \| kotobuki_tsumugi \| character \| 2956 \| \| shirai_kuroko \| character \| 2825 \| \| uzumaki_naruto \| character \| 2755 \| \| satou_kazuma \| character \| 2686 \| \| yoshida_yuuko_(machikado_mazoku) \| character \| 2426 \| \| kousaka_reina \| character \| 2291 \| \| araragi_koyomi \| character \| 2235 \| \| kamado_tanjirou \| character \| 2203 \| \| emiya_shirou \| character \| 2075 \| \| takagi-san \| character \| 2056 \| \| kazanari_tsubasa \| character \| 2017 \| \| gon_freecss \| character \| 1990 \| \| sora_harewataru \| character \| 1951 \| \| kafuu_chino \| character \| 1861 \| \| asirpa \| character \| 1835 \| These are the top 30 tags (6826 tags in total) of type `general`: \| tag \| type \| count \| \|:------------------\|:--------\|--------:\| \| solo \| general \| 866519 \| \| 1girl \| general \| 617253 \| \| 1boy \| general \| 533345 \| \| male_focus \| general \| 488199 \| \| short_hair \| general \| 472448 \| \| long_hair \| general \| 388260 \| \| black_hair \| general \| 383584 \| \| shirt \| general \| 363654 \| \| brown_hair \| general \| 340743 \| \| upper_body \| general \| 308224 \| \| closed_mouth \| general \| 288325 \| \| open_mouth \| general \| 271939 \| \| looking_at_viewer \| general \| 267001 \| \| smile \| general \| 252195 \| \| school_uniform \| general \| 215854 \| \| brown_eyes \| general \| 212886 \| \| blonde_hair \| general \| 184176 \| \| parody \| general \| 173041 \| \| jacket \| general \| 172627 \| \| outdoors \| general \| 172395 \| \| indoors \| general \| 169257 \| \| white_shirt \| general \| 164958 \| \| blush \| general \| 154054 \| \| long_sleeves \| general \| 152847 \| \| anime_coloring \| general \| 152375 \| \| blue_eyes \| general \| 145734 \| \| solo_focus \| general \| 143894 \| \| closed_eyes \| general \| 130706 \| \| holding \| general \| 127717 \| \| portrait \| general \| 127575 \|
aditijha/instruct_v1_2k	--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 1475295.9366042826 num_examples: 2000 download_size: 788725 dataset_size: 1475295.9366042826 --- # Dataset Card for "instruct_v1_2k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
phamtungthuy/cafedanluat2	--- dataset_info: features: - name: content dtype: string - name: question dtype: string - name: relevant_laws list: - name: law_id dtype: string - name: text dtype: string - name: split dtype: string - name: id dtype: string splits: - name: train num_bytes: 27357307 num_examples: 6616 download_size: 12227490 dataset_size: 27357307 configs: - config_name: default data_files: - split: train path: data/train-* ---
AdapterOcean/med_alpaca_standardized_cluster_7	--- dataset_info: features: - name: text dtype: string - name: conversation_id dtype: int64 - name: embedding sequence: float64 - name: cluster dtype: int64 splits: - name: train num_bytes: 73841362 num_examples: 7528 download_size: 21771105 dataset_size: 73841362 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_7" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Ssunbell/SROIE_layoutlmv2_sequence	--- dataset_info: features: - name: guid sequence: string - name: words sequence: string - name: labels sequence: int64 - name: boxes sequence: sequence: int64 - name: actual_bboxes sequence: sequence: int64 - name: file_name dtype: string - name: image sequence: sequence: sequence: uint8 splits: - name: train num_bytes: 98185080 num_examples: 594 - name: val num_bytes: 5264337 num_examples: 32 - name: test num_bytes: 57252300 num_examples: 347 download_size: 67438968 dataset_size: 160701717 --- # Dataset Card for "SROIE_layoutlmv2_sequence" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Mike0307/MNIST-M	--- license: mit dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': '0' '1': '1' '2': '2' '3': '3' '4': '4' '5': '5' '6': '6' '7': '7' '8': '8' '9': '9' splits: - name: train num_bytes: 119131988.027 num_examples: 59001 - name: test num_bytes: 18049625.166 num_examples: 9001 download_size: 143468539 dataset_size: 137181613.193 --- ## Train Example 👉[Domain-Adversarial-Neural-Network](https://github.com/yeyuting0307/Domain-Adversarial-Neural-Network)
version-control/the-stack-ds-lib-50k	--- dataset_info: features: - name: repo_name dtype: string - name: hexsha sequence: string - name: file_path sequence: string - name: code sequence: string - name: apis sequence: sequence: string splits: - name: train num_bytes: 616797241 num_examples: 40990 download_size: 221909836 dataset_size: 616797241 configs: - config_name: default data_files: - split: train path: data/train-* ---
CyberHarem/asagumo_kantaicollection	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of asagumo/朝雲 (Kantai Collection) This is the dataset of asagumo/朝雲 (Kantai Collection), containing 404 images and their tags. The core tags of this character are `brown_hair, long_hair, twintails, hair_ribbon, ribbon, grey_eyes`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages \| Name \| Images \| Size \| Download \| Type \| Description \| \|:-----------------\|---------:\|:-----------\|:--------------------------------------------------------------------------------------------------------------------------\|:-----------\|:---------------------------------------------------------------------\| \| raw \| 404 \| 314.31 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 404 \| 215.37 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 856 \| 433.91 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 404 \| 293.49 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 856 \| 553.79 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/asagumo_kantaicollection', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| Tags \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 7 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| 1girl, solo, white_shirt, grey_jacket, white_headband, buttons, grey_skirt, long_sleeves, pleated_skirt, simple_background, blue_necktie, closed_mouth, ponytail, white_background, collared_shirt, cowboy_shot, looking_at_viewer, official_alternate_costume, school_uniform \| \| 1 \| 17 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, grey_skirt, pleated_skirt, solo, white_shirt, blue_ascot, short_sleeves, suspender_skirt, arm_warmers, looking_at_viewer, simple_background, white_background, cowboy_shot, twitter_username, collared_shirt, black_thighhighs, school_uniform, smile \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, arm_warmers, ascot, black_thighhighs, looking_at_viewer, pleated_skirt, school_uniform, solo, suspenders, blush, grey_skirt, white_shirt, sitting, smile \| \| 3 \| 11 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| 1girl, looking_at_viewer, solo, cowboy_shot, blue_bikini, small_breasts, white_background, flat_chest, simple_background, blue_sky, blush, cloud, day, outdoors, side-tie_bikini_bottom, standing, twitter_username \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| solo \| white_shirt \| grey_jacket \| white_headband \| buttons \| grey_skirt \| long_sleeves \| pleated_skirt \| simple_background \| blue_necktie \| closed_mouth \| ponytail \| white_background \| collared_shirt \| cowboy_shot \| looking_at_viewer \| official_alternate_costume \| school_uniform \| blue_ascot \| short_sleeves \| suspender_skirt \| arm_warmers \| twitter_username \| black_thighhighs \| smile \| ascot \| suspenders \| blush \| sitting \| blue_bikini \| small_breasts \| flat_chest \| blue_sky \| cloud \| day \| outdoors \| side-tie_bikini_bottom \| standing \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-------\|:--------------\|:--------------\|:-----------------\|:----------\|:-------------\|:---------------\|:----------------\|:--------------------\|:---------------\|:---------------\|:-----------\|:-------------------\|:-----------------\|:--------------\|:--------------------\|:-----------------------------\|:-----------------\|:-------------\|:----------------\|:------------------\|:--------------\|:-------------------\|:-------------------\|:--------\|:--------\|:-------------\|:--------\|:----------\|:--------------\|:----------------\|:-------------\|:-----------\|:--------\|:------\|:-----------\|:-------------------------\|:-----------\| \| 0 \| 7 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 17 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| X \| X \| X \| \| \| \| X \| \| X \| X \| \| \| \| X \| X \| X \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| X \| X \| \| \| \| X \| \| X \| \| \| \| \| \| \| \| X \| \| X \| \| \| \| X \| \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| 3 \| 11 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| X \| X \| \| \| \| \| \| \| \| X \| \| \| \| X \| \| X \| X \| \| \| \| \| \| \| X \| \| \| \| \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
kkucheria/kkquickdataset	--- license: llama2 ---
ddtraveller/wisdom	--- license: mit task_categories: - table-question-answering language: - en size_categories: - 1K<n<10K ---
b583x2/test	--- license: apache-2.0 ---
Ninatacataca/dataset	--- license: openrail ---
Javtor/rock-paper-scissors	--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: 0: paper 1: rock 2: scissors splits: - name: test num_bytes: 29457688.0 num_examples: 372 - name: train num_bytes: 196585089.6 num_examples: 2520 download_size: 229783612 dataset_size: 226042777.6 --- # Dataset Card for "rock-paper-scissors" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
minoruskore/wlkjokj3454sd45sc45	--- license: other dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: user_id dtype: int64 - name: name dtype: string - name: anime_id dtype: int64 - name: anime dtype: string - name: rating dtype: int64 splits: - name: train num_bytes: 1386784355 num_examples: 19460153 - name: test num_bytes: 354541207 num_examples: 4865038 - name: train100k num_bytes: 5716739 num_examples: 80000 - name: test100k num_bytes: 1453191 num_examples: 20000 - name: train500k num_bytes: 28547903 num_examples: 400000 - name: test500k num_bytes: 7235060 num_examples: 100000 - name: train1kk num_bytes: 57023319 num_examples: 800000 - name: test1kk num_bytes: 14562005 num_examples: 200000 download_size: 832651093 dataset_size: 1855863779 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: train100k path: data/train100k-* - split: test100k path: data/test100k-* - split: train500k path: data/train500k-* - split: test500k path: data/test500k-* - split: train1kk path: data/train1kk-* - split: test1kk path: data/test1kk-* ---

automated-research-group/llama2_7b_chat-siqa-results

--- dataset_info: - config_name: '{''do_sample''=False, ''beams''=10}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96342 num_examples: 1935 download_size: 47737 dataset_size: 96342 - config_name: '{''do_sample''=False, ''beams''=1}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 180990 num_examples: 1935 download_size: 78972 dataset_size: 180990 - config_name: '{''do_sample''=False, ''beams''=5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96342 num_examples: 1935 download_size: 47737 dataset_size: 96342 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96734 num_examples: 1935 download_size: 47798 dataset_size: 96734 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96981 num_examples: 1935 download_size: 47639 dataset_size: 96981 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96734 num_examples: 1935 download_size: 47798 dataset_size: 96734 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96496 num_examples: 1935 download_size: 47755 dataset_size: 96496 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96746 num_examples: 1935 download_size: 47779 dataset_size: 96746 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96652 num_examples: 1935 download_size: 47680 dataset_size: 96652 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97052 num_examples: 1935 download_size: 47880 dataset_size: 97052 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111264 num_examples: 1935 download_size: 52779 dataset_size: 111264 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97197 num_examples: 1935 download_size: 47939 dataset_size: 97197 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 110781 num_examples: 1935 download_size: 50670 dataset_size: 110781 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97258 num_examples: 1935 download_size: 47698 dataset_size: 97258 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111045 num_examples: 1935 download_size: 50862 dataset_size: 111045 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 98672 num_examples: 1935 download_size: 48132 dataset_size: 98672 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 134089 num_examples: 1935 download_size: 61398 dataset_size: 134089 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 99516 num_examples: 1935 download_size: 48161 dataset_size: 99516 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 137455 num_examples: 1935 download_size: 62213 dataset_size: 137455 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 101581 num_examples: 1935 download_size: 48732 dataset_size: 101581 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 134295 num_examples: 1935 download_size: 61358 dataset_size: 134295 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96734 num_examples: 1935 download_size: 47798 dataset_size: 96734 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96561 num_examples: 1935 download_size: 47834 dataset_size: 96561 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96743 num_examples: 1935 download_size: 47805 dataset_size: 96743 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97090 num_examples: 1935 download_size: 47822 dataset_size: 97090 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96738 num_examples: 1935 download_size: 47791 dataset_size: 96738 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96023 num_examples: 1935 download_size: 47635 dataset_size: 96023 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97412 num_examples: 1935 download_size: 47951 dataset_size: 97412 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111967 num_examples: 1935 download_size: 52185 dataset_size: 111967 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96117 num_examples: 1935 download_size: 47458 dataset_size: 96117 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 112415 num_examples: 1935 download_size: 51502 dataset_size: 112415 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96624 num_examples: 1935 download_size: 47790 dataset_size: 96624 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 111988 num_examples: 1935 download_size: 51926 dataset_size: 111988 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 98309 num_examples: 1935 download_size: 47626 dataset_size: 98309 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 134350 num_examples: 1935 download_size: 61471 dataset_size: 134350 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 99802 num_examples: 1935 download_size: 48330 dataset_size: 99802 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 135980 num_examples: 1935 download_size: 61284 dataset_size: 135980 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 100008 num_examples: 1935 download_size: 48359 dataset_size: 100008 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 136931 num_examples: 1935 download_size: 62080 dataset_size: 136931 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96743 num_examples: 1935 download_size: 47805 dataset_size: 96743 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96689 num_examples: 1935 download_size: 47822 dataset_size: 96689 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96738 num_examples: 1935 download_size: 47791 dataset_size: 96738 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96052 num_examples: 1935 download_size: 47356 dataset_size: 96052 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96734 num_examples: 1935 download_size: 47798 dataset_size: 96734 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96659 num_examples: 1935 download_size: 47924 dataset_size: 96659 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97444 num_examples: 1935 download_size: 47973 dataset_size: 97444 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 112867 num_examples: 1935 download_size: 53176 dataset_size: 112867 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 97050 num_examples: 1935 download_size: 47889 dataset_size: 97050 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 112690 num_examples: 1935 download_size: 50935 dataset_size: 112690 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 96643 num_examples: 1935 download_size: 47676 dataset_size: 96643 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 113898 num_examples: 1935 download_size: 52185 dataset_size: 113898 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 98979 num_examples: 1935 download_size: 47482 dataset_size: 98979 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 136835 num_examples: 1935 download_size: 61929 dataset_size: 136835 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 99149 num_examples: 1935 download_size: 47983 dataset_size: 99149 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 137078 num_examples: 1935 download_size: 61948 dataset_size: 137078 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 100004 num_examples: 1935 download_size: 48201 dataset_size: 100004 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' features: - name: id dtype: string - name: prediction dtype: string - name: siqa_accuracy dtype: bool splits: - name: train num_bytes: 139488 num_examples: 1935 download_size: 64089 dataset_size: 139488 configs: - config_name: '{''do_sample''=False, ''beams''=10}' data_files: - split: train path: '{''do_sample''=False, ''beams''=10}/train-*' - config_name: '{''do_sample''=False, ''beams''=1}' data_files: - split: train path: '{''do_sample''=False, ''beams''=1}/train-*' - config_name: '{''do_sample''=False, ''beams''=5}' data_files: - split: train path: '{''do_sample''=False, ''beams''=5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.05, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.55, ''top_k''=10000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=100, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=1000, ''top_p''=1.0}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=0.5}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.05, ''top_k''=10000, ''top_p''=1.0}/train-*' ---

open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large

--- pretty_name: Evaluation run of LordNoah/Alpaca_spin_tuned_gpt2_large dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [LordNoah/Alpaca_spin_tuned_gpt2_large](https://huggingface.co/LordNoah/Alpaca_spin_tuned_gpt2_large)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-22T13:42:11.763277](https://huggingface.co/datasets/open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large/blob/main/results_2024-01-22T13-42-11.763277.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.27225604584142943,\n\ \ \"acc_stderr\": 0.03141590282455585,\n \"acc_norm\": 0.27399653003630087,\n\ \ \"acc_norm_stderr\": 0.03221603447267582,\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757449,\n \"mc2\": 0.39429285512218326,\n\ \ \"mc2_stderr\": 0.01421822540176183\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.2568259385665529,\n \"acc_stderr\": 0.0127669237941168,\n\ \ \"acc_norm\": 0.2790102389078498,\n \"acc_norm_stderr\": 0.013106784883601341\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.36297550288787095,\n\ \ \"acc_stderr\": 0.004798751281560822,\n \"acc_norm\": 0.45120493925512845,\n\ \ \"acc_norm_stderr\": 0.004965963647210318\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.24444444444444444,\n\ \ \"acc_stderr\": 0.037125378336148665,\n \"acc_norm\": 0.24444444444444444,\n\ \ \"acc_norm_stderr\": 0.037125378336148665\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.3026315789473684,\n \"acc_stderr\": 0.03738520676119667,\n\ \ \"acc_norm\": 0.3026315789473684,\n \"acc_norm_stderr\": 0.03738520676119667\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.24,\n\ \ \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.24,\n \ \ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.3433962264150943,\n \"acc_stderr\": 0.02922452646912479,\n\ \ \"acc_norm\": 0.3433962264150943,\n \"acc_norm_stderr\": 0.02922452646912479\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2569444444444444,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.2569444444444444,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.15,\n \"acc_stderr\": 0.03588702812826368,\n \ \ \"acc_norm\": 0.15,\n \"acc_norm_stderr\": 0.03588702812826368\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.34,\n \"acc_stderr\": 0.04760952285695236,\n \"acc_norm\": 0.34,\n\ \ \"acc_norm_stderr\": 0.04760952285695236\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.24277456647398843,\n\ \ \"acc_stderr\": 0.0326926380614177,\n \"acc_norm\": 0.24277456647398843,\n\ \ \"acc_norm_stderr\": 0.0326926380614177\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.042801058373643966,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.042801058373643966\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n\ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.30638297872340425,\n \"acc_stderr\": 0.030135906478517563,\n\ \ \"acc_norm\": 0.30638297872340425,\n \"acc_norm_stderr\": 0.030135906478517563\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.21929824561403508,\n\ \ \"acc_stderr\": 0.03892431106518753,\n \"acc_norm\": 0.21929824561403508,\n\ \ \"acc_norm_stderr\": 0.03892431106518753\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.30344827586206896,\n \"acc_stderr\": 0.038312260488503336,\n\ \ \"acc_norm\": 0.30344827586206896,\n \"acc_norm_stderr\": 0.038312260488503336\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2777777777777778,\n \"acc_stderr\": 0.023068188848261107,\n \"\ acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.023068188848261107\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2619047619047619,\n\ \ \"acc_stderr\": 0.03932537680392871,\n \"acc_norm\": 0.2619047619047619,\n\ \ \"acc_norm_stderr\": 0.03932537680392871\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.25806451612903225,\n\ \ \"acc_stderr\": 0.02489246917246284,\n \"acc_norm\": 0.25806451612903225,\n\ \ \"acc_norm_stderr\": 0.02489246917246284\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.30049261083743845,\n \"acc_stderr\": 0.03225799476233484,\n\ \ \"acc_norm\": 0.30049261083743845,\n \"acc_norm_stderr\": 0.03225799476233484\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.30303030303030304,\n \"acc_stderr\": 0.035886248000917075,\n\ \ \"acc_norm\": 0.30303030303030304,\n \"acc_norm_stderr\": 0.035886248000917075\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.35858585858585856,\n \"acc_stderr\": 0.03416903640391521,\n \"\ acc_norm\": 0.35858585858585856,\n \"acc_norm_stderr\": 0.03416903640391521\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.31088082901554404,\n \"acc_stderr\": 0.033403619062765885,\n\ \ \"acc_norm\": 0.31088082901554404,\n \"acc_norm_stderr\": 0.033403619062765885\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.358974358974359,\n \"acc_stderr\": 0.024321738484602357,\n \ \ \"acc_norm\": 0.358974358974359,\n \"acc_norm_stderr\": 0.024321738484602357\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.26296296296296295,\n \"acc_stderr\": 0.02684205787383371,\n \ \ \"acc_norm\": 0.26296296296296295,\n \"acc_norm_stderr\": 0.02684205787383371\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.2184873949579832,\n \"acc_stderr\": 0.026841514322958955,\n\ \ \"acc_norm\": 0.2184873949579832,\n \"acc_norm_stderr\": 0.026841514322958955\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.03631329803969653,\n \"acc_norm\"\ : 0.271523178807947,\n \"acc_norm_stderr\": 0.03631329803969653\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.3339449541284404,\n\ \ \"acc_stderr\": 0.020220554196736403,\n \"acc_norm\": 0.3339449541284404,\n\ \ \"acc_norm_stderr\": 0.020220554196736403\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.2824074074074074,\n \"acc_stderr\": 0.030701372111510927,\n\ \ \"acc_norm\": 0.2824074074074074,\n \"acc_norm_stderr\": 0.030701372111510927\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.25980392156862747,\n \"acc_stderr\": 0.030778554678693264,\n \"\ acc_norm\": 0.25980392156862747,\n \"acc_norm_stderr\": 0.030778554678693264\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n \ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.1031390134529148,\n\ \ \"acc_stderr\": 0.020412564289839272,\n \"acc_norm\": 0.1031390134529148,\n\ \ \"acc_norm_stderr\": 0.020412564289839272\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.2366412213740458,\n \"acc_stderr\": 0.037276735755969174,\n\ \ \"acc_norm\": 0.2366412213740458,\n \"acc_norm_stderr\": 0.037276735755969174\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.35537190082644626,\n \"acc_stderr\": 0.04369236326573981,\n \"\ acc_norm\": 0.35537190082644626,\n \"acc_norm_stderr\": 0.04369236326573981\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.2883435582822086,\n \"acc_stderr\": 0.035590395316173425,\n\ \ \"acc_norm\": 0.2883435582822086,\n \"acc_norm_stderr\": 0.035590395316173425\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.23214285714285715,\n\ \ \"acc_stderr\": 0.04007341809755807,\n \"acc_norm\": 0.23214285714285715,\n\ \ \"acc_norm_stderr\": 0.04007341809755807\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.3786407766990291,\n \"acc_stderr\": 0.04802694698258972,\n\ \ \"acc_norm\": 0.3786407766990291,\n \"acc_norm_stderr\": 0.04802694698258972\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2606837606837607,\n\ \ \"acc_stderr\": 0.028760348956523414,\n \"acc_norm\": 0.2606837606837607,\n\ \ \"acc_norm_stderr\": 0.028760348956523414\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.19,\n \"acc_stderr\": 0.03942772444036623,\n \ \ \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.03942772444036623\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.20434227330779056,\n\ \ \"acc_stderr\": 0.0144191239809319,\n \"acc_norm\": 0.20434227330779056,\n\ \ \"acc_norm_stderr\": 0.0144191239809319\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.2976878612716763,\n \"acc_stderr\": 0.024617055388677,\n\ \ \"acc_norm\": 0.2976878612716763,\n \"acc_norm_stderr\": 0.024617055388677\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217889,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217889\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.25163398692810457,\n \"acc_stderr\": 0.024848018263875195,\n\ \ \"acc_norm\": 0.25163398692810457,\n \"acc_norm_stderr\": 0.024848018263875195\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.3247588424437299,\n\ \ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.3247588424437299,\n\ \ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.023132376234543346,\n\ \ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.023132376234543346\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.2624113475177305,\n \"acc_stderr\": 0.026244920349843014,\n \ \ \"acc_norm\": 0.2624113475177305,\n \"acc_norm_stderr\": 0.026244920349843014\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.24445893089960888,\n\ \ \"acc_stderr\": 0.010976425013113893,\n \"acc_norm\": 0.24445893089960888,\n\ \ \"acc_norm_stderr\": 0.010976425013113893\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.26838235294117646,\n \"acc_stderr\": 0.02691748122437722,\n\ \ \"acc_norm\": 0.26838235294117646,\n \"acc_norm_stderr\": 0.02691748122437722\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.2434640522875817,\n \"acc_stderr\": 0.017362473762146623,\n \ \ \"acc_norm\": 0.2434640522875817,\n \"acc_norm_stderr\": 0.017362473762146623\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.2,\n\ \ \"acc_stderr\": 0.03831305140884603,\n \"acc_norm\": 0.2,\n \ \ \"acc_norm_stderr\": 0.03831305140884603\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.3224489795918367,\n \"acc_stderr\": 0.029923100563683903,\n\ \ \"acc_norm\": 0.3224489795918367,\n \"acc_norm_stderr\": 0.029923100563683903\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.24378109452736318,\n\ \ \"acc_stderr\": 0.03036049015401465,\n \"acc_norm\": 0.24378109452736318,\n\ \ \"acc_norm_stderr\": 0.03036049015401465\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.21686746987951808,\n\ \ \"acc_stderr\": 0.03208284450356365,\n \"acc_norm\": 0.21686746987951808,\n\ \ \"acc_norm_stderr\": 0.03208284450356365\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.29239766081871343,\n \"acc_stderr\": 0.034886477134579215,\n\ \ \"acc_norm\": 0.29239766081871343,\n \"acc_norm_stderr\": 0.034886477134579215\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757449,\n \"mc2\": 0.39429285512218326,\n\ \ \"mc2_stderr\": 0.01421822540176183\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.5461720599842147,\n \"acc_stderr\": 0.013992441563707063\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.006065200909780136,\n \ \ \"acc_stderr\": 0.00213867030146048\n }\n}\n```" repo_url: https://huggingface.co/LordNoah/Alpaca_spin_tuned_gpt2_large leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|arc:challenge|25_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-22T13-42-11.763277.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|gsm8k|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hellaswag|10_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-22T13-42-11.763277.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-management|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T13-42-11.763277.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|truthfulqa:mc|0_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-22T13-42-11.763277.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_22T13_42_11.763277 path: - '**/details_harness|winogrande|5_2024-01-22T13-42-11.763277.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-22T13-42-11.763277.parquet' - config_name: results data_files: - split: 2024_01_22T13_42_11.763277 path: - results_2024-01-22T13-42-11.763277.parquet - split: latest path: - results_2024-01-22T13-42-11.763277.parquet --- # Dataset Card for Evaluation run of LordNoah/Alpaca_spin_tuned_gpt2_large  Dataset automatically created during the evaluation run of model [LordNoah/Alpaca_spin_tuned_gpt2_large](https://huggingface.co/LordNoah/Alpaca_spin_tuned_gpt2_large) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-22T13:42:11.763277](https://huggingface.co/datasets/open-llm-leaderboard/details_LordNoah__Alpaca_spin_tuned_gpt2_large/blob/main/results_2024-01-22T13-42-11.763277.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.27225604584142943, "acc_stderr": 0.03141590282455585, "acc_norm": 0.27399653003630087, "acc_norm_stderr": 0.03221603447267582, "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757449, "mc2": 0.39429285512218326, "mc2_stderr": 0.01421822540176183 }, "harness|arc:challenge|25": { "acc": 0.2568259385665529, "acc_stderr": 0.0127669237941168, "acc_norm": 0.2790102389078498, "acc_norm_stderr": 0.013106784883601341 }, "harness|hellaswag|10": { "acc": 0.36297550288787095, "acc_stderr": 0.004798751281560822, "acc_norm": 0.45120493925512845, "acc_norm_stderr": 0.004965963647210318 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.24444444444444444, "acc_stderr": 0.037125378336148665, "acc_norm": 0.24444444444444444, "acc_norm_stderr": 0.037125378336148665 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.3026315789473684, "acc_stderr": 0.03738520676119667, "acc_norm": 0.3026315789473684, "acc_norm_stderr": 0.03738520676119667 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.3433962264150943, "acc_stderr": 0.02922452646912479, "acc_norm": 0.3433962264150943, "acc_norm_stderr": 0.02922452646912479 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.15, "acc_stderr": 0.03588702812826368, "acc_norm": 0.15, "acc_norm_stderr": 0.03588702812826368 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.24277456647398843, "acc_stderr": 0.0326926380614177, "acc_norm": 0.24277456647398843, "acc_norm_stderr": 0.0326926380614177 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.24509803921568626, "acc_stderr": 0.042801058373643966, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.042801058373643966 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.30638297872340425, "acc_stderr": 0.030135906478517563, "acc_norm": 0.30638297872340425, "acc_norm_stderr": 0.030135906478517563 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.21929824561403508, "acc_stderr": 0.03892431106518753, "acc_norm": 0.21929824561403508, "acc_norm_stderr": 0.03892431106518753 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.30344827586206896, "acc_stderr": 0.038312260488503336, "acc_norm": 0.30344827586206896, "acc_norm_stderr": 0.038312260488503336 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2777777777777778, "acc_stderr": 0.023068188848261107, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.023068188848261107 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2619047619047619, "acc_stderr": 0.03932537680392871, "acc_norm": 0.2619047619047619, "acc_norm_stderr": 0.03932537680392871 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.25806451612903225, "acc_stderr": 0.02489246917246284, "acc_norm": 0.25806451612903225, "acc_norm_stderr": 0.02489246917246284 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.30049261083743845, "acc_stderr": 0.03225799476233484, "acc_norm": 0.30049261083743845, "acc_norm_stderr": 0.03225799476233484 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.30303030303030304, "acc_stderr": 0.035886248000917075, "acc_norm": 0.30303030303030304, "acc_norm_stderr": 0.035886248000917075 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.35858585858585856, "acc_stderr": 0.03416903640391521, "acc_norm": 0.35858585858585856, "acc_norm_stderr": 0.03416903640391521 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.31088082901554404, "acc_stderr": 0.033403619062765885, "acc_norm": 0.31088082901554404, "acc_norm_stderr": 0.033403619062765885 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.358974358974359, "acc_stderr": 0.024321738484602357, "acc_norm": 0.358974358974359, "acc_norm_stderr": 0.024321738484602357 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.26296296296296295, "acc_stderr": 0.02684205787383371, "acc_norm": 0.26296296296296295, "acc_norm_stderr": 0.02684205787383371 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.2184873949579832, "acc_stderr": 0.026841514322958955, "acc_norm": 0.2184873949579832, "acc_norm_stderr": 0.026841514322958955 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.271523178807947, "acc_stderr": 0.03631329803969653, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.03631329803969653 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.3339449541284404, "acc_stderr": 0.020220554196736403, "acc_norm": 0.3339449541284404, "acc_norm_stderr": 0.020220554196736403 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.2824074074074074, "acc_stderr": 0.030701372111510927, "acc_norm": 0.2824074074074074, "acc_norm_stderr": 0.030701372111510927 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.25980392156862747, "acc_stderr": 0.030778554678693264, "acc_norm": 0.25980392156862747, "acc_norm_stderr": 0.030778554678693264 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.1031390134529148, "acc_stderr": 0.020412564289839272, "acc_norm": 0.1031390134529148, "acc_norm_stderr": 0.020412564289839272 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.2366412213740458, "acc_stderr": 0.037276735755969174, "acc_norm": 0.2366412213740458, "acc_norm_stderr": 0.037276735755969174 }, "harness|hendrycksTest-international_law|5": { "acc": 0.35537190082644626, "acc_stderr": 0.04369236326573981, "acc_norm": 0.35537190082644626, "acc_norm_stderr": 0.04369236326573981 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.25, "acc_stderr": 0.04186091791394607, "acc_norm": 0.25, "acc_norm_stderr": 0.04186091791394607 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.2883435582822086, "acc_stderr": 0.035590395316173425, "acc_norm": 0.2883435582822086, "acc_norm_stderr": 0.035590395316173425 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.23214285714285715, "acc_stderr": 0.04007341809755807, "acc_norm": 0.23214285714285715, "acc_norm_stderr": 0.04007341809755807 }, "harness|hendrycksTest-management|5": { "acc": 0.3786407766990291, "acc_stderr": 0.04802694698258972, "acc_norm": 0.3786407766990291, "acc_norm_stderr": 0.04802694698258972 }, "harness|hendrycksTest-marketing|5": { "acc": 0.2606837606837607, "acc_stderr": 0.028760348956523414, "acc_norm": 0.2606837606837607, "acc_norm_stderr": 0.028760348956523414 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.19, "acc_stderr": 0.03942772444036623, "acc_norm": 0.19, "acc_norm_stderr": 0.03942772444036623 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.20434227330779056, "acc_stderr": 0.0144191239809319, "acc_norm": 0.20434227330779056, "acc_norm_stderr": 0.0144191239809319 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.2976878612716763, "acc_stderr": 0.024617055388677, "acc_norm": 0.2976878612716763, "acc_norm_stderr": 0.024617055388677 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2424581005586592, "acc_stderr": 0.014333522059217889, "acc_norm": 0.2424581005586592, "acc_norm_stderr": 0.014333522059217889 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.25163398692810457, "acc_stderr": 0.024848018263875195, "acc_norm": 0.25163398692810457, "acc_norm_stderr": 0.024848018263875195 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.3247588424437299, "acc_stderr": 0.026596782287697043, "acc_norm": 0.3247588424437299, "acc_norm_stderr": 0.026596782287697043 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.2222222222222222, "acc_stderr": 0.023132376234543346, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.023132376234543346 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.2624113475177305, "acc_stderr": 0.026244920349843014, "acc_norm": 0.2624113475177305, "acc_norm_stderr": 0.026244920349843014 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.24445893089960888, "acc_stderr": 0.010976425013113893, "acc_norm": 0.24445893089960888, "acc_norm_stderr": 0.010976425013113893 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.26838235294117646, "acc_stderr": 0.02691748122437722, "acc_norm": 0.26838235294117646, "acc_norm_stderr": 0.02691748122437722 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.2434640522875817, "acc_stderr": 0.017362473762146623, "acc_norm": 0.2434640522875817, "acc_norm_stderr": 0.017362473762146623 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.2, "acc_stderr": 0.03831305140884603, "acc_norm": 0.2, "acc_norm_stderr": 0.03831305140884603 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.3224489795918367, "acc_stderr": 0.029923100563683903, "acc_norm": 0.3224489795918367, "acc_norm_stderr": 0.029923100563683903 }, "harness|hendrycksTest-sociology|5": { "acc": 0.24378109452736318, "acc_stderr": 0.03036049015401465, "acc_norm": 0.24378109452736318, "acc_norm_stderr": 0.03036049015401465 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-virology|5": { "acc": 0.21686746987951808, "acc_stderr": 0.03208284450356365, "acc_norm": 0.21686746987951808, "acc_norm_stderr": 0.03208284450356365 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.29239766081871343, "acc_stderr": 0.034886477134579215, "acc_norm": 0.29239766081871343, "acc_norm_stderr": 0.034886477134579215 }, "harness|truthfulqa:mc|0": { "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757449, "mc2": 0.39429285512218326, "mc2_stderr": 0.01421822540176183 }, "harness|winogrande|5": { "acc": 0.5461720599842147, "acc_stderr": 0.013992441563707063 }, "harness|gsm8k|5": { "acc": 0.006065200909780136, "acc_stderr": 0.00213867030146048 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### 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open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B

--- pretty_name: Evaluation run of vicgalleorg/TruthfulQwen1.5-1.8B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [vicgalleorg/TruthfulQwen1.5-1.8B](https://huggingface.co/vicgalleorg/TruthfulQwen1.5-1.8B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-04T13:58:06.789352](https://huggingface.co/datasets/open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B/blob/main/results_2024-03-04T13-58-06.789352.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.4680075333485934,\n\ \ \"acc_stderr\": 0.03457829883276736,\n \"acc_norm\": 0.4708825754058936,\n\ \ \"acc_norm_stderr\": 0.03529767780244664,\n \"mc1\": 0.2766217870257038,\n\ \ \"mc1_stderr\": 0.015659605755326923,\n \"mc2\": 0.4058019851571796,\n\ \ \"mc2_stderr\": 0.014539846563223038\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.36006825938566556,\n \"acc_stderr\": 0.014027516814585184,\n\ \ \"acc_norm\": 0.3873720136518771,\n \"acc_norm_stderr\": 0.014235872487909872\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4622585142401912,\n\ \ \"acc_stderr\": 0.00497554601895068,\n \"acc_norm\": 0.6135232025492929,\n\ \ \"acc_norm_stderr\": 0.004859467984155279\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.43703703703703706,\n\ \ \"acc_stderr\": 0.04284958639753399,\n \"acc_norm\": 0.43703703703703706,\n\ \ \"acc_norm_stderr\": 0.04284958639753399\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.47368421052631576,\n \"acc_stderr\": 0.04063302731486671,\n\ \ \"acc_norm\": 0.47368421052631576,\n \"acc_norm_stderr\": 0.04063302731486671\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.52,\n\ \ \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n \ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.5358490566037736,\n \"acc_stderr\": 0.030693675018458006,\n\ \ \"acc_norm\": 0.5358490566037736,\n \"acc_norm_stderr\": 0.030693675018458006\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.4236111111111111,\n\ \ \"acc_stderr\": 0.041321250197233685,\n \"acc_norm\": 0.4236111111111111,\n\ \ \"acc_norm_stderr\": 0.041321250197233685\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.46,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4161849710982659,\n\ \ \"acc_stderr\": 0.03758517775404947,\n \"acc_norm\": 0.4161849710982659,\n\ \ \"acc_norm_stderr\": 0.03758517775404947\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.27450980392156865,\n \"acc_stderr\": 0.044405219061793275,\n\ \ \"acc_norm\": 0.27450980392156865,\n \"acc_norm_stderr\": 0.044405219061793275\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.59,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.59,\n\ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.4085106382978723,\n \"acc_stderr\": 0.03213418026701576,\n\ \ \"acc_norm\": 0.4085106382978723,\n \"acc_norm_stderr\": 0.03213418026701576\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2982456140350877,\n\ \ \"acc_stderr\": 0.04303684033537314,\n \"acc_norm\": 0.2982456140350877,\n\ \ \"acc_norm_stderr\": 0.04303684033537314\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.4896551724137931,\n \"acc_stderr\": 0.041657747757287644,\n\ \ \"acc_norm\": 0.4896551724137931,\n \"acc_norm_stderr\": 0.041657747757287644\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.36243386243386244,\n \"acc_stderr\": 0.02475747390275205,\n \"\ acc_norm\": 0.36243386243386244,\n \"acc_norm_stderr\": 0.02475747390275205\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.23809523809523808,\n\ \ \"acc_stderr\": 0.03809523809523812,\n \"acc_norm\": 0.23809523809523808,\n\ \ \"acc_norm_stderr\": 0.03809523809523812\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.5419354838709678,\n\ \ \"acc_stderr\": 0.028343787250540632,\n \"acc_norm\": 0.5419354838709678,\n\ \ \"acc_norm_stderr\": 0.028343787250540632\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.3645320197044335,\n \"acc_stderr\": 0.033864057460620905,\n\ \ \"acc_norm\": 0.3645320197044335,\n \"acc_norm_stderr\": 0.033864057460620905\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \"acc_norm\"\ : 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6,\n \"acc_stderr\": 0.038254602783800246,\n \ \ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.038254602783800246\n \ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.5555555555555556,\n \"acc_stderr\": 0.035402943770953675,\n \"\ acc_norm\": 0.5555555555555556,\n \"acc_norm_stderr\": 0.035402943770953675\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.5647668393782384,\n \"acc_stderr\": 0.03578038165008586,\n\ \ \"acc_norm\": 0.5647668393782384,\n \"acc_norm_stderr\": 0.03578038165008586\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.4256410256410256,\n \"acc_stderr\": 0.02506909438729654,\n \ \ \"acc_norm\": 0.4256410256410256,\n \"acc_norm_stderr\": 0.02506909438729654\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.31851851851851853,\n \"acc_stderr\": 0.028406533090608463,\n \ \ \"acc_norm\": 0.31851851851851853,\n \"acc_norm_stderr\": 0.028406533090608463\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.39915966386554624,\n \"acc_stderr\": 0.03181110032413925,\n\ \ \"acc_norm\": 0.39915966386554624,\n \"acc_norm_stderr\": 0.03181110032413925\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360384,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360384\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.5944954128440367,\n \"acc_stderr\": 0.021050997991896837,\n \"\ acc_norm\": 0.5944954128440367,\n \"acc_norm_stderr\": 0.021050997991896837\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.2824074074074074,\n \"acc_stderr\": 0.030701372111510923,\n \"\ acc_norm\": 0.2824074074074074,\n \"acc_norm_stderr\": 0.030701372111510923\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.5049019607843137,\n \"acc_stderr\": 0.03509143375606786,\n \"\ acc_norm\": 0.5049019607843137,\n \"acc_norm_stderr\": 0.03509143375606786\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.6075949367088608,\n \"acc_stderr\": 0.03178471874564729,\n \ \ \"acc_norm\": 0.6075949367088608,\n \"acc_norm_stderr\": 0.03178471874564729\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5336322869955157,\n\ \ \"acc_stderr\": 0.03348180017060306,\n \"acc_norm\": 0.5336322869955157,\n\ \ \"acc_norm_stderr\": 0.03348180017060306\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5725190839694656,\n \"acc_stderr\": 0.04338920305792401,\n\ \ \"acc_norm\": 0.5725190839694656,\n \"acc_norm_stderr\": 0.04338920305792401\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7107438016528925,\n \"acc_stderr\": 0.041391127276354626,\n \"\ acc_norm\": 0.7107438016528925,\n \"acc_norm_stderr\": 0.041391127276354626\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5092592592592593,\n\ \ \"acc_stderr\": 0.04832853553437056,\n \"acc_norm\": 0.5092592592592593,\n\ \ \"acc_norm_stderr\": 0.04832853553437056\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.4601226993865031,\n \"acc_stderr\": 0.03915857291436972,\n\ \ \"acc_norm\": 0.4601226993865031,\n \"acc_norm_stderr\": 0.03915857291436972\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.32142857142857145,\n\ \ \"acc_stderr\": 0.04432804055291519,\n \"acc_norm\": 0.32142857142857145,\n\ \ \"acc_norm_stderr\": 0.04432804055291519\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.6504854368932039,\n \"acc_stderr\": 0.047211885060971716,\n\ \ \"acc_norm\": 0.6504854368932039,\n \"acc_norm_stderr\": 0.047211885060971716\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7649572649572649,\n\ \ \"acc_stderr\": 0.027778835904935444,\n \"acc_norm\": 0.7649572649572649,\n\ \ \"acc_norm_stderr\": 0.027778835904935444\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.55,\n \"acc_stderr\": 0.04999999999999998,\n \ \ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.04999999999999998\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6181353767560664,\n\ \ \"acc_stderr\": 0.017373732736677583,\n \"acc_norm\": 0.6181353767560664,\n\ \ \"acc_norm_stderr\": 0.017373732736677583\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.5289017341040463,\n \"acc_stderr\": 0.026874085883518348,\n\ \ \"acc_norm\": 0.5289017341040463,\n \"acc_norm_stderr\": 0.026874085883518348\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217892,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217892\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.5849673202614379,\n \"acc_stderr\": 0.028213504177824103,\n\ \ \"acc_norm\": 0.5849673202614379,\n \"acc_norm_stderr\": 0.028213504177824103\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.49517684887459806,\n\ \ \"acc_stderr\": 0.02839677044411129,\n \"acc_norm\": 0.49517684887459806,\n\ \ \"acc_norm_stderr\": 0.02839677044411129\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.4691358024691358,\n \"acc_stderr\": 0.027767689606833925,\n\ \ \"acc_norm\": 0.4691358024691358,\n \"acc_norm_stderr\": 0.027767689606833925\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.37943262411347517,\n \"acc_stderr\": 0.028947338851614105,\n \ \ \"acc_norm\": 0.37943262411347517,\n \"acc_norm_stderr\": 0.028947338851614105\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3683181225554107,\n\ \ \"acc_stderr\": 0.012319403369564637,\n \"acc_norm\": 0.3683181225554107,\n\ \ \"acc_norm_stderr\": 0.012319403369564637\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.39705882352941174,\n \"acc_stderr\": 0.02972215209928007,\n\ \ \"acc_norm\": 0.39705882352941174,\n \"acc_norm_stderr\": 0.02972215209928007\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.42483660130718953,\n \"acc_stderr\": 0.019997973035458333,\n \ \ \"acc_norm\": 0.42483660130718953,\n \"acc_norm_stderr\": 0.019997973035458333\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6,\n\ \ \"acc_stderr\": 0.0469237132203465,\n \"acc_norm\": 0.6,\n \ \ \"acc_norm_stderr\": 0.0469237132203465\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.49795918367346936,\n \"acc_stderr\": 0.0320089533497105,\n\ \ \"acc_norm\": 0.49795918367346936,\n \"acc_norm_stderr\": 0.0320089533497105\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6169154228855721,\n\ \ \"acc_stderr\": 0.0343751933733825,\n \"acc_norm\": 0.6169154228855721,\n\ \ \"acc_norm_stderr\": 0.0343751933733825\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.42771084337349397,\n\ \ \"acc_stderr\": 0.038515976837185335,\n \"acc_norm\": 0.42771084337349397,\n\ \ \"acc_norm_stderr\": 0.038515976837185335\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.5847953216374269,\n \"acc_stderr\": 0.03779275945503201,\n\ \ \"acc_norm\": 0.5847953216374269,\n \"acc_norm_stderr\": 0.03779275945503201\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2766217870257038,\n\ \ \"mc1_stderr\": 0.015659605755326923,\n \"mc2\": 0.4058019851571796,\n\ \ \"mc2_stderr\": 0.014539846563223038\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6037884767166535,\n \"acc_stderr\": 0.013746404157154946\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.3411675511751327,\n \ \ \"acc_stderr\": 0.01305911193583148\n }\n}\n```" repo_url: https://huggingface.co/vicgalleorg/TruthfulQwen1.5-1.8B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|arc:challenge|25_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-04T13-58-06.789352.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|gsm8k|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hellaswag|10_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-04T13-58-06.789352.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-management|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-04T13-58-06.789352.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|truthfulqa:mc|0_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-04T13-58-06.789352.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_04T13_58_06.789352 path: - '**/details_harness|winogrande|5_2024-03-04T13-58-06.789352.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-04T13-58-06.789352.parquet' - config_name: results data_files: - split: 2024_03_04T13_58_06.789352 path: - results_2024-03-04T13-58-06.789352.parquet - split: latest path: - results_2024-03-04T13-58-06.789352.parquet --- # Dataset Card for Evaluation run of vicgalleorg/TruthfulQwen1.5-1.8B  Dataset automatically created during the evaluation run of model [vicgalleorg/TruthfulQwen1.5-1.8B](https://huggingface.co/vicgalleorg/TruthfulQwen1.5-1.8B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-04T13:58:06.789352](https://huggingface.co/datasets/open-llm-leaderboard/details_vicgalleorg__TruthfulQwen1.5-1.8B/blob/main/results_2024-03-04T13-58-06.789352.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.4680075333485934, "acc_stderr": 0.03457829883276736, "acc_norm": 0.4708825754058936, "acc_norm_stderr": 0.03529767780244664, "mc1": 0.2766217870257038, "mc1_stderr": 0.015659605755326923, "mc2": 0.4058019851571796, "mc2_stderr": 0.014539846563223038 }, "harness|arc:challenge|25": { "acc": 0.36006825938566556, "acc_stderr": 0.014027516814585184, "acc_norm": 0.3873720136518771, "acc_norm_stderr": 0.014235872487909872 }, "harness|hellaswag|10": { "acc": 0.4622585142401912, "acc_stderr": 0.00497554601895068, "acc_norm": 0.6135232025492929, "acc_norm_stderr": 0.004859467984155279 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.43703703703703706, "acc_stderr": 0.04284958639753399, "acc_norm": 0.43703703703703706, "acc_norm_stderr": 0.04284958639753399 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.47368421052631576, "acc_stderr": 0.04063302731486671, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.04063302731486671 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5358490566037736, "acc_stderr": 0.030693675018458006, "acc_norm": 0.5358490566037736, "acc_norm_stderr": 0.030693675018458006 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4236111111111111, "acc_stderr": 0.041321250197233685, "acc_norm": 0.4236111111111111, "acc_norm_stderr": 0.041321250197233685 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4161849710982659, "acc_stderr": 0.03758517775404947, "acc_norm": 0.4161849710982659, "acc_norm_stderr": 0.03758517775404947 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.27450980392156865, "acc_stderr": 0.044405219061793275, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.044405219061793275 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4085106382978723, "acc_stderr": 0.03213418026701576, "acc_norm": 0.4085106382978723, "acc_norm_stderr": 0.03213418026701576 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2982456140350877, "acc_stderr": 0.04303684033537314, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.04303684033537314 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4896551724137931, "acc_stderr": 0.041657747757287644, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.041657747757287644 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.36243386243386244, "acc_stderr": 0.02475747390275205, "acc_norm": 0.36243386243386244, "acc_norm_stderr": 0.02475747390275205 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.23809523809523808, "acc_stderr": 0.03809523809523812, "acc_norm": 0.23809523809523808, "acc_norm_stderr": 0.03809523809523812 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5419354838709678, "acc_stderr": 0.028343787250540632, "acc_norm": 0.5419354838709678, "acc_norm_stderr": 0.028343787250540632 }, 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0.6, "acc_norm_stderr": 0.0469237132203465 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.49795918367346936, "acc_stderr": 0.0320089533497105, "acc_norm": 0.49795918367346936, "acc_norm_stderr": 0.0320089533497105 }, "harness|hendrycksTest-sociology|5": { "acc": 0.6169154228855721, "acc_stderr": 0.0343751933733825, "acc_norm": 0.6169154228855721, "acc_norm_stderr": 0.0343751933733825 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-virology|5": { "acc": 0.42771084337349397, "acc_stderr": 0.038515976837185335, "acc_norm": 0.42771084337349397, "acc_norm_stderr": 0.038515976837185335 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.5847953216374269, "acc_stderr": 0.03779275945503201, "acc_norm": 0.5847953216374269, "acc_norm_stderr": 0.03779275945503201 }, "harness|truthfulqa:mc|0": { "mc1": 0.2766217870257038, "mc1_stderr": 0.015659605755326923, "mc2": 0.4058019851571796, "mc2_stderr": 0.014539846563223038 }, "harness|winogrande|5": { "acc": 0.6037884767166535, "acc_stderr": 0.013746404157154946 }, "harness|gsm8k|5": { "acc": 0.3411675511751327, "acc_stderr": 0.01305911193583148 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

luna-code/sqlmodel

--- dataset_info: features: - name: prompt dtype: string - name: completion dtype: string - name: api dtype: string splits: - name: train num_bytes: 2894322 num_examples: 1663 - name: test num_bytes: 92483 num_examples: 44 download_size: 450555 dataset_size: 2986805 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

huggingartists/booker

--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/booker" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - **Homepage:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Repository:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of the generated dataset:** 0.782002 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/fb0d7cebfd97c76d99f1015b6ddc0e55.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/booker"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Booker</div> <a href="https://genius.com/artists/booker"> <div style="text-align: center; font-size: 14px;">@booker</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/booker). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/booker") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits | train |validation|test| |------:|---------:|---:| |196| -| -| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/booker") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About *Built by Aleksey Korshuk* [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)

blabble-io/libritts

--- license: cc-by-4.0 task_categories: - text-to-speech language: - en size_categories: - 10K<n<100K configs: - config_name: dev data_files: - split: dev.clean path: "data/dev.clean/dev.clean*.parquet" - config_name: clean data_files: - split: dev.clean path: "data/dev.clean/dev.clean*.parquet" - split: test.clean path: "data/test.clean/test.clean*.parquet" - split: train.clean.100 path: "data/train.clean.100/train.clean.100*.parquet" - split: train.clean.360 path: "data/train.clean.360/train.clean.360*.parquet" - config_name: other data_files: - split: dev.other path: "data/dev.other/dev.other*.parquet" - split: test.other path: "data/test.other/test.other*.parquet" - split: train.other.500 path: "data/train.other.500/train.other.500*.parquet" - config_name: all data_files: - split: dev.clean path: "data/dev.clean/dev.clean*.parquet" - split: dev.other path: "data/dev.other/dev.other*.parquet" - split: test.clean path: "data/test.clean/test.clean*.parquet" - split: test.other path: "data/test.other/test.other*.parquet" - split: train.clean.100 path: "data/train.clean.100/train.clean.100*.parquet" - split: train.clean.360 path: "data/train.clean.360/train.clean.360*.parquet" - split: train.other.500 path: "data/train.other.500/train.other.500*.parquet" --- # Dataset Card for LibriTTS  LibriTTS is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz sampling rate, prepared by Heiga Zen with the assistance of Google Speech and Google Brain team members. The LibriTTS corpus is designed for TTS research. It is derived from the original materials (mp3 audio files from LibriVox and text files from Project Gutenberg) of the LibriSpeech corpus. ## Overview This is the LibriTTS dataset, adapted for the `datasets` library. ## Usage ### Splits There are 7 splits (dots replace dashes from the original dataset, to comply with hf naming requirements): - dev.clean - dev.other - test.clean - test.other - train.clean.100 - train.clean.360 - train.other.500 ### Configurations There are 3 configurations, each which limits the splits the `load_dataset()` function will download. The default configuration is "all". - "dev": only the "dev.clean" split (good for testing the dataset quickly) - "clean": contains only "clean" splits - "other": contains only "other" splits - "all": contains only "all" splits ### Example Loading the `clean` config with only the `train.clean.360` split. ``` load_dataset("blabble-io/libritts", "clean", split="train.clean.100") ``` Streaming is also supported. ``` load_dataset("blabble-io/libritts", streaming=True) ``` ### Columns ``` { "audio": datasets.Audio(sampling_rate=24_000), "text_normalized": datasets.Value("string"), "text_original": datasets.Value("string"), "speaker_id": datasets.Value("string"), "path": datasets.Value("string"), "chapter_id": datasets.Value("string"), "id": datasets.Value("string"), } ``` ### Example Row ``` { 'audio': { 'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/5551a515e85b9e463062524539c2e1cb52ba32affe128dffd866db0205248bdd/LibriTTS/dev-clean/3081/166546/3081_166546_000028_000002.wav', 'array': ..., 'sampling_rate': 24000 }, 'text_normalized': 'How quickly he disappeared!"', 'text_original': 'How quickly he disappeared!"', 'speaker_id': '3081', 'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/5551a515e85b9e463062524539c2e1cb52ba32affe128dffd866db0205248bdd/LibriTTS/dev-clean/3081/166546/3081_166546_000028_000002.wav', 'chapter_id': '166546', 'id': '3081_166546_000028_000002' } ``` ## Dataset Details ### Dataset Description - **License:** CC BY 4.0 ### Dataset Sources [optional]  - **Homepage:** https://www.openslr.org/60/ - **Paper:** https://arxiv.org/abs/1904.02882 ## Citation  ``` @ARTICLE{Zen2019-kz, title = "{LibriTTS}: A corpus derived from {LibriSpeech} for text-to-speech", author = "Zen, Heiga and Dang, Viet and Clark, Rob and Zhang, Yu and Weiss, Ron J and Jia, Ye and Chen, Zhifeng and Wu, Yonghui", abstract = "This paper introduces a new speech corpus called ``LibriTTS'' designed for text-to-speech use. It is derived from the original audio and text materials of the LibriSpeech corpus, which has been used for training and evaluating automatic speech recognition systems. The new corpus inherits desired properties of the LibriSpeech corpus while addressing a number of issues which make LibriSpeech less than ideal for text-to-speech work. The released corpus consists of 585 hours of speech data at 24kHz sampling rate from 2,456 speakers and the corresponding texts. Experimental results show that neural end-to-end TTS models trained from the LibriTTS corpus achieved above 4.0 in mean opinion scores in naturalness in five out of six evaluation speakers. The corpus is freely available for download from http://www.openslr.org/60/.", month = apr, year = 2019, copyright = "http://arxiv.org/licenses/nonexclusive-distrib/1.0/", archivePrefix = "arXiv", primaryClass = "cs.SD", eprint = "1904.02882" } ```

BangumiBase/jigokushoujo

--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Jigoku Shoujo This is the image base of bangumi Jigoku Shoujo, we detected 89 characters, 6611 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 538 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 26 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 26 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 102 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 52 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 434 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 637 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 703 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 102 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 56 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 50 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 73 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 35 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 109 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 211 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 127 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 25 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 81 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 18 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 31 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 51 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 109 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 46 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 42 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 78 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 31 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 136 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 48 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 30 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 49 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 27 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 29 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 44 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | ![preview 8](32/preview_8.png) | | 33 | 428 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 41 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 55 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 40 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 23 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | ![preview 8](37/preview_8.png) | | 38 | 271 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 41 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 42 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 39 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | 42 | 12 | [Download](42/dataset.zip) | ![preview 1](42/preview_1.png) | ![preview 2](42/preview_2.png) | ![preview 3](42/preview_3.png) | ![preview 4](42/preview_4.png) | ![preview 5](42/preview_5.png) | ![preview 6](42/preview_6.png) | ![preview 7](42/preview_7.png) | ![preview 8](42/preview_8.png) | | 43 | 23 | [Download](43/dataset.zip) | ![preview 1](43/preview_1.png) | ![preview 2](43/preview_2.png) | ![preview 3](43/preview_3.png) | ![preview 4](43/preview_4.png) | ![preview 5](43/preview_5.png) | ![preview 6](43/preview_6.png) | ![preview 7](43/preview_7.png) | ![preview 8](43/preview_8.png) | | 44 | 26 | [Download](44/dataset.zip) | ![preview 1](44/preview_1.png) | ![preview 2](44/preview_2.png) | ![preview 3](44/preview_3.png) | ![preview 4](44/preview_4.png) | ![preview 5](44/preview_5.png) | ![preview 6](44/preview_6.png) | ![preview 7](44/preview_7.png) | ![preview 8](44/preview_8.png) | | 45 | 68 | [Download](45/dataset.zip) | ![preview 1](45/preview_1.png) | ![preview 2](45/preview_2.png) | ![preview 3](45/preview_3.png) | ![preview 4](45/preview_4.png) | ![preview 5](45/preview_5.png) | ![preview 6](45/preview_6.png) | ![preview 7](45/preview_7.png) | ![preview 8](45/preview_8.png) | | 46 | 47 | [Download](46/dataset.zip) | ![preview 1](46/preview_1.png) | ![preview 2](46/preview_2.png) | ![preview 3](46/preview_3.png) | ![preview 4](46/preview_4.png) | ![preview 5](46/preview_5.png) | ![preview 6](46/preview_6.png) | ![preview 7](46/preview_7.png) | ![preview 8](46/preview_8.png) | | 47 | 53 | [Download](47/dataset.zip) | ![preview 1](47/preview_1.png) | ![preview 2](47/preview_2.png) | ![preview 3](47/preview_3.png) | ![preview 4](47/preview_4.png) | ![preview 5](47/preview_5.png) | ![preview 6](47/preview_6.png) | ![preview 7](47/preview_7.png) | ![preview 8](47/preview_8.png) | | 48 | 24 | [Download](48/dataset.zip) | ![preview 1](48/preview_1.png) | ![preview 2](48/preview_2.png) | ![preview 3](48/preview_3.png) | ![preview 4](48/preview_4.png) | ![preview 5](48/preview_5.png) | ![preview 6](48/preview_6.png) | ![preview 7](48/preview_7.png) | ![preview 8](48/preview_8.png) | | 49 | 26 | [Download](49/dataset.zip) | ![preview 1](49/preview_1.png) | ![preview 2](49/preview_2.png) | ![preview 3](49/preview_3.png) | ![preview 4](49/preview_4.png) | ![preview 5](49/preview_5.png) | ![preview 6](49/preview_6.png) | ![preview 7](49/preview_7.png) | ![preview 8](49/preview_8.png) | | 50 | 185 | [Download](50/dataset.zip) | ![preview 1](50/preview_1.png) | ![preview 2](50/preview_2.png) | ![preview 3](50/preview_3.png) | ![preview 4](50/preview_4.png) | ![preview 5](50/preview_5.png) | ![preview 6](50/preview_6.png) | ![preview 7](50/preview_7.png) | ![preview 8](50/preview_8.png) | | 51 | 46 | [Download](51/dataset.zip) | ![preview 1](51/preview_1.png) | ![preview 2](51/preview_2.png) | ![preview 3](51/preview_3.png) | ![preview 4](51/preview_4.png) | ![preview 5](51/preview_5.png) | ![preview 6](51/preview_6.png) | ![preview 7](51/preview_7.png) | ![preview 8](51/preview_8.png) | | 52 | 32 | [Download](52/dataset.zip) | ![preview 1](52/preview_1.png) | ![preview 2](52/preview_2.png) | ![preview 3](52/preview_3.png) | ![preview 4](52/preview_4.png) | ![preview 5](52/preview_5.png) | ![preview 6](52/preview_6.png) | ![preview 7](52/preview_7.png) | ![preview 8](52/preview_8.png) | | 53 | 27 | [Download](53/dataset.zip) | ![preview 1](53/preview_1.png) | ![preview 2](53/preview_2.png) | ![preview 3](53/preview_3.png) | ![preview 4](53/preview_4.png) | ![preview 5](53/preview_5.png) | ![preview 6](53/preview_6.png) | ![preview 7](53/preview_7.png) | ![preview 8](53/preview_8.png) | | 54 | 50 | [Download](54/dataset.zip) | ![preview 1](54/preview_1.png) | ![preview 2](54/preview_2.png) | ![preview 3](54/preview_3.png) | ![preview 4](54/preview_4.png) | ![preview 5](54/preview_5.png) | ![preview 6](54/preview_6.png) | ![preview 7](54/preview_7.png) | ![preview 8](54/preview_8.png) | | 55 | 40 | [Download](55/dataset.zip) | ![preview 1](55/preview_1.png) | ![preview 2](55/preview_2.png) | ![preview 3](55/preview_3.png) | ![preview 4](55/preview_4.png) | ![preview 5](55/preview_5.png) | ![preview 6](55/preview_6.png) | ![preview 7](55/preview_7.png) | ![preview 8](55/preview_8.png) | | 56 | 12 | [Download](56/dataset.zip) | ![preview 1](56/preview_1.png) | ![preview 2](56/preview_2.png) | ![preview 3](56/preview_3.png) | ![preview 4](56/preview_4.png) | ![preview 5](56/preview_5.png) | ![preview 6](56/preview_6.png) | ![preview 7](56/preview_7.png) | ![preview 8](56/preview_8.png) | | 57 | 25 | [Download](57/dataset.zip) | ![preview 1](57/preview_1.png) | ![preview 2](57/preview_2.png) | ![preview 3](57/preview_3.png) | ![preview 4](57/preview_4.png) | ![preview 5](57/preview_5.png) | ![preview 6](57/preview_6.png) | ![preview 7](57/preview_7.png) | ![preview 8](57/preview_8.png) | | 58 | 35 | [Download](58/dataset.zip) | ![preview 1](58/preview_1.png) | ![preview 2](58/preview_2.png) | ![preview 3](58/preview_3.png) | ![preview 4](58/preview_4.png) | ![preview 5](58/preview_5.png) | ![preview 6](58/preview_6.png) | ![preview 7](58/preview_7.png) | ![preview 8](58/preview_8.png) | | 59 | 17 | [Download](59/dataset.zip) | ![preview 1](59/preview_1.png) | ![preview 2](59/preview_2.png) | ![preview 3](59/preview_3.png) | ![preview 4](59/preview_4.png) | ![preview 5](59/preview_5.png) | ![preview 6](59/preview_6.png) | ![preview 7](59/preview_7.png) | ![preview 8](59/preview_8.png) | | 60 | 66 | [Download](60/dataset.zip) | ![preview 1](60/preview_1.png) | ![preview 2](60/preview_2.png) | ![preview 3](60/preview_3.png) | ![preview 4](60/preview_4.png) | ![preview 5](60/preview_5.png) | ![preview 6](60/preview_6.png) | ![preview 7](60/preview_7.png) | ![preview 8](60/preview_8.png) | | 61 | 41 | [Download](61/dataset.zip) | ![preview 1](61/preview_1.png) | ![preview 2](61/preview_2.png) | ![preview 3](61/preview_3.png) | ![preview 4](61/preview_4.png) | ![preview 5](61/preview_5.png) | ![preview 6](61/preview_6.png) | ![preview 7](61/preview_7.png) | ![preview 8](61/preview_8.png) | | 62 | 28 | [Download](62/dataset.zip) | ![preview 1](62/preview_1.png) | ![preview 2](62/preview_2.png) | ![preview 3](62/preview_3.png) | ![preview 4](62/preview_4.png) | ![preview 5](62/preview_5.png) | ![preview 6](62/preview_6.png) | ![preview 7](62/preview_7.png) | ![preview 8](62/preview_8.png) | | 63 | 21 | [Download](63/dataset.zip) | ![preview 1](63/preview_1.png) | ![preview 2](63/preview_2.png) | ![preview 3](63/preview_3.png) | ![preview 4](63/preview_4.png) | ![preview 5](63/preview_5.png) | ![preview 6](63/preview_6.png) | ![preview 7](63/preview_7.png) | ![preview 8](63/preview_8.png) | | 64 | 17 | [Download](64/dataset.zip) | ![preview 1](64/preview_1.png) | ![preview 2](64/preview_2.png) | ![preview 3](64/preview_3.png) | ![preview 4](64/preview_4.png) | ![preview 5](64/preview_5.png) | ![preview 6](64/preview_6.png) | ![preview 7](64/preview_7.png) | ![preview 8](64/preview_8.png) | | 65 | 16 | [Download](65/dataset.zip) | ![preview 1](65/preview_1.png) | ![preview 2](65/preview_2.png) | ![preview 3](65/preview_3.png) | ![preview 4](65/preview_4.png) | ![preview 5](65/preview_5.png) | ![preview 6](65/preview_6.png) | ![preview 7](65/preview_7.png) | ![preview 8](65/preview_8.png) | | 66 | 54 | [Download](66/dataset.zip) | ![preview 1](66/preview_1.png) | ![preview 2](66/preview_2.png) | ![preview 3](66/preview_3.png) | ![preview 4](66/preview_4.png) | ![preview 5](66/preview_5.png) | ![preview 6](66/preview_6.png) | ![preview 7](66/preview_7.png) | ![preview 8](66/preview_8.png) | | 67 | 22 | [Download](67/dataset.zip) | ![preview 1](67/preview_1.png) | ![preview 2](67/preview_2.png) | ![preview 3](67/preview_3.png) | ![preview 4](67/preview_4.png) | ![preview 5](67/preview_5.png) | ![preview 6](67/preview_6.png) | ![preview 7](67/preview_7.png) | ![preview 8](67/preview_8.png) | | 68 | 17 | [Download](68/dataset.zip) | ![preview 1](68/preview_1.png) | ![preview 2](68/preview_2.png) | ![preview 3](68/preview_3.png) | ![preview 4](68/preview_4.png) | ![preview 5](68/preview_5.png) | ![preview 6](68/preview_6.png) | ![preview 7](68/preview_7.png) | ![preview 8](68/preview_8.png) | | 69 | 9 | [Download](69/dataset.zip) | ![preview 1](69/preview_1.png) | ![preview 2](69/preview_2.png) | ![preview 3](69/preview_3.png) | ![preview 4](69/preview_4.png) | ![preview 5](69/preview_5.png) | ![preview 6](69/preview_6.png) | ![preview 7](69/preview_7.png) | ![preview 8](69/preview_8.png) | | 70 | 21 | [Download](70/dataset.zip) | ![preview 1](70/preview_1.png) | ![preview 2](70/preview_2.png) | ![preview 3](70/preview_3.png) | ![preview 4](70/preview_4.png) | ![preview 5](70/preview_5.png) | ![preview 6](70/preview_6.png) | ![preview 7](70/preview_7.png) | ![preview 8](70/preview_8.png) | | 71 | 30 | [Download](71/dataset.zip) | ![preview 1](71/preview_1.png) | ![preview 2](71/preview_2.png) | ![preview 3](71/preview_3.png) | ![preview 4](71/preview_4.png) | ![preview 5](71/preview_5.png) | ![preview 6](71/preview_6.png) | ![preview 7](71/preview_7.png) | ![preview 8](71/preview_8.png) | | 72 | 15 | [Download](72/dataset.zip) | ![preview 1](72/preview_1.png) | ![preview 2](72/preview_2.png) | ![preview 3](72/preview_3.png) | ![preview 4](72/preview_4.png) | ![preview 5](72/preview_5.png) | ![preview 6](72/preview_6.png) | ![preview 7](72/preview_7.png) | ![preview 8](72/preview_8.png) | | 73 | 21 | [Download](73/dataset.zip) | ![preview 1](73/preview_1.png) | ![preview 2](73/preview_2.png) | ![preview 3](73/preview_3.png) | ![preview 4](73/preview_4.png) | ![preview 5](73/preview_5.png) | ![preview 6](73/preview_6.png) | ![preview 7](73/preview_7.png) | ![preview 8](73/preview_8.png) | | 74 | 19 | [Download](74/dataset.zip) | ![preview 1](74/preview_1.png) | ![preview 2](74/preview_2.png) | ![preview 3](74/preview_3.png) | ![preview 4](74/preview_4.png) | ![preview 5](74/preview_5.png) | ![preview 6](74/preview_6.png) | ![preview 7](74/preview_7.png) | ![preview 8](74/preview_8.png) | | 75 | 13 | [Download](75/dataset.zip) | ![preview 1](75/preview_1.png) | ![preview 2](75/preview_2.png) | ![preview 3](75/preview_3.png) | ![preview 4](75/preview_4.png) | ![preview 5](75/preview_5.png) | ![preview 6](75/preview_6.png) | ![preview 7](75/preview_7.png) | ![preview 8](75/preview_8.png) | | 76 | 17 | [Download](76/dataset.zip) | ![preview 1](76/preview_1.png) | ![preview 2](76/preview_2.png) | ![preview 3](76/preview_3.png) | ![preview 4](76/preview_4.png) | ![preview 5](76/preview_5.png) | ![preview 6](76/preview_6.png) | ![preview 7](76/preview_7.png) | ![preview 8](76/preview_8.png) | | 77 | 13 | [Download](77/dataset.zip) | ![preview 1](77/preview_1.png) | ![preview 2](77/preview_2.png) | ![preview 3](77/preview_3.png) | ![preview 4](77/preview_4.png) | ![preview 5](77/preview_5.png) | ![preview 6](77/preview_6.png) | ![preview 7](77/preview_7.png) | ![preview 8](77/preview_8.png) | | 78 | 101 | [Download](78/dataset.zip) | ![preview 1](78/preview_1.png) | ![preview 2](78/preview_2.png) | ![preview 3](78/preview_3.png) | ![preview 4](78/preview_4.png) | ![preview 5](78/preview_5.png) | ![preview 6](78/preview_6.png) | ![preview 7](78/preview_7.png) | ![preview 8](78/preview_8.png) | | 79 | 17 | [Download](79/dataset.zip) | ![preview 1](79/preview_1.png) | ![preview 2](79/preview_2.png) | ![preview 3](79/preview_3.png) | ![preview 4](79/preview_4.png) | ![preview 5](79/preview_5.png) | ![preview 6](79/preview_6.png) | ![preview 7](79/preview_7.png) | ![preview 8](79/preview_8.png) | | 80 | 23 | [Download](80/dataset.zip) | ![preview 1](80/preview_1.png) | ![preview 2](80/preview_2.png) | ![preview 3](80/preview_3.png) | ![preview 4](80/preview_4.png) | ![preview 5](80/preview_5.png) | ![preview 6](80/preview_6.png) | ![preview 7](80/preview_7.png) | ![preview 8](80/preview_8.png) | | 81 | 23 | [Download](81/dataset.zip) | ![preview 1](81/preview_1.png) | ![preview 2](81/preview_2.png) | ![preview 3](81/preview_3.png) | ![preview 4](81/preview_4.png) | ![preview 5](81/preview_5.png) | ![preview 6](81/preview_6.png) | ![preview 7](81/preview_7.png) | ![preview 8](81/preview_8.png) | | 82 | 7 | [Download](82/dataset.zip) | ![preview 1](82/preview_1.png) | ![preview 2](82/preview_2.png) | ![preview 3](82/preview_3.png) | ![preview 4](82/preview_4.png) | ![preview 5](82/preview_5.png) | ![preview 6](82/preview_6.png) | ![preview 7](82/preview_7.png) | N/A | | 83 | 7 | [Download](83/dataset.zip) | ![preview 1](83/preview_1.png) | ![preview 2](83/preview_2.png) | ![preview 3](83/preview_3.png) | ![preview 4](83/preview_4.png) | ![preview 5](83/preview_5.png) | ![preview 6](83/preview_6.png) | ![preview 7](83/preview_7.png) | N/A | | 84 | 29 | [Download](84/dataset.zip) | ![preview 1](84/preview_1.png) | ![preview 2](84/preview_2.png) | ![preview 3](84/preview_3.png) | ![preview 4](84/preview_4.png) | ![preview 5](84/preview_5.png) | ![preview 6](84/preview_6.png) | ![preview 7](84/preview_7.png) | ![preview 8](84/preview_8.png) | | 85 | 14 | [Download](85/dataset.zip) | ![preview 1](85/preview_1.png) | ![preview 2](85/preview_2.png) | ![preview 3](85/preview_3.png) | ![preview 4](85/preview_4.png) | ![preview 5](85/preview_5.png) | ![preview 6](85/preview_6.png) | ![preview 7](85/preview_7.png) | ![preview 8](85/preview_8.png) | | 86 | 5 | [Download](86/dataset.zip) | ![preview 1](86/preview_1.png) | ![preview 2](86/preview_2.png) | ![preview 3](86/preview_3.png) | ![preview 4](86/preview_4.png) | ![preview 5](86/preview_5.png) | N/A | N/A | N/A | | 87 | 7 | [Download](87/dataset.zip) | ![preview 1](87/preview_1.png) | ![preview 2](87/preview_2.png) | ![preview 3](87/preview_3.png) | ![preview 4](87/preview_4.png) | ![preview 5](87/preview_5.png) | ![preview 6](87/preview_6.png) | ![preview 7](87/preview_7.png) | N/A | | noise | 54 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |

maghwa/OpenHermes-2-AR-10K-38-820k-830k

--- dataset_info: features: - name: model_name dtype: 'null' - name: idx dtype: 'null' - name: language dtype: 'null' - name: skip_prompt_formatting dtype: 'null' - name: custom_instruction dtype: 'null' - name: conversations dtype: string - name: system_prompt dtype: 'null' - name: id dtype: 'null' - name: model dtype: 'null' - name: category dtype: 'null' - name: hash dtype: 'null' - name: avatarUrl dtype: 'null' - name: source dtype: string - name: topic dtype: 'null' - name: views dtype: float64 - name: title dtype: 'null' splits: - name: train num_bytes: 25256647 num_examples: 10001 download_size: 11400617 dataset_size: 25256647 configs: - config_name: default data_files: - split: train path: data/train-* ---

delphi-suite/v0-next-logprobs-llama2-1.6m

--- dataset_info: features: - name: logprobs sequence: float64 splits: - name: validation num_bytes: 45818277 num_examples: 10982 download_size: 37795921 dataset_size: 45818277 configs: - config_name: default data_files: - split: validation path: data/validation-* ---

MaryLux/banking_sentiment

--- dataset_info: features: - name: text dtype: string - name: inputs struct: - name: text dtype: string - name: prediction list: - name: label dtype: string - name: score dtype: float64 - name: prediction_agent dtype: string - name: annotation dtype: 'null' - name: annotation_agent dtype: 'null' - name: vectors dtype: 'null' - name: multi_label dtype: bool - name: explanation dtype: 'null' - name: id dtype: string - name: metadata struct: - name: category dtype: int64 - name: status dtype: string - name: event_timestamp dtype: timestamp[us] - name: metrics dtype: 'null' splits: - name: train num_bytes: 1445808 num_examples: 5001 download_size: 672079 dataset_size: 1445808 --- # Dataset Card for "banking_sentiment" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Dahoas/prompted_svamp

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 1179345 num_examples: 700 - name: test num_bytes: 499449 num_examples: 300 download_size: 702499 dataset_size: 1678794 --- # Dataset Card for "prompted_svamp" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

HuggingFaceM4/imagenet1k_support_5k_query_sets_part_1

Invalid username or password.

Svenni551/questions

--- dataset_info: features: - name: asker dtype: string - name: question dtype: string splits: - name: train num_bytes: 27697 num_examples: 318 download_size: 9920 dataset_size: 27697 configs: - config_name: default data_files: - split: train path: data/train-* ---

jack008/TTR

--- license: unknown ---

Weni/LLM_Base_2.0.3_SFT

--- dataset_info: features: - name: prompt dtype: string - name: question dtype: string - name: answer dtype: string - name: context dtype: string - name: correct_ans dtype: int64 splits: - name: train num_bytes: 73736965 num_examples: 39345 download_size: 25677022 dataset_size: 73736965 configs: - config_name: default data_files: - split: train path: data/train-* ---

realfolkcode/open-music-dataset-demo

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: audio dtype: audio - name: caption dtype: string splits: - name: train num_bytes: 387155570.0 num_examples: 8 download_size: 386530208 dataset_size: 387155570.0 --- # Dataset Card for "open-music-dataset-demo" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Maxis47/Irons

--- license: unlicense task_categories: - text-to-image language: - en tags: - art size_categories: - 1M<n<10M ---

NobodyExistsOnTheInternet/ToxicQAtextFiltered

--- license: mit tags: - not-for-all-audiences --- This is the TEXT filtered version of TOXICQA with all the semi-refusals (e.g. Remember, killing is bad) This is a work in progress. Use only for Alignment research. NOETI is not responsible for what you might do with it.

el2e10/aya-paraphrase-malayalam

--- language: - ml license: cc size_categories: - n<1K source_datasets: - extended|ai4bharat/IndicXParaphrase task_categories: - text-generation pretty_name: Aya Paraphrase Malayalam dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: template_lang dtype: string - name: template_id dtype: int64 splits: - name: train num_bytes: 710999 num_examples: 1001 download_size: 255190 dataset_size: 710999 configs: - config_name: default data_files: - split: train path: data/train-* --- ### Description This dataset is derived from the already existing dataset made by AI4Bharat. We have used the [IndicXParaphrase](https://huggingface.co/datasets/ai4bharat/IndicXParaphrase) dataset of AI4Bharat to create this instruction style dataset. We have used the malayalam split of the above mentioned dataset to create this one. This was created as part of [Aya Open Science Initiative](https://sites.google.com/cohere.com/aya-en/home) from Cohere For AI. IndicXParaphrase is multilingual, and n-way parallel dataset for paraphrase detection in 10 Indic languages. The original dataset(IndicXParaphrase) was made available under the cc-0 license. ### Template The following templates(Malayalam) where used for converting the original dataset: ``` #Template 1 prompt: ഇനിപ്പറയുന്ന വാചകം വ്യത്യസ്ത വാക്കുകളിൽ എഴുതുക: "{original_sentence}" completion: {paraphrased_sentence} ``` ``` #Template 2 prompt: ഇനിപ്പറയുന്ന വാചകം മറ്റൊരു രീതിയിൽ എഴുതുക: "{original_sentence}" completion: {paraphrased_sentence} ``` ``` #Template 3 prompt: താഴെപ്പറയുന്ന വാചകം പരാവർത്തനം ചെയ്യുക: "{original_sentence}" completion: {paraphrased_sentence} ```

open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1

--- pretty_name: Evaluation run of cloudyu/mistral_18B_instruct_v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [cloudyu/mistral_18B_instruct_v0.1](https://huggingface.co/cloudyu/mistral_18B_instruct_v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-05T02:39:44.844538](https://huggingface.co/datasets/open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1/blob/main/results_2024-03-05T02-39-44.844538.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6039258028692152,\n\ \ \"acc_stderr\": 0.03320637767752478,\n \"acc_norm\": 0.6081395694844028,\n\ \ \"acc_norm_stderr\": 0.03388517114573973,\n \"mc1\": 0.4663402692778458,\n\ \ \"mc1_stderr\": 0.017463793867168106,\n \"mc2\": 0.6484634670784011,\n\ \ \"mc2_stderr\": 0.015219765533463015\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5477815699658704,\n \"acc_stderr\": 0.01454451988063383,\n\ \ \"acc_norm\": 0.5691126279863481,\n \"acc_norm_stderr\": 0.014471133392642466\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6204939255128461,\n\ \ \"acc_stderr\": 0.004842723234022032,\n \"acc_norm\": 0.8135829516032663,\n\ \ \"acc_norm_stderr\": 0.0038864693752987305\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6074074074074074,\n\ \ \"acc_stderr\": 0.04218506215368879,\n \"acc_norm\": 0.6074074074074074,\n\ \ \"acc_norm_stderr\": 0.04218506215368879\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6578947368421053,\n \"acc_stderr\": 0.03860731599316092,\n\ \ \"acc_norm\": 0.6578947368421053,\n \"acc_norm_stderr\": 0.03860731599316092\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6754716981132075,\n \"acc_stderr\": 0.02881561571343211,\n\ \ \"acc_norm\": 0.6754716981132075,\n \"acc_norm_stderr\": 0.02881561571343211\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6597222222222222,\n\ \ \"acc_stderr\": 0.039621355734862175,\n \"acc_norm\": 0.6597222222222222,\n\ \ \"acc_norm_stderr\": 0.039621355734862175\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.51,\n\ \ \"acc_stderr\": 0.05024183937956911,\n \"acc_norm\": 0.51,\n \ \ \"acc_norm_stderr\": 0.05024183937956911\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6069364161849711,\n\ \ \"acc_stderr\": 0.03724249595817731,\n \"acc_norm\": 0.6069364161849711,\n\ \ \"acc_norm_stderr\": 0.03724249595817731\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.04784060704105654,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.04784060704105654\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.71,\n \"acc_stderr\": 0.04560480215720684,\n \"acc_norm\": 0.71,\n\ \ \"acc_norm_stderr\": 0.04560480215720684\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5446808510638298,\n \"acc_stderr\": 0.03255525359340355,\n\ \ \"acc_norm\": 0.5446808510638298,\n \"acc_norm_stderr\": 0.03255525359340355\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.41228070175438597,\n\ \ \"acc_stderr\": 0.04630653203366595,\n \"acc_norm\": 0.41228070175438597,\n\ \ \"acc_norm_stderr\": 0.04630653203366595\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6,\n \"acc_stderr\": 0.04082482904638629,\n \ \ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.04082482904638629\n },\n\ \ \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\": 0.3862433862433862,\n\ \ \"acc_stderr\": 0.025075981767601684,\n \"acc_norm\": 0.3862433862433862,\n\ \ \"acc_norm_stderr\": 0.025075981767601684\n },\n \"harness|hendrycksTest-formal_logic|5\"\ : {\n \"acc\": 0.40476190476190477,\n \"acc_stderr\": 0.04390259265377562,\n\ \ \"acc_norm\": 0.40476190476190477,\n \"acc_norm_stderr\": 0.04390259265377562\n\ \ },\n \"harness|hendrycksTest-global_facts|5\": {\n \"acc\": 0.34,\n\ \ \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n \ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness|hendrycksTest-high_school_biology|5\"\ : {\n \"acc\": 0.5645161290322581,\n \"acc_stderr\": 0.02820622559150274,\n\ \ \"acc_norm\": 0.5645161290322581,\n \"acc_norm_stderr\": 0.02820622559150274\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.5024630541871922,\n \"acc_stderr\": 0.03517945038691063,\n \"\ acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7212121212121212,\n \"acc_stderr\": 0.03501438706296781,\n\ \ \"acc_norm\": 0.7212121212121212,\n \"acc_norm_stderr\": 0.03501438706296781\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7727272727272727,\n \"acc_stderr\": 0.029857515673386417,\n \"\ acc_norm\": 0.7727272727272727,\n \"acc_norm_stderr\": 0.029857515673386417\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8393782383419689,\n \"acc_stderr\": 0.02649905770139746,\n\ \ \"acc_norm\": 0.8393782383419689,\n \"acc_norm_stderr\": 0.02649905770139746\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5794871794871795,\n \"acc_stderr\": 0.025028610276710862,\n\ \ \"acc_norm\": 0.5794871794871795,\n \"acc_norm_stderr\": 0.025028610276710862\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.32592592592592595,\n \"acc_stderr\": 0.028578348365473082,\n \ \ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.028578348365473082\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.030868682604121626,\n\ \ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.030868682604121626\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.39072847682119205,\n \"acc_stderr\": 0.03983798306659807,\n \"\ acc_norm\": 0.39072847682119205,\n \"acc_norm_stderr\": 0.03983798306659807\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8,\n \"acc_stderr\": 0.01714985851425095,\n \"acc_norm\": 0.8,\n\ \ \"acc_norm_stderr\": 0.01714985851425095\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.4861111111111111,\n \"acc_stderr\": 0.03408655867977748,\n\ \ \"acc_norm\": 0.4861111111111111,\n \"acc_norm_stderr\": 0.03408655867977748\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7303921568627451,\n \"acc_stderr\": 0.031145570659486782,\n \"\ acc_norm\": 0.7303921568627451,\n \"acc_norm_stderr\": 0.031145570659486782\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7426160337552743,\n \"acc_stderr\": 0.02845882099146031,\n \ \ \"acc_norm\": 0.7426160337552743,\n \"acc_norm_stderr\": 0.02845882099146031\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6591928251121076,\n\ \ \"acc_stderr\": 0.031811497470553604,\n \"acc_norm\": 0.6591928251121076,\n\ \ \"acc_norm_stderr\": 0.031811497470553604\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7251908396946565,\n \"acc_stderr\": 0.03915345408847837,\n\ \ \"acc_norm\": 0.7251908396946565,\n \"acc_norm_stderr\": 0.03915345408847837\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.754601226993865,\n \"acc_stderr\": 0.03380939813943354,\n\ \ \"acc_norm\": 0.754601226993865,\n \"acc_norm_stderr\": 0.03380939813943354\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.45535714285714285,\n\ \ \"acc_stderr\": 0.04726835553719099,\n \"acc_norm\": 0.45535714285714285,\n\ \ \"acc_norm_stderr\": 0.04726835553719099\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7184466019417476,\n \"acc_stderr\": 0.04453254836326466,\n\ \ \"acc_norm\": 0.7184466019417476,\n \"acc_norm_stderr\": 0.04453254836326466\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8461538461538461,\n\ \ \"acc_stderr\": 0.0236368733174893,\n \"acc_norm\": 0.8461538461538461,\n\ \ \"acc_norm_stderr\": 0.0236368733174893\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7854406130268199,\n\ \ \"acc_stderr\": 0.014680033956893346,\n \"acc_norm\": 0.7854406130268199,\n\ \ \"acc_norm_stderr\": 0.014680033956893346\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6791907514450867,\n \"acc_stderr\": 0.025131000233647893,\n\ \ \"acc_norm\": 0.6791907514450867,\n \"acc_norm_stderr\": 0.025131000233647893\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3642458100558659,\n\ \ \"acc_stderr\": 0.016094338768474596,\n \"acc_norm\": 0.3642458100558659,\n\ \ \"acc_norm_stderr\": 0.016094338768474596\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.026787453111906497,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.026787453111906497\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6881028938906752,\n\ \ \"acc_stderr\": 0.02631185807185416,\n \"acc_norm\": 0.6881028938906752,\n\ \ \"acc_norm_stderr\": 0.02631185807185416\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6820987654320988,\n \"acc_stderr\": 0.02591006352824088,\n\ \ \"acc_norm\": 0.6820987654320988,\n \"acc_norm_stderr\": 0.02591006352824088\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.450354609929078,\n \"acc_stderr\": 0.02968010556502904,\n \ \ \"acc_norm\": 0.450354609929078,\n \"acc_norm_stderr\": 0.02968010556502904\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4041720990873533,\n\ \ \"acc_stderr\": 0.012533504046491362,\n \"acc_norm\": 0.4041720990873533,\n\ \ \"acc_norm_stderr\": 0.012533504046491362\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6397058823529411,\n \"acc_stderr\": 0.029163128570670733,\n\ \ \"acc_norm\": 0.6397058823529411,\n \"acc_norm_stderr\": 0.029163128570670733\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6143790849673203,\n \"acc_stderr\": 0.019691459052354025,\n \ \ \"acc_norm\": 0.6143790849673203,\n \"acc_norm_stderr\": 0.019691459052354025\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7,\n\ \ \"acc_stderr\": 0.04389311454644287,\n \"acc_norm\": 0.7,\n \ \ \"acc_norm_stderr\": 0.04389311454644287\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.710204081632653,\n \"acc_stderr\": 0.02904308868330433,\n\ \ \"acc_norm\": 0.710204081632653,\n \"acc_norm_stderr\": 0.02904308868330433\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6915422885572139,\n\ \ \"acc_stderr\": 0.03265819588512698,\n \"acc_norm\": 0.6915422885572139,\n\ \ \"acc_norm_stderr\": 0.03265819588512698\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4879518072289157,\n\ \ \"acc_stderr\": 0.03891364495835821,\n \"acc_norm\": 0.4879518072289157,\n\ \ \"acc_norm_stderr\": 0.03891364495835821\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.02954774168764004,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.02954774168764004\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4663402692778458,\n\ \ \"mc1_stderr\": 0.017463793867168106,\n \"mc2\": 0.6484634670784011,\n\ \ \"mc2_stderr\": 0.015219765533463015\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7703235990528808,\n \"acc_stderr\": 0.011821645601838232\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.40333586050037906,\n \ \ \"acc_stderr\": 0.013512654781814694\n }\n}\n```" repo_url: https://huggingface.co/cloudyu/mistral_18B_instruct_v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|arc:challenge|25_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-05T02-39-44.844538.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|gsm8k|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hellaswag|10_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-05T02-39-44.844538.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-management|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-05T02-39-44.844538.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|truthfulqa:mc|0_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-05T02-39-44.844538.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_05T02_39_44.844538 path: - '**/details_harness|winogrande|5_2024-03-05T02-39-44.844538.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-05T02-39-44.844538.parquet' - config_name: results data_files: - split: 2024_03_05T02_39_44.844538 path: - results_2024-03-05T02-39-44.844538.parquet - split: latest path: - results_2024-03-05T02-39-44.844538.parquet --- # Dataset Card for Evaluation run of cloudyu/mistral_18B_instruct_v0.1  Dataset automatically created during the evaluation run of model [cloudyu/mistral_18B_instruct_v0.1](https://huggingface.co/cloudyu/mistral_18B_instruct_v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-05T02:39:44.844538](https://huggingface.co/datasets/open-llm-leaderboard/details_cloudyu__mistral_18B_instruct_v0.1/blob/main/results_2024-03-05T02-39-44.844538.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6039258028692152, "acc_stderr": 0.03320637767752478, "acc_norm": 0.6081395694844028, "acc_norm_stderr": 0.03388517114573973, "mc1": 0.4663402692778458, "mc1_stderr": 0.017463793867168106, "mc2": 0.6484634670784011, "mc2_stderr": 0.015219765533463015 }, "harness|arc:challenge|25": { "acc": 0.5477815699658704, "acc_stderr": 0.01454451988063383, "acc_norm": 0.5691126279863481, "acc_norm_stderr": 0.014471133392642466 }, "harness|hellaswag|10": { "acc": 0.6204939255128461, "acc_stderr": 0.004842723234022032, "acc_norm": 0.8135829516032663, "acc_norm_stderr": 0.0038864693752987305 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6074074074074074, "acc_stderr": 0.04218506215368879, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.04218506215368879 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6578947368421053, "acc_stderr": 0.03860731599316092, "acc_norm": 0.6578947368421053, "acc_norm_stderr": 0.03860731599316092 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6754716981132075, "acc_stderr": 0.02881561571343211, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.02881561571343211 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6597222222222222, "acc_stderr": 0.039621355734862175, "acc_norm": 0.6597222222222222, "acc_norm_stderr": 0.039621355734862175 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6069364161849711, "acc_stderr": 0.03724249595817731, "acc_norm": 0.6069364161849711, "acc_norm_stderr": 0.03724249595817731 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105654, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105654 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.71, "acc_stderr": 0.04560480215720684, "acc_norm": 0.71, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.41228070175438597, "acc_stderr": 0.04630653203366595, "acc_norm": 0.41228070175438597, "acc_norm_stderr": 0.04630653203366595 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6, "acc_stderr": 0.04082482904638629, "acc_norm": 0.6, "acc_norm_stderr": 0.04082482904638629 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3862433862433862, "acc_stderr": 0.025075981767601684, "acc_norm": 0.3862433862433862, "acc_norm_stderr": 0.025075981767601684 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.40476190476190477, "acc_stderr": 0.04390259265377562, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.04390259265377562 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5645161290322581, "acc_stderr": 0.02820622559150274, "acc_norm": 0.5645161290322581, "acc_norm_stderr": 0.02820622559150274 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5024630541871922, "acc_stderr": 0.03517945038691063, "acc_norm": 0.5024630541871922, "acc_norm_stderr": 0.03517945038691063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7212121212121212, "acc_stderr": 0.03501438706296781, "acc_norm": 0.7212121212121212, "acc_norm_stderr": 0.03501438706296781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7727272727272727, "acc_stderr": 0.029857515673386417, "acc_norm": 0.7727272727272727, "acc_norm_stderr": 0.029857515673386417 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8393782383419689, "acc_stderr": 0.02649905770139746, "acc_norm": 0.8393782383419689, "acc_norm_stderr": 0.02649905770139746 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5794871794871795, "acc_stderr": 0.025028610276710862, "acc_norm": 0.5794871794871795, "acc_norm_stderr": 0.025028610276710862 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32592592592592595, "acc_stderr": 0.028578348365473082, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.028578348365473082 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6554621848739496, "acc_stderr": 0.030868682604121626, "acc_norm": 0.6554621848739496, "acc_norm_stderr": 0.030868682604121626 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.39072847682119205, "acc_stderr": 0.03983798306659807, "acc_norm": 0.39072847682119205, "acc_norm_stderr": 0.03983798306659807 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8, "acc_stderr": 0.01714985851425095, "acc_norm": 0.8, "acc_norm_stderr": 0.01714985851425095 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4861111111111111, "acc_stderr": 0.03408655867977748, "acc_norm": 0.4861111111111111, "acc_norm_stderr": 0.03408655867977748 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7303921568627451, "acc_stderr": 0.031145570659486782, "acc_norm": 0.7303921568627451, "acc_norm_stderr": 0.031145570659486782 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7426160337552743, "acc_stderr": 0.02845882099146031, "acc_norm": 0.7426160337552743, "acc_norm_stderr": 0.02845882099146031 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6591928251121076, "acc_stderr": 0.031811497470553604, "acc_norm": 0.6591928251121076, "acc_norm_stderr": 0.031811497470553604 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7251908396946565, "acc_stderr": 0.03915345408847837, "acc_norm": 0.7251908396946565, "acc_norm_stderr": 0.03915345408847837 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228732, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228732 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.754601226993865, "acc_stderr": 0.03380939813943354, "acc_norm": 0.754601226993865, "acc_norm_stderr": 0.03380939813943354 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.45535714285714285, "acc_stderr": 0.04726835553719099, "acc_norm": 0.45535714285714285, "acc_norm_stderr": 0.04726835553719099 }, "harness|hendrycksTest-management|5": { "acc": 0.7184466019417476, "acc_stderr": 0.04453254836326466, "acc_norm": 0.7184466019417476, "acc_norm_stderr": 0.04453254836326466 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8461538461538461, "acc_stderr": 0.0236368733174893, "acc_norm": 0.8461538461538461, "acc_norm_stderr": 0.0236368733174893 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7854406130268199, "acc_stderr": 0.014680033956893346, "acc_norm": 0.7854406130268199, "acc_norm_stderr": 0.014680033956893346 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6791907514450867, "acc_stderr": 0.025131000233647893, "acc_norm": 0.6791907514450867, "acc_norm_stderr": 0.025131000233647893 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.3642458100558659, "acc_stderr": 0.016094338768474596, "acc_norm": 0.3642458100558659, "acc_norm_stderr": 0.016094338768474596 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6764705882352942, "acc_stderr": 0.026787453111906497, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.026787453111906497 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6881028938906752, "acc_stderr": 0.02631185807185416, "acc_norm": 0.6881028938906752, "acc_norm_stderr": 0.02631185807185416 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6820987654320988, "acc_stderr": 0.02591006352824088, "acc_norm": 0.6820987654320988, "acc_norm_stderr": 0.02591006352824088 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.450354609929078, "acc_stderr": 0.02968010556502904, "acc_norm": 0.450354609929078, "acc_norm_stderr": 0.02968010556502904 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4041720990873533, "acc_stderr": 0.012533504046491362, "acc_norm": 0.4041720990873533, "acc_norm_stderr": 0.012533504046491362 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6397058823529411, "acc_stderr": 0.029163128570670733, "acc_norm": 0.6397058823529411, "acc_norm_stderr": 0.029163128570670733 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6143790849673203, "acc_stderr": 0.019691459052354025, "acc_norm": 0.6143790849673203, "acc_norm_stderr": 0.019691459052354025 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7, "acc_stderr": 0.04389311454644287, "acc_norm": 0.7, "acc_norm_stderr": 0.04389311454644287 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.710204081632653, "acc_stderr": 0.02904308868330433, "acc_norm": 0.710204081632653, "acc_norm_stderr": 0.02904308868330433 }, "harness|hendrycksTest-sociology|5": { "acc": 0.6915422885572139, "acc_stderr": 0.03265819588512698, "acc_norm": 0.6915422885572139, "acc_norm_stderr": 0.03265819588512698 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness|hendrycksTest-virology|5": { "acc": 0.4879518072289157, "acc_stderr": 0.03891364495835821, "acc_norm": 0.4879518072289157, "acc_norm_stderr": 0.03891364495835821 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8187134502923976, "acc_stderr": 0.02954774168764004, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.02954774168764004 }, "harness|truthfulqa:mc|0": { "mc1": 0.4663402692778458, "mc1_stderr": 0.017463793867168106, "mc2": 0.6484634670784011, "mc2_stderr": 0.015219765533463015 }, "harness|winogrande|5": { "acc": 0.7703235990528808, "acc_stderr": 0.011821645601838232 }, "harness|gsm8k|5": { "acc": 0.40333586050037906, "acc_stderr": 0.013512654781814694 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

AlekseyKorshuk/sharegpt-chatml

--- dataset_info: features: - name: conversation list: - name: content dtype: string - name: do_train dtype: bool - name: role dtype: string splits: - name: train num_bytes: 628712441 num_examples: 94145 download_size: 0 dataset_size: 628712441 --- # Dataset Card for "sharegpt-chatml" Data preprocessing pipeline: https://github.com/AlekseyKorshuk/chat-data-pipeline

open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache

--- pretty_name: Evaluation run of saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache](https://huggingface.co/saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-28T18:15:46.929459](https://huggingface.co/datasets/open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache/blob/main/results_2024-01-28T18-15-46.929459.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.23209302149061675,\n\ \ \"acc_stderr\": 0.02992707807148158,\n \"acc_norm\": 0.23163380863022787,\n\ \ \"acc_norm_stderr\": 0.03071316471647595,\n \"mc1\": 0.23011015911872704,\n\ \ \"mc1_stderr\": 0.014734557959807763,\n \"mc2\": 0.48987576662324334,\n\ \ \"mc2_stderr\": 0.016135847085052512\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.2022184300341297,\n \"acc_stderr\": 0.011737454431872104,\n\ \ \"acc_norm\": 0.23037542662116042,\n \"acc_norm_stderr\": 0.01230492841874761\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.25951005775741887,\n\ \ \"acc_stderr\": 0.004374699189284863,\n \"acc_norm\": 0.25941047600079664,\n\ \ \"acc_norm_stderr\": 0.004374153847826759\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.18518518518518517,\n\ \ \"acc_stderr\": 0.03355677216313142,\n \"acc_norm\": 0.18518518518518517,\n\ \ \"acc_norm_stderr\": 0.03355677216313142\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.17763157894736842,\n \"acc_stderr\": 0.031103182383123398,\n\ \ \"acc_norm\": 0.17763157894736842,\n \"acc_norm_stderr\": 0.031103182383123398\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.21509433962264152,\n \"acc_stderr\": 0.02528839450289137,\n\ \ \"acc_norm\": 0.21509433962264152,\n \"acc_norm_stderr\": 0.02528839450289137\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2569444444444444,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.2569444444444444,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036845,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036845\n },\n\ \ \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.26,\n\ \ \"acc_stderr\": 0.0440844002276808,\n \"acc_norm\": 0.26,\n \ \ \"acc_norm_stderr\": 0.0440844002276808\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \ \ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.20809248554913296,\n\ \ \"acc_stderr\": 0.030952890217749874,\n \"acc_norm\": 0.20809248554913296,\n\ \ \"acc_norm_stderr\": 0.030952890217749874\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237654,\n\ \ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237654\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.045126085985421276\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102973,\n\ \ \"acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102973\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813365,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813365\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135302,\n\ \ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135302\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.20899470899470898,\n \"acc_stderr\": 0.02094048156533486,\n \"\ acc_norm\": 0.20899470899470898,\n \"acc_norm_stderr\": 0.02094048156533486\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2857142857142857,\n\ \ \"acc_stderr\": 0.04040610178208841,\n \"acc_norm\": 0.2857142857142857,\n\ \ \"acc_norm_stderr\": 0.04040610178208841\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.18,\n \"acc_stderr\": 0.038612291966536934,\n \ \ \"acc_norm\": 0.18,\n \"acc_norm_stderr\": 0.038612291966536934\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.1774193548387097,\n \"acc_stderr\": 0.02173254068932927,\n \"\ acc_norm\": 0.1774193548387097,\n \"acc_norm_stderr\": 0.02173254068932927\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.15270935960591134,\n \"acc_stderr\": 0.02530890453938063,\n \"\ acc_norm\": 0.15270935960591134,\n \"acc_norm_stderr\": 0.02530890453938063\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.17676767676767677,\n \"acc_stderr\": 0.027178752639044915,\n \"\ acc_norm\": 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860664,\n\ \ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.20256410256410257,\n \"acc_stderr\": 0.020377660970371372,\n\ \ \"acc_norm\": 0.20256410256410257,\n \"acc_norm_stderr\": 0.020377660970371372\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2111111111111111,\n \"acc_stderr\": 0.024882116857655075,\n \ \ \"acc_norm\": 0.2111111111111111,\n \"acc_norm_stderr\": 0.024882116857655075\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.21008403361344538,\n \"acc_stderr\": 0.026461398717471874,\n\ \ \"acc_norm\": 0.21008403361344538,\n \"acc_norm_stderr\": 0.026461398717471874\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.1986754966887417,\n \"acc_stderr\": 0.03257847384436776,\n \"\ acc_norm\": 0.1986754966887417,\n \"acc_norm_stderr\": 0.03257847384436776\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.1926605504587156,\n \"acc_stderr\": 0.016909276884936094,\n \"\ acc_norm\": 0.1926605504587156,\n \"acc_norm_stderr\": 0.016909276884936094\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.1527777777777778,\n \"acc_stderr\": 0.024536326026134224,\n \"\ acc_norm\": 0.1527777777777778,\n \"acc_norm_stderr\": 0.024536326026134224\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.31390134529147984,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.31390134529147984,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.2595419847328244,\n \"acc_stderr\": 0.03844876139785271,\n\ \ \"acc_norm\": 0.2595419847328244,\n \"acc_norm_stderr\": 0.03844876139785271\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25925925925925924,\n\ \ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.25925925925925924,\n\ \ \"acc_norm_stderr\": 0.042365112580946336\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.032591773927421776,\n\ \ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.17475728155339806,\n \"acc_stderr\": 0.037601780060266224,\n\ \ \"acc_norm\": 0.17475728155339806,\n \"acc_norm_stderr\": 0.037601780060266224\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2905982905982906,\n\ \ \"acc_stderr\": 0.02974504857267404,\n \"acc_norm\": 0.2905982905982906,\n\ \ \"acc_norm_stderr\": 0.02974504857267404\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.23754789272030652,\n\ \ \"acc_stderr\": 0.015218733046150193,\n \"acc_norm\": 0.23754789272030652,\n\ \ \"acc_norm_stderr\": 0.015218733046150193\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.24855491329479767,\n \"acc_stderr\": 0.023267528432100174,\n\ \ \"acc_norm\": 0.24855491329479767,\n \"acc_norm_stderr\": 0.023267528432100174\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.023929155517351284,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.023929155517351284\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.1864951768488746,\n\ \ \"acc_stderr\": 0.02212243977248077,\n \"acc_norm\": 0.1864951768488746,\n\ \ \"acc_norm_stderr\": 0.02212243977248077\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.21604938271604937,\n \"acc_stderr\": 0.022899162918445806,\n\ \ \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.022899162918445806\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.23404255319148937,\n \"acc_stderr\": 0.025257861359432417,\n \ \ \"acc_norm\": 0.23404255319148937,\n \"acc_norm_stderr\": 0.025257861359432417\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2457627118644068,\n\ \ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\ \ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.25,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness|hendrycksTest-public_relations|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03955932861795833,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03955932861795833\n\ \ },\n \"harness|hendrycksTest-security_studies|5\": {\n \"acc\": 0.18775510204081633,\n\ \ \"acc_stderr\": 0.02500025603954621,\n \"acc_norm\": 0.18775510204081633,\n\ \ \"acc_norm_stderr\": 0.02500025603954621\n },\n \"harness|hendrycksTest-sociology|5\"\ : {\n \"acc\": 0.24378109452736318,\n \"acc_stderr\": 0.03036049015401465,\n\ \ \"acc_norm\": 0.24378109452736318,\n \"acc_norm_stderr\": 0.03036049015401465\n\ \ },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness|hendrycksTest-virology|5\"\ : {\n \"acc\": 0.28313253012048195,\n \"acc_stderr\": 0.03507295431370518,\n\ \ \"acc_norm\": 0.28313253012048195,\n \"acc_norm_stderr\": 0.03507295431370518\n\ \ },\n \"harness|hendrycksTest-world_religions|5\": {\n \"acc\": 0.3216374269005848,\n\ \ \"acc_stderr\": 0.03582529442573122,\n \"acc_norm\": 0.3216374269005848,\n\ \ \"acc_norm_stderr\": 0.03582529442573122\n },\n \"harness|truthfulqa:mc|0\"\ : {\n \"mc1\": 0.23011015911872704,\n \"mc1_stderr\": 0.014734557959807763,\n\ \ \"mc2\": 0.48987576662324334,\n \"mc2_stderr\": 0.016135847085052512\n\ \ },\n \"harness|winogrande|5\": {\n \"acc\": 0.5193370165745856,\n\ \ \"acc_stderr\": 0.01404197273371297\n },\n \"harness|gsm8k|5\": {\n\ \ \"acc\": 0.0,\n \"acc_stderr\": 0.0\n }\n}\n```" repo_url: https://huggingface.co/saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|arc:challenge|25_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-28T18-15-46.929459.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|gsm8k|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hellaswag|10_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-28T18-15-46.929459.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-management|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T18-15-46.929459.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|truthfulqa:mc|0_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-28T18-15-46.929459.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_28T18_15_46.929459 path: - '**/details_harness|winogrande|5_2024-01-28T18-15-46.929459.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-28T18-15-46.929459.parquet' - config_name: results data_files: - split: 2024_01_28T18_15_46.929459 path: - results_2024-01-28T18-15-46.929459.parquet - split: latest path: - results_2024-01-28T18-15-46.929459.parquet --- # Dataset Card for Evaluation run of saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache  Dataset automatically created during the evaluation run of model [saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache](https://huggingface.co/saarvajanik/facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-28T18:15:46.929459](https://huggingface.co/datasets/open-llm-leaderboard/details_saarvajanik__facebook-opt-6.7b-gqa-ub-16-best-for-KV-cache/blob/main/results_2024-01-28T18-15-46.929459.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.23209302149061675, "acc_stderr": 0.02992707807148158, "acc_norm": 0.23163380863022787, "acc_norm_stderr": 0.03071316471647595, "mc1": 0.23011015911872704, "mc1_stderr": 0.014734557959807763, "mc2": 0.48987576662324334, "mc2_stderr": 0.016135847085052512 }, "harness|arc:challenge|25": { "acc": 0.2022184300341297, "acc_stderr": 0.011737454431872104, "acc_norm": 0.23037542662116042, "acc_norm_stderr": 0.01230492841874761 }, "harness|hellaswag|10": { "acc": 0.25951005775741887, "acc_stderr": 0.004374699189284863, "acc_norm": 0.25941047600079664, "acc_norm_stderr": 0.004374153847826759 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.18518518518518517, "acc_stderr": 0.03355677216313142, "acc_norm": 0.18518518518518517, "acc_norm_stderr": 0.03355677216313142 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.17763157894736842, "acc_stderr": 0.031103182383123398, "acc_norm": 0.17763157894736842, "acc_norm_stderr": 0.031103182383123398 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.21509433962264152, "acc_stderr": 0.02528839450289137, "acc_norm": 0.21509433962264152, "acc_norm_stderr": 0.02528839450289137 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.2, "acc_stderr": 0.04020151261036845, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036845 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749874, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749874 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237654, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237654 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.26382978723404255, "acc_stderr": 0.028809989854102973, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.028809989854102973 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813365, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813365 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.2413793103448276, "acc_stderr": 0.03565998174135302, "acc_norm": 0.2413793103448276, "acc_norm_stderr": 0.03565998174135302 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.20899470899470898, "acc_stderr": 0.02094048156533486, "acc_norm": 0.20899470899470898, "acc_norm_stderr": 0.02094048156533486 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2857142857142857, "acc_stderr": 0.04040610178208841, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.04040610178208841 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.18, "acc_stderr": 0.038612291966536934, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536934 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.1774193548387097, "acc_stderr": 0.02173254068932927, "acc_norm": 0.1774193548387097, "acc_norm_stderr": 0.02173254068932927 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.15270935960591134, "acc_stderr": 0.02530890453938063, "acc_norm": 0.15270935960591134, "acc_norm_stderr": 0.02530890453938063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.17676767676767677, "acc_stderr": 0.027178752639044915, "acc_norm": 0.17676767676767677, "acc_norm_stderr": 0.027178752639044915 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.19689119170984457, "acc_stderr": 0.028697873971860664, "acc_norm": 0.19689119170984457, "acc_norm_stderr": 0.028697873971860664 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.20256410256410257, "acc_stderr": 0.020377660970371372, "acc_norm": 0.20256410256410257, "acc_norm_stderr": 0.020377660970371372 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2111111111111111, "acc_stderr": 0.024882116857655075, "acc_norm": 0.2111111111111111, "acc_norm_stderr": 0.024882116857655075 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.21008403361344538, "acc_stderr": 0.026461398717471874, "acc_norm": 0.21008403361344538, "acc_norm_stderr": 0.026461398717471874 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.1986754966887417, "acc_stderr": 0.03257847384436776, "acc_norm": 0.1986754966887417, "acc_norm_stderr": 0.03257847384436776 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.1926605504587156, "acc_stderr": 0.016909276884936094, "acc_norm": 0.1926605504587156, "acc_norm_stderr": 0.016909276884936094 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.1527777777777778, "acc_stderr": 0.024536326026134224, "acc_norm": 0.1527777777777778, "acc_norm_stderr": 0.024536326026134224 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.31390134529147984, "acc_stderr": 0.031146796482972465, "acc_norm": 0.31390134529147984, "acc_norm_stderr": 0.031146796482972465 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.2595419847328244, "acc_stderr": 0.03844876139785271, "acc_norm": 0.2595419847328244, "acc_norm_stderr": 0.03844876139785271 }, "harness|hendrycksTest-international_law|5": { "acc": 0.2396694214876033, "acc_stderr": 0.03896878985070417, "acc_norm": 0.2396694214876033, "acc_norm_stderr": 0.03896878985070417 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.25925925925925924, "acc_stderr": 0.042365112580946336, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.042365112580946336 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.22085889570552147, "acc_stderr": 0.032591773927421776, "acc_norm": 0.22085889570552147, "acc_norm_stderr": 0.032591773927421776 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness|hendrycksTest-management|5": { "acc": 0.17475728155339806, "acc_stderr": 0.037601780060266224, "acc_norm": 0.17475728155339806, "acc_norm_stderr": 0.037601780060266224 }, "harness|hendrycksTest-marketing|5": { "acc": 0.2905982905982906, "acc_stderr": 0.02974504857267404, "acc_norm": 0.2905982905982906, "acc_norm_stderr": 0.02974504857267404 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.23754789272030652, "acc_stderr": 0.015218733046150193, "acc_norm": 0.23754789272030652, "acc_norm_stderr": 0.015218733046150193 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.24855491329479767, "acc_stderr": 0.023267528432100174, "acc_norm": 0.24855491329479767, "acc_norm_stderr": 0.023267528432100174 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.22549019607843138, "acc_stderr": 0.023929155517351284, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.023929155517351284 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.1864951768488746, "acc_stderr": 0.02212243977248077, "acc_norm": 0.1864951768488746, "acc_norm_stderr": 0.02212243977248077 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.21604938271604937, "acc_stderr": 0.022899162918445806, "acc_norm": 0.21604938271604937, "acc_norm_stderr": 0.022899162918445806 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.23404255319148937, "acc_stderr": 0.025257861359432417, "acc_norm": 0.23404255319148937, "acc_norm_stderr": 0.025257861359432417 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.2457627118644068, "acc_stderr": 0.010996156635142692, "acc_norm": 0.2457627118644068, "acc_norm_stderr": 0.010996156635142692 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.25, "acc_stderr": 0.01751781884501444, "acc_norm": 0.25, "acc_norm_stderr": 0.01751781884501444 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03955932861795833, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03955932861795833 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.18775510204081633, "acc_stderr": 0.02500025603954621, "acc_norm": 0.18775510204081633, "acc_norm_stderr": 0.02500025603954621 }, "harness|hendrycksTest-sociology|5": { "acc": 0.24378109452736318, "acc_stderr": 0.03036049015401465, "acc_norm": 0.24378109452736318, "acc_norm_stderr": 0.03036049015401465 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-virology|5": { "acc": 0.28313253012048195, "acc_stderr": 0.03507295431370518, "acc_norm": 0.28313253012048195, "acc_norm_stderr": 0.03507295431370518 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.3216374269005848, "acc_stderr": 0.03582529442573122, "acc_norm": 0.3216374269005848, "acc_norm_stderr": 0.03582529442573122 }, "harness|truthfulqa:mc|0": { "mc1": 0.23011015911872704, "mc1_stderr": 0.014734557959807763, "mc2": 0.48987576662324334, "mc2_stderr": 0.016135847085052512 }, "harness|winogrande|5": { "acc": 0.5193370165745856, "acc_stderr": 0.01404197273371297 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More 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[More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3

--- pretty_name: Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v3 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [oh-yeontaek/llama-2-70B-LoRA-assemble-v3](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-15T17:36:30.757691](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3/blob/main/results_2023-09-15T17-36-30.757691.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6985803552112708,\n\ \ \"acc_stderr\": 0.03118492094070661,\n \"acc_norm\": 0.7024274155828159,\n\ \ \"acc_norm_stderr\": 0.031154550420018332,\n \"mc1\": 0.47980416156670747,\n\ \ \"mc1_stderr\": 0.01748921684973705,\n \"mc2\": 0.658093697491632,\n\ \ \"mc2_stderr\": 0.014747866760131165\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6860068259385665,\n \"acc_stderr\": 0.013562691224726291,\n\ \ \"acc_norm\": 0.7209897610921502,\n \"acc_norm_stderr\": 0.013106784883601334\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6820354511053575,\n\ \ \"acc_stderr\": 0.004647338877642188,\n \"acc_norm\": 0.8740290778729337,\n\ \ \"acc_norm_stderr\": 0.0033113844981586464\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.041539484047424,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.041539484047424\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7828947368421053,\n \"acc_stderr\": 0.03355045304882924,\n\ \ \"acc_norm\": 0.7828947368421053,\n \"acc_norm_stderr\": 0.03355045304882924\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.76,\n\ \ \"acc_stderr\": 0.04292346959909284,\n \"acc_norm\": 0.76,\n \ \ \"acc_norm_stderr\": 0.04292346959909284\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7547169811320755,\n \"acc_stderr\": 0.026480357179895695,\n\ \ \"acc_norm\": 0.7547169811320755,\n \"acc_norm_stderr\": 0.026480357179895695\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8194444444444444,\n\ \ \"acc_stderr\": 0.03216600808802267,\n \"acc_norm\": 0.8194444444444444,\n\ \ \"acc_norm_stderr\": 0.03216600808802267\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.62,\n \"acc_stderr\": 0.04878317312145632,\n \"acc_norm\"\ : 0.62,\n \"acc_norm_stderr\": 0.04878317312145632\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6647398843930635,\n\ \ \"acc_stderr\": 0.03599586301247077,\n \"acc_norm\": 0.6647398843930635,\n\ \ \"acc_norm_stderr\": 0.03599586301247077\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383888,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383888\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768078,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768078\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.676595744680851,\n \"acc_stderr\": 0.03057944277361034,\n\ \ \"acc_norm\": 0.676595744680851,\n \"acc_norm_stderr\": 0.03057944277361034\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4649122807017544,\n\ \ \"acc_stderr\": 0.04692008381368909,\n \"acc_norm\": 0.4649122807017544,\n\ \ \"acc_norm_stderr\": 0.04692008381368909\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6413793103448275,\n \"acc_stderr\": 0.03996629574876719,\n\ \ \"acc_norm\": 0.6413793103448275,\n \"acc_norm_stderr\": 0.03996629574876719\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.47354497354497355,\n \"acc_stderr\": 0.025715239811346758,\n \"\ acc_norm\": 0.47354497354497355,\n \"acc_norm_stderr\": 0.025715239811346758\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.49206349206349204,\n\ \ \"acc_stderr\": 0.044715725362943486,\n \"acc_norm\": 0.49206349206349204,\n\ \ \"acc_norm_stderr\": 0.044715725362943486\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8193548387096774,\n\ \ \"acc_stderr\": 0.02188617856717253,\n \"acc_norm\": 0.8193548387096774,\n\ \ \"acc_norm_stderr\": 0.02188617856717253\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.541871921182266,\n \"acc_stderr\": 0.03505630140785741,\n\ \ \"acc_norm\": 0.541871921182266,\n \"acc_norm_stderr\": 0.03505630140785741\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\"\ : 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8484848484848485,\n \"acc_stderr\": 0.027998073798781675,\n\ \ \"acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.027998073798781675\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8888888888888888,\n \"acc_stderr\": 0.022390787638216763,\n \"\ acc_norm\": 0.8888888888888888,\n \"acc_norm_stderr\": 0.022390787638216763\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.927461139896373,\n \"acc_stderr\": 0.018718998520678178,\n\ \ \"acc_norm\": 0.927461139896373,\n \"acc_norm_stderr\": 0.018718998520678178\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6974358974358974,\n \"acc_stderr\": 0.02329088805377272,\n \ \ \"acc_norm\": 0.6974358974358974,\n \"acc_norm_stderr\": 0.02329088805377272\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.32592592592592595,\n \"acc_stderr\": 0.028578348365473072,\n \ \ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.028578348365473072\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.773109243697479,\n \"acc_stderr\": 0.02720537153827947,\n \ \ \"acc_norm\": 0.773109243697479,\n \"acc_norm_stderr\": 0.02720537153827947\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.4966887417218543,\n \"acc_stderr\": 0.04082393379449654,\n \"\ acc_norm\": 0.4966887417218543,\n \"acc_norm_stderr\": 0.04082393379449654\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8954128440366973,\n \"acc_stderr\": 0.013120530245265586,\n \"\ acc_norm\": 0.8954128440366973,\n \"acc_norm_stderr\": 0.013120530245265586\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5833333333333334,\n \"acc_stderr\": 0.03362277436608043,\n \"\ acc_norm\": 0.5833333333333334,\n \"acc_norm_stderr\": 0.03362277436608043\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.9019607843137255,\n \"acc_stderr\": 0.020871118455552097,\n \"\ acc_norm\": 0.9019607843137255,\n \"acc_norm_stderr\": 0.020871118455552097\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.890295358649789,\n \"acc_stderr\": 0.020343400734868837,\n \ \ \"acc_norm\": 0.890295358649789,\n \"acc_norm_stderr\": 0.020343400734868837\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7623318385650224,\n\ \ \"acc_stderr\": 0.028568079464714274,\n \"acc_norm\": 0.7623318385650224,\n\ \ \"acc_norm_stderr\": 0.028568079464714274\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8396946564885496,\n \"acc_stderr\": 0.03217829420744632,\n\ \ \"acc_norm\": 0.8396946564885496,\n \"acc_norm_stderr\": 0.03217829420744632\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8512396694214877,\n \"acc_stderr\": 0.03248470083807194,\n \"\ acc_norm\": 0.8512396694214877,\n \"acc_norm_stderr\": 0.03248470083807194\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.8282208588957055,\n \"acc_stderr\": 0.02963471727237104,\n\ \ \"acc_norm\": 0.8282208588957055,\n \"acc_norm_stderr\": 0.02963471727237104\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.48214285714285715,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.48214285714285715,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8349514563106796,\n \"acc_stderr\": 0.03675668832233188,\n\ \ \"acc_norm\": 0.8349514563106796,\n \"acc_norm_stderr\": 0.03675668832233188\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8974358974358975,\n\ \ \"acc_stderr\": 0.01987565502786745,\n \"acc_norm\": 0.8974358974358975,\n\ \ \"acc_norm_stderr\": 0.01987565502786745\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.859514687100894,\n\ \ \"acc_stderr\": 0.012426211353093448,\n \"acc_norm\": 0.859514687100894,\n\ \ \"acc_norm_stderr\": 0.012426211353093448\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7658959537572254,\n \"acc_stderr\": 0.022797110278071128,\n\ \ \"acc_norm\": 0.7658959537572254,\n \"acc_norm_stderr\": 0.022797110278071128\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.582122905027933,\n\ \ \"acc_stderr\": 0.016495400635820084,\n \"acc_norm\": 0.582122905027933,\n\ \ \"acc_norm_stderr\": 0.016495400635820084\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7483660130718954,\n \"acc_stderr\": 0.024848018263875195,\n\ \ \"acc_norm\": 0.7483660130718954,\n \"acc_norm_stderr\": 0.024848018263875195\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7427652733118971,\n\ \ \"acc_stderr\": 0.024826171289250888,\n \"acc_norm\": 0.7427652733118971,\n\ \ \"acc_norm_stderr\": 0.024826171289250888\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.8117283950617284,\n \"acc_stderr\": 0.021751866060815882,\n\ \ \"acc_norm\": 0.8117283950617284,\n \"acc_norm_stderr\": 0.021751866060815882\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.574468085106383,\n \"acc_stderr\": 0.02949482760014436,\n \ \ \"acc_norm\": 0.574468085106383,\n \"acc_norm_stderr\": 0.02949482760014436\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5788787483702738,\n\ \ \"acc_stderr\": 0.012610325733489905,\n \"acc_norm\": 0.5788787483702738,\n\ \ \"acc_norm_stderr\": 0.012610325733489905\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7242647058823529,\n \"acc_stderr\": 0.027146271936625162,\n\ \ \"acc_norm\": 0.7242647058823529,\n \"acc_norm_stderr\": 0.027146271936625162\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.7565359477124183,\n \"acc_stderr\": 0.017362473762146613,\n \ \ \"acc_norm\": 0.7565359477124183,\n \"acc_norm_stderr\": 0.017362473762146613\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7454545454545455,\n\ \ \"acc_stderr\": 0.04172343038705383,\n \"acc_norm\": 0.7454545454545455,\n\ \ \"acc_norm_stderr\": 0.04172343038705383\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7959183673469388,\n \"acc_stderr\": 0.025801283475090496,\n\ \ \"acc_norm\": 0.7959183673469388,\n \"acc_norm_stderr\": 0.025801283475090496\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8905472636815921,\n\ \ \"acc_stderr\": 0.02207632610182466,\n \"acc_norm\": 0.8905472636815921,\n\ \ \"acc_norm_stderr\": 0.02207632610182466\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.033799766898963086,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.033799766898963086\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8596491228070176,\n \"acc_stderr\": 0.0266405825391332,\n\ \ \"acc_norm\": 0.8596491228070176,\n \"acc_norm_stderr\": 0.0266405825391332\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.47980416156670747,\n\ \ \"mc1_stderr\": 0.01748921684973705,\n \"mc2\": 0.658093697491632,\n\ \ \"mc2_stderr\": 0.014747866760131165\n }\n}\n```" repo_url: https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|arc:challenge|25_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hellaswag|10_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T17-36-30.757691.parquet' - config_name: results data_files: - split: 2023_09_15T17_36_30.757691 path: - results_2023-09-15T17-36-30.757691.parquet - split: latest path: - results_2023-09-15T17-36-30.757691.parquet --- # Dataset Card for Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v3 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3 - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [oh-yeontaek/llama-2-70B-LoRA-assemble-v3](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-15T17:36:30.757691](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3/blob/main/results_2023-09-15T17-36-30.757691.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6985803552112708, "acc_stderr": 0.03118492094070661, "acc_norm": 0.7024274155828159, "acc_norm_stderr": 0.031154550420018332, "mc1": 0.47980416156670747, "mc1_stderr": 0.01748921684973705, "mc2": 0.658093697491632, "mc2_stderr": 0.014747866760131165 }, "harness|arc:challenge|25": { "acc": 0.6860068259385665, "acc_stderr": 0.013562691224726291, "acc_norm": 0.7209897610921502, "acc_norm_stderr": 0.013106784883601334 }, "harness|hellaswag|10": { "acc": 0.6820354511053575, "acc_stderr": 0.004647338877642188, "acc_norm": 0.8740290778729337, "acc_norm_stderr": 0.0033113844981586464 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6370370370370371, "acc_stderr": 0.041539484047424, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.041539484047424 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7828947368421053, "acc_stderr": 0.03355045304882924, "acc_norm": 0.7828947368421053, "acc_norm_stderr": 0.03355045304882924 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.76, "acc_stderr": 0.04292346959909284, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7547169811320755, "acc_stderr": 0.026480357179895695, "acc_norm": 0.7547169811320755, "acc_norm_stderr": 0.026480357179895695 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8194444444444444, "acc_stderr": 0.03216600808802267, "acc_norm": 0.8194444444444444, "acc_norm_stderr": 0.03216600808802267 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6647398843930635, "acc_stderr": 0.03599586301247077, "acc_norm": 0.6647398843930635, "acc_norm_stderr": 0.03599586301247077 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383888, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383888 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768078, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.676595744680851, "acc_stderr": 0.03057944277361034, "acc_norm": 0.676595744680851, "acc_norm_stderr": 0.03057944277361034 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4649122807017544, "acc_stderr": 0.04692008381368909, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.04692008381368909 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6413793103448275, "acc_stderr": 0.03996629574876719, "acc_norm": 0.6413793103448275, "acc_norm_stderr": 0.03996629574876719 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.47354497354497355, "acc_stderr": 0.025715239811346758, "acc_norm": 0.47354497354497355, "acc_norm_stderr": 0.025715239811346758 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.49206349206349204, "acc_stderr": 0.044715725362943486, "acc_norm": 0.49206349206349204, "acc_norm_stderr": 0.044715725362943486 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8193548387096774, "acc_stderr": 0.02188617856717253, "acc_norm": 0.8193548387096774, "acc_norm_stderr": 0.02188617856717253 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.541871921182266, "acc_stderr": 0.03505630140785741, "acc_norm": 0.541871921182266, "acc_norm_stderr": 0.03505630140785741 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8484848484848485, "acc_stderr": 0.027998073798781675, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.027998073798781675 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8888888888888888, "acc_stderr": 0.022390787638216763, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.022390787638216763 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.927461139896373, "acc_stderr": 0.018718998520678178, "acc_norm": 0.927461139896373, "acc_norm_stderr": 0.018718998520678178 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6974358974358974, "acc_stderr": 0.02329088805377272, "acc_norm": 0.6974358974358974, "acc_norm_stderr": 0.02329088805377272 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32592592592592595, "acc_stderr": 0.028578348365473072, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.028578348365473072 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.773109243697479, "acc_stderr": 0.02720537153827947, "acc_norm": 0.773109243697479, "acc_norm_stderr": 0.02720537153827947 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.4966887417218543, "acc_stderr": 0.04082393379449654, "acc_norm": 0.4966887417218543, "acc_norm_stderr": 0.04082393379449654 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8954128440366973, "acc_stderr": 0.013120530245265586, "acc_norm": 0.8954128440366973, "acc_norm_stderr": 0.013120530245265586 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5833333333333334, "acc_stderr": 0.03362277436608043, "acc_norm": 0.5833333333333334, "acc_norm_stderr": 0.03362277436608043 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.9019607843137255, "acc_stderr": 0.020871118455552097, "acc_norm": 0.9019607843137255, "acc_norm_stderr": 0.020871118455552097 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.890295358649789, "acc_stderr": 0.020343400734868837, "acc_norm": 0.890295358649789, "acc_norm_stderr": 0.020343400734868837 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7623318385650224, "acc_stderr": 0.028568079464714274, "acc_norm": 0.7623318385650224, "acc_norm_stderr": 0.028568079464714274 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8396946564885496, "acc_stderr": 0.03217829420744632, "acc_norm": 0.8396946564885496, "acc_norm_stderr": 0.03217829420744632 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8512396694214877, "acc_stderr": 0.03248470083807194, "acc_norm": 0.8512396694214877, "acc_norm_stderr": 0.03248470083807194 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8333333333333334, "acc_stderr": 0.03602814176392645, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.03602814176392645 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.8282208588957055, "acc_stderr": 0.02963471727237104, "acc_norm": 0.8282208588957055, "acc_norm_stderr": 0.02963471727237104 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.48214285714285715, "acc_stderr": 0.047427623612430116, "acc_norm": 0.48214285714285715, "acc_norm_stderr": 0.047427623612430116 }, "harness|hendrycksTest-management|5": { "acc": 0.8349514563106796, "acc_stderr": 0.03675668832233188, "acc_norm": 0.8349514563106796, "acc_norm_stderr": 0.03675668832233188 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8974358974358975, "acc_stderr": 0.01987565502786745, "acc_norm": 0.8974358974358975, "acc_norm_stderr": 0.01987565502786745 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.859514687100894, "acc_stderr": 0.012426211353093448, "acc_norm": 0.859514687100894, "acc_norm_stderr": 0.012426211353093448 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7658959537572254, "acc_stderr": 0.022797110278071128, "acc_norm": 0.7658959537572254, "acc_norm_stderr": 0.022797110278071128 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.582122905027933, "acc_stderr": 0.016495400635820084, "acc_norm": 0.582122905027933, "acc_norm_stderr": 0.016495400635820084 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7483660130718954, "acc_stderr": 0.024848018263875195, "acc_norm": 0.7483660130718954, "acc_norm_stderr": 0.024848018263875195 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7427652733118971, "acc_stderr": 0.024826171289250888, "acc_norm": 0.7427652733118971, "acc_norm_stderr": 0.024826171289250888 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.8117283950617284, "acc_stderr": 0.021751866060815882, "acc_norm": 0.8117283950617284, "acc_norm_stderr": 0.021751866060815882 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.574468085106383, "acc_stderr": 0.02949482760014436, "acc_norm": 0.574468085106383, "acc_norm_stderr": 0.02949482760014436 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.5788787483702738, "acc_stderr": 0.012610325733489905, "acc_norm": 0.5788787483702738, "acc_norm_stderr": 0.012610325733489905 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7242647058823529, "acc_stderr": 0.027146271936625162, "acc_norm": 0.7242647058823529, "acc_norm_stderr": 0.027146271936625162 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.7565359477124183, "acc_stderr": 0.017362473762146613, "acc_norm": 0.7565359477124183, "acc_norm_stderr": 0.017362473762146613 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7454545454545455, "acc_stderr": 0.04172343038705383, "acc_norm": 0.7454545454545455, "acc_norm_stderr": 0.04172343038705383 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7959183673469388, "acc_stderr": 0.025801283475090496, "acc_norm": 0.7959183673469388, "acc_norm_stderr": 0.025801283475090496 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8905472636815921, "acc_stderr": 0.02207632610182466, "acc_norm": 0.8905472636815921, "acc_norm_stderr": 0.02207632610182466 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.87, "acc_stderr": 0.033799766898963086, "acc_norm": 0.87, "acc_norm_stderr": 0.033799766898963086 }, "harness|hendrycksTest-virology|5": { "acc": 0.5120481927710844, "acc_stderr": 0.03891364495835817, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.03891364495835817 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8596491228070176, "acc_stderr": 0.0266405825391332, "acc_norm": 0.8596491228070176, "acc_norm_stderr": 0.0266405825391332 }, "harness|truthfulqa:mc|0": { "mc1": 0.47980416156670747, "mc1_stderr": 0.01748921684973705, "mc2": 0.658093697491632, "mc2_stderr": 0.014747866760131165 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]

AdapterOcean/med_alpaca_standardized_cluster_33_std

--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 15881902 num_examples: 31912 download_size: 7840649 dataset_size: 15881902 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_33_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

siddharthjadhav6565/vedas

--- license: openrail ---

ASR-HypR/AISHELL1_withoutLM

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: dev path: data/dev-* dataset_info: features: - name: ref dtype: string - name: hyps sequence: string - name: ctc_score sequence: float64 - name: att_score sequence: float64 - name: utt_id dtype: string - name: score sequence: float64 splits: - name: train num_bytes: 520539152 num_examples: 120098 - name: test num_bytes: 31358088 num_examples: 7176 - name: dev num_bytes: 61833418 num_examples: 14326 download_size: 283530745 dataset_size: 613730658 --- # Dataset Card for "AISHELL1_withoutLM" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

316usman/thematic5e-pw-embed-part5

--- dataset_info: features: - name: text dtype: string - name: document_url dtype: string - name: source_url dtype: string - name: country dtype: string splits: - name: train num_bytes: 269487465 num_examples: 405601 download_size: 105797465 dataset_size: 269487465 configs: - config_name: default data_files: - split: train path: data/train-* ---

joey234/mmlu-high_school_microeconomics

--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string - name: neg_question dtype: string - name: fewshot_context dtype: string - name: fewshot_context_neg dtype: string splits: - name: dev num_bytes: 4194 num_examples: 5 - name: test num_bytes: 839869 num_examples: 238 download_size: 104401 dataset_size: 844063 configs: - config_name: default data_files: - split: dev path: data/dev-* - split: test path: data/test-* --- # Dataset Card for "mmlu-high_school_microeconomics" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

convaiinnovations/llama2-new

--- license: mit ---

Jingkang/PVSG

--- license: mit --- We carefully collect 400 videos, each featuring dynamic scenes and rich in logical reasoning content. On average, these videos are 76.5 seconds long (5 FPS). The collection comprises 289 videos from VidOR, 55 videos from EpicKitchen, and 56 videos from Ego4D. Please `git clone` https://github.com/LilyDaytoy/OpenPVSG and organize your files according to the structure below. You can put the HF dataset in `data_zip` directory. ``` ├── assets ├── checkpoints ├── configs ├── data ├── data_zip │ ├── Ego4D │ │ ├── ego4d_masks.zip │ │ └── ego4d_videos.zip │ ├── EpicKitchen │ │ ├── epic_kitchen_masks.zip │ │ └── epic_kitchen_videos.zip │ ├── VidOR │ │ ├── vidor_masks.zip │ │ └── vidor_videos.zip │ └── pvsg.json ├── datasets ├── models ├── scripts ├── tools ├── utils ├── .gitignore ├── environment.yml └── README.md ``` Please run unzip_and_extract.py to unzip the files and extract frames from the videos. If you use zip, make sure to use `unzip -j xxx.zip` to remove junk paths. You should have your data directory looks like this: ``` data ├── ego4d │ ├── frames │ ├── masks │ └── videos ├── epic_kitchen │ ├── frames │ ├── masks │ └── videos ├── vidor │ ├── frames │ ├── masks │ └── videos └── pvsg.json ``` We suggest our users to play with `./notebooks/Visualize_Dataset.ipynb` to quickly get familiar with PVSG dataset. ## Citation For more information about the methods used in this dataset, please refer to the following paper: [Panoptic Video Scene Graph Generation](https://arxiv.org/abs/2310.15166), arXiv:2310.15166.

edbeeching/prj_gia_dataset_atari_2B_atari_zaxxon_1111

--- library_name: gia tags: - deep-reinforcement-learning - reinforcement-learning - gia - multi-task - multi-modal - imitation-learning - offline-reinforcement-learning --- An imitation learning environment for the atari_zaxxon environment, sample for the policy atari_2B_atari_zaxxon_1111 This environment was created as part of the Generally Intelligent Agents project gia: https://github.com/huggingface/gia

LIKirin/klonetai-prompts

--- license: mit ---

zakcroft/test_lamini_docs

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 4054.5 num_examples: 5 - name: test num_bytes: 4054.5 num_examples: 5 download_size: 12911 dataset_size: 8109.0 --- # Dataset Card for "test_lamini_docs" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ahmadSiddiqi/t5-qrels

--- dataset_info: features: - name: qid dtype: string - name: pid dtype: string - name: score dtype: int64 splits: - name: dev num_bytes: 24384 num_examples: 1061 download_size: 7749 dataset_size: 24384 configs: - config_name: default data_files: - split: dev path: data/dev-* ---

mtkinit/mtkinit_test_xyz_aaa

--- pretty_name: mtkinit/test_xyz_aaa --- # mtkinit/test_xyz_aaa Created from AIOD platform

muhammadravi251001/squadid-nli

--- annotations_creators: - machine-generated - manual-partial-validation language_creators: - expert-generated language: - id license: unknown multilinguality: - monolingual size_categories: - 100K<n<1M source_datasets: - SQuAD-ID task_categories: - text-classification task_ids: - natural-language-inference pretty_name: SQuAD-ID-NLI dataset_info: features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: '0': entailment '1': neutral '2': contradiction config_name: squadid-nli splits: - name: train num_bytes: 103934750 num_examples: 236891 - name: validation num_bytes: 10831375 num_examples: 23749 - name: test num_bytes: 10969750 num_examples: 23747 download_size: 125735875 dataset_size: 284387 --- # Dataset Card for SQuAD-ID-NLI ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Repository:** [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/squadid-nli) - **Point of Contact:** [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/squadid-nli) - **Experiment:** [Github](https://github.com/muhammadravi251001/multilingual-qas-with-nli) ### Dataset Summary The SQuAD-ID-NLI dataset is derived from the SQuAD-ID question answering dataset, utilizing named entity recognition (NER), chunking tags, Regex, and embedding similarity techniques to determine its contradiction sets. Collected through this process, the dataset comprises various columns beyond premise, hypothesis, and label, including properties aligned with NER and chunking tags. This dataset is designed to facilitate Natural Language Inference (NLI) tasks and contains information extracted from diverse sources to provide comprehensive coverage. Each data instance encapsulates premise, hypothesis, label, and additional properties pertinent to NLI evaluation. ### Supported Tasks and Leaderboards - Natural Language Inference for Indonesian ### Languages Indonesian ## Dataset Structure ### Data Instances An example of `test` looks as follows. ``` { "premise": "Beberapa keluarga Yunani Bizantium berasal dari tentara bayaran Norman selama periode Restorasi Comnenian, ketika kaisar Bizantium mencari prajurit Eropa Barat. Raoulii adalah keturunan dari orang Italia-Norman bernama Raoul, Petraliphae adalah keturunan dari Pierre d'Aulps, dan kelompok klan Albania yang dikenal sebagai Maniakate diturunkan dari Normandia yang bertugas di bawah George Maniaces dalam ekspedisi Sisilia tahun 1038.", "hypothesis": "Dari mana beberapa famili tentara bayaran Norman berasal? Yunani Bizantium", "label": 0 } ``` ### Data Fields The data fields are: - `premise`: a `string` feature - `hypothesis`: a `string` feature - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). ### Data Splits #TODO The data is split across `train`, `valid`, and `test`. | split | # examples | |----------|-------:| |train| 236891| |valid| 23749| |test| 23747| ## Dataset Creation ### Curation Rationale Indonesian NLP is considered under-resourced. We need NLI dataset to fine-tuning the NLI model to utilizing them for QA models in order to improving the performance of the QA's. ### Source Data #### Initial Data Collection and Normalization We collect the data from the prominent QA dataset in Indonesian. The annotation fully by the original dataset's researcher. #### Who are the source language producers? This synthetic data was produced by machine, but the original data was produced by human. ### Personal and Sensitive Information There might be some personal information coming from Wikipedia and news, especially the information of famous/important people. ## Considerations for Using the Data ### Discussion of Biases The QA dataset (so the NLI-derived from them) is created using premise sentences taken from Wikipedia and news. These data sources may contain some bias. ### Other Known Limitations No other known limitations ## Additional Information ### Dataset Curators This dataset is the result of the collaborative work of Indonesian researchers from the University of Indonesia, Mohamed bin Zayed University of Artificial Intelligence, and the Korea Advanced Institute of Science & Technology. ### Licensing Information The license is Unknown. Please contact authors for any information on the dataset.

yuyijiong/Book_Summary_Chinese

--- license: cc-by-nc-4.0 task_categories: - text-generation language: - zh size_categories: - 1K<n<10K --- # 中文图书总结数据集每个样本包含： <font color=red> 图书的一个章节、此章节的总结、图书名字</font>，可以训练模型总结长文本的能力。\ 数据主要来自较为著名的中文版小说。

results-sd-v1-5-sd-v2-1-if-v1-0-karlo/f1e9865c

--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 180 num_examples: 10 download_size: 1340 dataset_size: 180 --- # Dataset Card for "f1e9865c" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Swati1981/ETHICS-IN-LIFE

--- license: apache-2.0 ---

rajuptvs/English-to-hindi-podcast-translation

--- dataset_info: features: - name: video_id dtype: string - name: English subtitles dtype: string - name: Hindi subtitles dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1827416 num_examples: 11427 download_size: 784942 dataset_size: 1827416 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "en-hi" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

jinwoos/cartoonizer-dataset-640

--- dataset_info: features: - name: original_image dtype: image - name: edit_prompt dtype: string - name: cartoonized_image dtype: image splits: - name: train num_bytes: 11462200198.0 num_examples: 740 download_size: 11461609579 dataset_size: 11462200198.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

404NotF0und/MtG-json-to-ForgeScript

--- license: mit ---

Aremstrom/llama2_prompt_template_for_ChrisHayduk_Llama-2-SQL-Dataset

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 991555 num_examples: 2000 download_size: 235903 dataset_size: 991555 configs: - config_name: default data_files: - split: train path: data/train-* ---

HugNetw0rk/Ucenie02_Embedding

--- license: other ---

CyberHarem/tsukimi_eiko_paripikoumei

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Tsukimi Eiko This is the dataset of Tsukimi Eiko, containing 299 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 299 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 719 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 299 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 299 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 299 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 299 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 299 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 719 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 719 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 719 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |

Nithees/complete_sherlock_holmes-book

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 3300084 num_examples: 1 download_size: 2276499 dataset_size: 3300084 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "complete_sherlock_holmes-book" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

mPLUG/M-Paper

--- license: apache-2.0 ---

AlanRobotics/saiga_tokenized

--- dataset_info: features: - name: labels sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 52968582.0 num_examples: 32688 - name: test num_bytes: 5885398.0 num_examples: 3632 download_size: 20205153 dataset_size: 58853980.0 --- # Dataset Card for "saiga_tokenized" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

quocanh34/test_result_large_data_ver2

--- dataset_info: features: - name: id dtype: string - name: pred_str dtype: string - name: test_norm dtype: string splits: - name: train num_bytes: 208107 num_examples: 1299 download_size: 108997 dataset_size: 208107 --- # Dataset Card for "test_result_large_data_ver2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

MaheshMc2/petcare_sample

--- license: other ---

Sharathhebbar24/BeaverTails_unfiltered

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 185218245 num_examples: 364170 download_size: 97617848 dataset_size: 185218245 configs: - config_name: default data_files: - split: train path: data/train-* license: apache-2.0 task_categories: - text-generation language: - en size_categories: - 10K<n<100K --- # Beaver Tails This is a cleansed version of [PKU-Alignment/BeaverTails](https://huggingface.co/datasets/PKU-Alignment/BeaverTails) It has two version based on the sensitivity ## Filtered ### Usage ```python from datasets import load_dataset dataset = load_dataset("Sharathhebbar24/BeaverTails_filtered", split="train") ``` ## Unfiltered ### Usage ```python from datasets import load_dataset dataset = load_dataset("Sharathhebbar24/BeaverTails_unfiltered", split="train") ```

stauntonjr/dtic_sent

--- dataset_info: features: - name: Accession Number dtype: string - name: Title dtype: string - name: Descriptive Note dtype: string - name: Corporate Author dtype: string - name: Personal Author(s) sequence: string - name: Report Date dtype: string - name: Pagination or Media Count dtype: string - name: Descriptors sequence: string - name: Subject Categories dtype: string - name: Distribution Statement dtype: string - name: fulltext dtype: string - name: cleantext dtype: string - name: sents sequence: string splits: - name: train num_bytes: 6951041151 num_examples: 27425 download_size: 3712549813 dataset_size: 6951041151 --- # Dataset Card for "dtic_sent" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

anan-2024/twitter_dataset_1713094859

--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 134425 num_examples: 360 download_size: 80168 dataset_size: 134425 configs: - config_name: default data_files: - split: train path: data/train-* ---

Ashmal/Preprocessed_ArabicMMLU

--- dataset_info: features: - name: Question dtype: string - name: A dtype: string - name: B dtype: string - name: C dtype: string - name: D dtype: string - name: E dtype: string - name: Answer dtype: string splits: - name: train num_bytes: 3444182 num_examples: 14575 download_size: 1533096 dataset_size: 3444182 configs: - config_name: default data_files: - split: train path: data/train-* ---

Den4ikAI/russian_dialogues_2

--- license: mit task_categories: - conversational - text-generation - text2text-generation language: - ru size_categories: - 1M<n<10M --- ### Den4ikAI/russian_dialogues_2 Датасет русских диалогов для обучения диалоговых моделей. Количество диалогов - 1.6 миллиона Формат датасета: ``` { 'sample': ['Привет', 'Привет', 'Как дела?'] } ``` ### Citation: ``` @MISC{russian_instructions, author = {Denis Petrov}, title = {Russian context dialogues dataset for conversational agents}, url = {https://huggingface.co/datasets/Den4ikAI/russian_dialogues_2}, year = 2023 } ```

Apinapi/Lucas12

--- license: openrail ---

distilled-from-one-sec-cv12/chunk_176

--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1282989736 num_examples: 249998 download_size: 1310567103 dataset_size: 1282989736 --- # Dataset Card for "chunk_176" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

arubenruben/brazilian_senate_speeches

--- dataset_info: features: - name: text dtype: string - name: label dtype: class_label: names: '0': pt-PT '1': pt-BR splits: - name: train num_bytes: 8433586.765427053 num_examples: 3915 - name: test num_bytes: 2108935.2345729466 num_examples: 979 download_size: 6066217 dataset_size: 10542522.0 --- # Dataset Card for "brazilian_senate_speeches_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

DragonLine/ksponspeech_03_preprocess

--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 95285021616 num_examples: 99200 - name: test num_bytes: 11910618728 num_examples: 12400 - name: valid num_bytes: 11910635984 num_examples: 12400 download_size: 23741227475 dataset_size: 119106276328 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* ---

anjelammcgraw/collegeessays

--- license: apache-2.0 ---

huggingartists/yung-plague

--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/yung-plague" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - **Homepage:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Repository:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of the generated dataset:** 0.109415 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/6c0f8e02f467c694379f242ea2897efd.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/yung-plague"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Yung Plague</div> <a href="https://genius.com/artists/yung-plague"> <div style="text-align: center; font-size: 14px;">@yung-plague</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/yung-plague). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/yung-plague") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits | train |validation|test| |------:|---------:|---:| |38| -| -| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/yung-plague") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About *Built by Aleksey Korshuk* [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)

tinyBenchmarks/tinyHellaswag

--- dataset_info: features: - name: ind dtype: int32 - name: activity_label dtype: string - name: ctx_a dtype: string - name: ctx_b dtype: string - name: ctx dtype: string - name: endings sequence: string - name: source_id dtype: string - name: split dtype: string - name: split_type dtype: string - name: label dtype: string - name: input_formatted dtype: string splits: - name: train num_bytes: 160899446 num_examples: 39905 - name: test num_bytes: 40288101 num_examples: 10003 - name: validation num_bytes: 473652 num_examples: 100 download_size: 50109798 dataset_size: 201661199 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* language: - en pretty_name: tinyHellaswag size_categories: - n<1K multilinguality: - monolingual source_datasets: - Rowan/hellaswag language_bcp47: - en-US --- # tinyHellaswag Welcome to tinyHellaswag! This dataset serves as a concise version of the [hellaswag](https://huggingface.co/datasets/hellaswag) dataset, offering a subset of 100 data points selected from the original compilation. tinyHellaswag is designed to enable users to efficiently estimate the performance of a large language model (LLM) with reduced dataset size, saving computational resources while maintaining the essence of the hellaswag evaluation. ## Features - **Compact Dataset:** With only 100 data points, tinyHellaswag provides a swift and efficient way to evaluate your LLM's performance against a benchmark set, maintaining the essence of the original hellaswag dataset. - **Compatibility:** tinyHellaswag is compatible with evaluation using the [lm evaluation harness](https://github.com/EleutherAI/lm-evaluation-harness/), but can also be integrated into your custom pipeline. See below for more details. ## Model Evaluation Users looking to evaluate a new model with tinyHellaswag can use the [lm evaluation harness (v0.4.1 or later)](https://github.com/EleutherAI/lm-evaluation-harness/). Simply replace `dataset_path: hellaswag` with `dataset_path: tinyBenchmarks/tinyHellaswag` in the file `lm-evaluation-harness/lm_eval/tasks/hellaswag/hellaswag.yaml` and run your evaluation harness as usual, using the `--log_samples` argument: ```shell lm_eval --model hf --model_args pretrained="<your-model>" --tasks=hellaswag --batch_size=1 --num_fewshot 10 --output_path=<output_path> --log_samples ``` Alternatively, the tinyHellaswag can be integrated into any other pipeline by downloading the data via ```python from datasets import load_dataset tiny_data = load_dataset('tinyBenchmarks/tinyHellaswag')['validation'] ``` Now, `tiny_data` contains the 100 subsampled data points with the same features as the original dataset, as well as an additional field containing the preformatted data points. The preformatted data points follow the formatting used in the [open llm leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) including the respective in-context examples. When using the lm evaluation harness, you can then estimate your LLM's performance using the following code. First, ensure you have the tinyBenchmarks package installed: ```shell pip install git+https://github.com/felipemaiapolo/tinyBenchmarks ``` Then, use the code snippet below for the evaluation: ```python import numpy as np import tinyBenchmarks as tb ### Score vector y = # your original score vector ### Parameters benchmark = 'hellaswag' ### Evaluation tb.evaluate(y, benchmark) ``` This process will help you estimate the performance of your LLM against the tinyHellaswag dataset, providing a streamlined approach to benchmarking. Please be aware that evaluating on multiple GPUs can change the order of outputs in the lm evaluation harness. Ordering your score vector following the original order in tinyHellaswag will be necessary to use the tinyBenchmarks library. For more detailed instructions on evaluating new models and computing scores, please refer to the comprehensive guides available at [lm evaluation harness](https://github.com/EleutherAI/lm-evaluation-harness/) and [tinyBenchmarks GitHub](https://github.com/felipemaiapolo/tinyBenchmarks). Happy benchmarking! ## More tinyBenchmarks **Open LLM leaderboard**: [tiny MMLU](https://huggingface.co/datasets/tinyBenchmarks/tinyMMLU), [tiny Arc-Challenge](https://huggingface.co/datasets/tinyBenchmarks/tinyAI2_arc), [tiny Winogrande](https://huggingface.co/datasets/tinyBenchmarks/tinyWinogrande), [tiny TruthfulQA](https://huggingface.co/datasets/tinyBenchmarks/tinyTruthfulQA), [tiny GSM8k](https://huggingface.co/datasets/tinyBenchmarks/tinyGSM8k) **AlpacaEval**: [tiny AlpacaEval](https://huggingface.co/datasets/tinyBenchmarks/tinyAlpacaEval) **HELM-lite**: _work-in-progress_ ## Citation @article{polo2024tinybenchmarks, title={tinyBenchmarks: evaluating LLMs with fewer examples}, author={Felipe Maia Polo and Lucas Weber and Leshem Choshen and Yuekai Sun and Gongjun Xu and Mikhail Yurochkin}, year={2024}, eprint={2402.14992}, archivePrefix={arXiv}, primaryClass={cs.CL} } @inproceedings{zellers2019hellaswag, title={HellaSwag: Can a Machine Really Finish Your Sentence?}, author={Zellers, Rowan and Holtzman, Ari and Bisk, Yonatan and Farhadi, Ali and Choi, Yejin}, booktitle ={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics}, year={2019} }

open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1

--- pretty_name: Evaluation run of HuggingFaceH4/zephyr-7b-gemma-v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [HuggingFaceH4/zephyr-7b-gemma-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-02T04:15:22.465767](https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1/blob/main/results_2024-03-02T04-15-22.465767.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6064698705754529,\n\ \ \"acc_stderr\": 0.03312365418757596,\n \"acc_norm\": 0.6103117238998753,\n\ \ \"acc_norm_stderr\": 0.03378577550936012,\n \"mc1\": 0.3525091799265606,\n\ \ \"mc1_stderr\": 0.016724646380756547,\n \"mc2\": 0.5207310735270693,\n\ \ \"mc2_stderr\": 0.01596371997542123\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5563139931740614,\n \"acc_stderr\": 0.014518421825670444,\n\ \ \"acc_norm\": 0.5844709897610921,\n \"acc_norm_stderr\": 0.014401366641216384\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6516630153355906,\n\ \ \"acc_stderr\": 0.004754697013354955,\n \"acc_norm\": 0.8347938657637921,\n\ \ \"acc_norm_stderr\": 0.003706075184380285\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932267,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932267\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5481481481481482,\n\ \ \"acc_stderr\": 0.04299268905480864,\n \"acc_norm\": 0.5481481481481482,\n\ \ \"acc_norm_stderr\": 0.04299268905480864\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7171052631578947,\n \"acc_stderr\": 0.03665349695640767,\n\ \ \"acc_norm\": 0.7171052631578947,\n \"acc_norm_stderr\": 0.03665349695640767\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.62,\n\ \ \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n \ \ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6075471698113207,\n \"acc_stderr\": 0.03005258057955784,\n\ \ \"acc_norm\": 0.6075471698113207,\n \"acc_norm_stderr\": 0.03005258057955784\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7361111111111112,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.7361111111111112,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \ \ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.51,\n\ \ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6127167630057804,\n\ \ \"acc_stderr\": 0.03714325906302065,\n \"acc_norm\": 0.6127167630057804,\n\ \ \"acc_norm_stderr\": 0.03714325906302065\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.39215686274509803,\n \"acc_stderr\": 0.048580835742663454,\n\ \ \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.048580835742663454\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108102,\n\ \ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108102\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.40350877192982454,\n\ \ \"acc_stderr\": 0.046151869625837026,\n \"acc_norm\": 0.40350877192982454,\n\ \ \"acc_norm_stderr\": 0.046151869625837026\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6275862068965518,\n \"acc_stderr\": 0.04028731532947558,\n\ \ \"acc_norm\": 0.6275862068965518,\n \"acc_norm_stderr\": 0.04028731532947558\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.4470899470899471,\n \"acc_stderr\": 0.025606723995777028,\n \"\ acc_norm\": 0.4470899470899471,\n \"acc_norm_stderr\": 0.025606723995777028\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.7451612903225806,\n \"acc_stderr\": 0.024790118459332208,\n \"\ acc_norm\": 0.7451612903225806,\n \"acc_norm_stderr\": 0.024790118459332208\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.47783251231527096,\n \"acc_stderr\": 0.035145285621750094,\n \"\ acc_norm\": 0.47783251231527096,\n \"acc_norm_stderr\": 0.035145285621750094\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\"\ : 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7151515151515152,\n \"acc_stderr\": 0.03524390844511781,\n\ \ \"acc_norm\": 0.7151515151515152,\n \"acc_norm_stderr\": 0.03524390844511781\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8131313131313131,\n \"acc_stderr\": 0.027772533334218964,\n \"\ acc_norm\": 0.8131313131313131,\n \"acc_norm_stderr\": 0.027772533334218964\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8497409326424871,\n \"acc_stderr\": 0.02578772318072388,\n\ \ \"acc_norm\": 0.8497409326424871,\n \"acc_norm_stderr\": 0.02578772318072388\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5897435897435898,\n \"acc_stderr\": 0.02493931390694079,\n \ \ \"acc_norm\": 0.5897435897435898,\n \"acc_norm_stderr\": 0.02493931390694079\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.362962962962963,\n \"acc_stderr\": 0.029318203645206868,\n \ \ \"acc_norm\": 0.362962962962963,\n \"acc_norm_stderr\": 0.029318203645206868\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6134453781512605,\n \"acc_stderr\": 0.0316314580755238,\n \ \ \"acc_norm\": 0.6134453781512605,\n \"acc_norm_stderr\": 0.0316314580755238\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.039291117812427424,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.039291117812427424\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8146788990825689,\n \"acc_stderr\": 0.016659279700295827,\n \"\ acc_norm\": 0.8146788990825689,\n \"acc_norm_stderr\": 0.016659279700295827\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7696078431372549,\n \"acc_stderr\": 0.029554292605695066,\n \"\ acc_norm\": 0.7696078431372549,\n \"acc_norm_stderr\": 0.029554292605695066\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7974683544303798,\n \"acc_stderr\": 0.026160568246601436,\n \ \ \"acc_norm\": 0.7974683544303798,\n \"acc_norm_stderr\": 0.026160568246601436\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6816143497757847,\n\ \ \"acc_stderr\": 0.03126580522513713,\n \"acc_norm\": 0.6816143497757847,\n\ \ \"acc_norm_stderr\": 0.03126580522513713\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5801526717557252,\n \"acc_stderr\": 0.043285772152629715,\n\ \ \"acc_norm\": 0.5801526717557252,\n \"acc_norm_stderr\": 0.043285772152629715\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7314814814814815,\n\ \ \"acc_stderr\": 0.042844679680521934,\n \"acc_norm\": 0.7314814814814815,\n\ \ \"acc_norm_stderr\": 0.042844679680521934\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7239263803680982,\n \"acc_stderr\": 0.035123852837050475,\n\ \ \"acc_norm\": 0.7239263803680982,\n \"acc_norm_stderr\": 0.035123852837050475\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4375,\n\ \ \"acc_stderr\": 0.04708567521880525,\n \"acc_norm\": 0.4375,\n \ \ \"acc_norm_stderr\": 0.04708567521880525\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.03989139859531771,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.03989139859531771\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8589743589743589,\n\ \ \"acc_stderr\": 0.022801382534597542,\n \"acc_norm\": 0.8589743589743589,\n\ \ \"acc_norm_stderr\": 0.022801382534597542\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7790549169859514,\n\ \ \"acc_stderr\": 0.014836205167333562,\n \"acc_norm\": 0.7790549169859514,\n\ \ \"acc_norm_stderr\": 0.014836205167333562\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6242774566473989,\n \"acc_stderr\": 0.02607431485165708,\n\ \ \"acc_norm\": 0.6242774566473989,\n \"acc_norm_stderr\": 0.02607431485165708\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.22569832402234638,\n\ \ \"acc_stderr\": 0.013981395058455066,\n \"acc_norm\": 0.22569832402234638,\n\ \ \"acc_norm_stderr\": 0.013981395058455066\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6568627450980392,\n \"acc_stderr\": 0.027184498909941616,\n\ \ \"acc_norm\": 0.6568627450980392,\n \"acc_norm_stderr\": 0.027184498909941616\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6495176848874598,\n\ \ \"acc_stderr\": 0.02709865262130175,\n \"acc_norm\": 0.6495176848874598,\n\ \ \"acc_norm_stderr\": 0.02709865262130175\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7006172839506173,\n \"acc_stderr\": 0.025483115601195448,\n\ \ \"acc_norm\": 0.7006172839506173,\n \"acc_norm_stderr\": 0.025483115601195448\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.450354609929078,\n \"acc_stderr\": 0.029680105565029036,\n \ \ \"acc_norm\": 0.450354609929078,\n \"acc_norm_stderr\": 0.029680105565029036\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.470013037809648,\n\ \ \"acc_stderr\": 0.012747248967079051,\n \"acc_norm\": 0.470013037809648,\n\ \ \"acc_norm_stderr\": 0.012747248967079051\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5735294117647058,\n \"acc_stderr\": 0.03004261583271486,\n\ \ \"acc_norm\": 0.5735294117647058,\n \"acc_norm_stderr\": 0.03004261583271486\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6111111111111112,\n \"acc_stderr\": 0.01972205893961807,\n \ \ \"acc_norm\": 0.6111111111111112,\n \"acc_norm_stderr\": 0.01972205893961807\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.689795918367347,\n \"acc_stderr\": 0.029613459872484375,\n\ \ \"acc_norm\": 0.689795918367347,\n \"acc_norm_stderr\": 0.029613459872484375\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7412935323383084,\n\ \ \"acc_stderr\": 0.030965903123573026,\n \"acc_norm\": 0.7412935323383084,\n\ \ \"acc_norm_stderr\": 0.030965903123573026\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.8,\n \"acc_stderr\": 0.04020151261036843,\n \ \ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.04020151261036843\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7953216374269005,\n \"acc_stderr\": 0.030944459778533207,\n\ \ \"acc_norm\": 0.7953216374269005,\n \"acc_norm_stderr\": 0.030944459778533207\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3525091799265606,\n\ \ \"mc1_stderr\": 0.016724646380756547,\n \"mc2\": 0.5207310735270693,\n\ \ \"mc2_stderr\": 0.01596371997542123\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7419100236779794,\n \"acc_stderr\": 0.012298278833972387\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.45564821834723274,\n \ \ \"acc_stderr\": 0.013718194542485596\n }\n}\n```" repo_url: https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|arc:challenge|25_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|arc:challenge|25_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-02T04-15-22.465767.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|gsm8k|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|gsm8k|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hellaswag|10_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hellaswag|10_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-02T00-16-56.064220.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-02T04-15-22.465767.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-management|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-management|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T04-15-22.465767.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|truthfulqa:mc|0_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|truthfulqa:mc|0_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-02T04-15-22.465767.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_02T00_16_56.064220 path: - '**/details_harness|winogrande|5_2024-03-02T00-16-56.064220.parquet' - split: 2024_03_02T04_15_22.465767 path: - '**/details_harness|winogrande|5_2024-03-02T04-15-22.465767.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-02T04-15-22.465767.parquet' - config_name: results data_files: - split: 2024_03_02T00_16_56.064220 path: - results_2024-03-02T00-16-56.064220.parquet - split: 2024_03_02T04_15_22.465767 path: - results_2024-03-02T04-15-22.465767.parquet - split: latest path: - results_2024-03-02T04-15-22.465767.parquet --- # Dataset Card for Evaluation run of HuggingFaceH4/zephyr-7b-gemma-v0.1  Dataset automatically created during the evaluation run of model [HuggingFaceH4/zephyr-7b-gemma-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-02T04:15:22.465767](https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-gemma-v0.1/blob/main/results_2024-03-02T04-15-22.465767.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6064698705754529, "acc_stderr": 0.03312365418757596, "acc_norm": 0.6103117238998753, "acc_norm_stderr": 0.03378577550936012, "mc1": 0.3525091799265606, "mc1_stderr": 0.016724646380756547, "mc2": 0.5207310735270693, "mc2_stderr": 0.01596371997542123 }, "harness|arc:challenge|25": { "acc": 0.5563139931740614, "acc_stderr": 0.014518421825670444, "acc_norm": 0.5844709897610921, "acc_norm_stderr": 0.014401366641216384 }, "harness|hellaswag|10": { "acc": 0.6516630153355906, "acc_stderr": 0.004754697013354955, "acc_norm": 0.8347938657637921, "acc_norm_stderr": 0.003706075184380285 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.22, "acc_stderr": 0.04163331998932267, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932267 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5481481481481482, "acc_stderr": 0.04299268905480864, "acc_norm": 0.5481481481481482, "acc_norm_stderr": 0.04299268905480864 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7171052631578947, "acc_stderr": 0.03665349695640767, "acc_norm": 0.7171052631578947, "acc_norm_stderr": 0.03665349695640767 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6075471698113207, "acc_stderr": 0.03005258057955784, "acc_norm": 0.6075471698113207, "acc_norm_stderr": 0.03005258057955784 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7361111111111112, "acc_stderr": 0.03685651095897532, "acc_norm": 0.7361111111111112, "acc_norm_stderr": 0.03685651095897532 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6127167630057804, "acc_stderr": 0.03714325906302065, "acc_norm": 0.6127167630057804, "acc_norm_stderr": 0.03714325906302065 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.39215686274509803, "acc_stderr": 0.048580835742663454, "acc_norm": 0.39215686274509803, "acc_norm_stderr": 0.048580835742663454 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5617021276595745, "acc_stderr": 0.03243618636108102, "acc_norm": 0.5617021276595745, "acc_norm_stderr": 0.03243618636108102 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.40350877192982454, "acc_stderr": 0.046151869625837026, "acc_norm": 0.40350877192982454, "acc_norm_stderr": 0.046151869625837026 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6275862068965518, "acc_stderr": 0.04028731532947558, "acc_norm": 0.6275862068965518, "acc_norm_stderr": 0.04028731532947558 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4470899470899471, "acc_stderr": 0.025606723995777028, "acc_norm": 0.4470899470899471, "acc_norm_stderr": 0.025606723995777028 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7451612903225806, "acc_stderr": 0.024790118459332208, "acc_norm": 0.7451612903225806, "acc_norm_stderr": 0.024790118459332208 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.47783251231527096, "acc_stderr": 0.035145285621750094, "acc_norm": 0.47783251231527096, "acc_norm_stderr": 0.035145285621750094 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7151515151515152, "acc_stderr": 0.03524390844511781, "acc_norm": 0.7151515151515152, "acc_norm_stderr": 0.03524390844511781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8131313131313131, "acc_stderr": 0.027772533334218964, "acc_norm": 0.8131313131313131, "acc_norm_stderr": 0.027772533334218964 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8497409326424871, "acc_stderr": 0.02578772318072388, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.02578772318072388 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5897435897435898, "acc_stderr": 0.02493931390694079, "acc_norm": 0.5897435897435898, "acc_norm_stderr": 0.02493931390694079 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.362962962962963, "acc_stderr": 0.029318203645206868, "acc_norm": 0.362962962962963, "acc_norm_stderr": 0.029318203645206868 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6134453781512605, "acc_stderr": 0.0316314580755238, "acc_norm": 0.6134453781512605, "acc_norm_stderr": 0.0316314580755238 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.36423841059602646, "acc_stderr": 0.039291117812427424, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.039291117812427424 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8146788990825689, "acc_stderr": 0.016659279700295827, "acc_norm": 0.8146788990825689, "acc_norm_stderr": 0.016659279700295827 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7696078431372549, "acc_stderr": 0.029554292605695066, "acc_norm": 0.7696078431372549, "acc_norm_stderr": 0.029554292605695066 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7974683544303798, "acc_stderr": 0.026160568246601436, "acc_norm": 0.7974683544303798, "acc_norm_stderr": 0.026160568246601436 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6816143497757847, "acc_stderr": 0.03126580522513713, "acc_norm": 0.6816143497757847, "acc_norm_stderr": 0.03126580522513713 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.5801526717557252, "acc_stderr": 0.043285772152629715, "acc_norm": 0.5801526717557252, "acc_norm_stderr": 0.043285772152629715 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228732, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228732 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7314814814814815, "acc_stderr": 0.042844679680521934, "acc_norm": 0.7314814814814815, "acc_norm_stderr": 0.042844679680521934 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7239263803680982, "acc_stderr": 0.035123852837050475, "acc_norm": 0.7239263803680982, "acc_norm_stderr": 0.035123852837050475 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.4375, "acc_stderr": 0.04708567521880525, "acc_norm": 0.4375, "acc_norm_stderr": 0.04708567521880525 }, "harness|hendrycksTest-management|5": { "acc": 0.7961165048543689, "acc_stderr": 0.03989139859531771, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.03989139859531771 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8589743589743589, "acc_stderr": 0.022801382534597542, "acc_norm": 0.8589743589743589, "acc_norm_stderr": 0.022801382534597542 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7790549169859514, "acc_stderr": 0.014836205167333562, "acc_norm": 0.7790549169859514, "acc_norm_stderr": 0.014836205167333562 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6242774566473989, "acc_stderr": 0.02607431485165708, "acc_norm": 0.6242774566473989, "acc_norm_stderr": 0.02607431485165708 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.22569832402234638, "acc_stderr": 0.013981395058455066, "acc_norm": 0.22569832402234638, "acc_norm_stderr": 0.013981395058455066 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6568627450980392, "acc_stderr": 0.027184498909941616, "acc_norm": 0.6568627450980392, "acc_norm_stderr": 0.027184498909941616 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6495176848874598, "acc_stderr": 0.02709865262130175, "acc_norm": 0.6495176848874598, "acc_norm_stderr": 0.02709865262130175 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7006172839506173, "acc_stderr": 0.025483115601195448, "acc_norm": 0.7006172839506173, "acc_norm_stderr": 0.025483115601195448 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.450354609929078, "acc_stderr": 0.029680105565029036, "acc_norm": 0.450354609929078, "acc_norm_stderr": 0.029680105565029036 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.470013037809648, "acc_stderr": 0.012747248967079051, "acc_norm": 0.470013037809648, "acc_norm_stderr": 0.012747248967079051 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5735294117647058, "acc_stderr": 0.03004261583271486, "acc_norm": 0.5735294117647058, "acc_norm_stderr": 0.03004261583271486 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6111111111111112, "acc_stderr": 0.01972205893961807, "acc_norm": 0.6111111111111112, "acc_norm_stderr": 0.01972205893961807 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.689795918367347, "acc_stderr": 0.029613459872484375, "acc_norm": 0.689795918367347, "acc_norm_stderr": 0.029613459872484375 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7412935323383084, "acc_stderr": 0.030965903123573026, "acc_norm": 0.7412935323383084, "acc_norm_stderr": 0.030965903123573026 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.8, "acc_stderr": 0.04020151261036843, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036843 }, "harness|hendrycksTest-virology|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7953216374269005, "acc_stderr": 0.030944459778533207, "acc_norm": 0.7953216374269005, "acc_norm_stderr": 0.030944459778533207 }, "harness|truthfulqa:mc|0": { "mc1": 0.3525091799265606, "mc1_stderr": 0.016724646380756547, "mc2": 0.5207310735270693, "mc2_stderr": 0.01596371997542123 }, "harness|winogrande|5": { "acc": 0.7419100236779794, "acc_stderr": 0.012298278833972387 }, "harness|gsm8k|5": { "acc": 0.45564821834723274, "acc_stderr": 0.013718194542485596 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

Vageesh1/tokenized_contract_hf_selected

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: source_code dtype: string - name: success dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 1722286150 num_examples: 60000 download_size: 522906155 dataset_size: 1722286150 --- # Dataset Card for "tokenized_contract_hf_selected" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Anderson-Andre-P/text-template-to-summarize

--- license: mit task_categories: - summarization language: - pt tags: - code ---

Deivid457/Jennie

--- license: openrail ---

Codec-SUPERB/librispeech_asr_dummy_extract_unit

--- configs: - config_name: default data_files: - split: academicodec_hifi_16k_320d path: data/academicodec_hifi_16k_320d-* - split: academicodec_hifi_16k_320d_large_uni path: data/academicodec_hifi_16k_320d_large_uni-* - split: academicodec_hifi_24k_320d path: data/academicodec_hifi_24k_320d-* - split: audiodec_24k_320d path: data/audiodec_24k_320d-* - split: dac_16k path: data/dac_16k-* - split: dac_24k path: data/dac_24k-* - split: dac_44k path: data/dac_44k-* - split: encodec_24k path: data/encodec_24k-* - split: funcodec_en_libritts_16k_gr1nq32ds320 path: data/funcodec_en_libritts_16k_gr1nq32ds320-* - split: funcodec_en_libritts_16k_gr8nq32ds320 path: data/funcodec_en_libritts_16k_gr8nq32ds320-* - split: funcodec_en_libritts_16k_nq32ds320 path: data/funcodec_en_libritts_16k_nq32ds320-* - split: funcodec_en_libritts_16k_nq32ds640 path: data/funcodec_en_libritts_16k_nq32ds640-* - split: funcodec_zh_en_16k_nq32ds320 path: data/funcodec_zh_en_16k_nq32ds320-* - split: funcodec_zh_en_16k_nq32ds640 path: data/funcodec_zh_en_16k_nq32ds640-* - split: speech_tokenizer_16k path: data/speech_tokenizer_16k-* dataset_info: features: - name: id dtype: string - name: unit sequence: sequence: int64 splits: - name: academicodec_hifi_16k_320d num_bytes: 771752 num_examples: 73 - name: academicodec_hifi_16k_320d_large_uni num_bytes: 771752 num_examples: 73 - name: academicodec_hifi_24k_320d num_bytes: 1156456 num_examples: 73 - name: audiodec_24k_320d num_bytes: 2468728 num_examples: 73 - name: dac_16k num_bytes: 4813128 num_examples: 73 - name: dac_24k num_bytes: 13650008 num_examples: 73 - name: dac_44k num_bytes: 4047900 num_examples: 73 - name: encodec_24k num_bytes: 580208 num_examples: 73 - name: funcodec_en_libritts_16k_gr1nq32ds320 num_bytes: 6180696 num_examples: 73 - name: funcodec_en_libritts_16k_gr8nq32ds320 num_bytes: 6180696 num_examples: 73 - name: funcodec_en_libritts_16k_nq32ds320 num_bytes: 6179160 num_examples: 73 - name: funcodec_en_libritts_16k_nq32ds640 num_bytes: 3100504 num_examples: 73 - name: funcodec_zh_en_16k_nq32ds320 num_bytes: 6179160 num_examples: 73 - name: funcodec_zh_en_16k_nq32ds640 num_bytes: 6179160 num_examples: 73 - name: speech_tokenizer_16k num_bytes: 1546104 num_examples: 73 download_size: 10104884 dataset_size: 63805412 --- # Dataset Card for "librispeech_asr_dummy_extract_unit" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

DragonLine/ksponspeech_04

--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: transcripts dtype: string splits: - name: train num_bytes: 17609433455.2 num_examples: 99200 - name: test num_bytes: 2152518506.7 num_examples: 12400 - name: valid num_bytes: 2326954936.3 num_examples: 12400 download_size: 20778654985 dataset_size: 22088906898.2 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* ---

fathyshalab/massive_takeaway

--- dataset_info: features: - name: id dtype: string - name: label dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 14816 num_examples: 257 - name: validation num_bytes: 2450 num_examples: 44 - name: test num_bytes: 3176 num_examples: 57 download_size: 14963 dataset_size: 20442 --- # Dataset Card for "massive_takeaway" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

matejklemen/wi_locness

--- license: other dataset_info: - config_name: A features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 3847179 num_examples: 10493 - name: validation num_bytes: 392622 num_examples: 1037 download_size: 6120469 dataset_size: 4239801 - config_name: B features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 4649805 num_examples: 13032 - name: validation num_bytes: 468078 num_examples: 1290 download_size: 6120469 dataset_size: 5117883 - config_name: C features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 3765831 num_examples: 10783 - name: validation num_bytes: 390439 num_examples: 1069 download_size: 6120469 dataset_size: 4156270 - config_name: N features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: validation num_bytes: 421656 num_examples: 988 download_size: 6120469 dataset_size: 421656 - config_name: all features: - name: src_tokens sequence: string - name: tgt_tokens sequence: string - name: corrections list: - name: idx_src sequence: int32 - name: idx_tgt sequence: int32 - name: corr_type dtype: string splits: - name: train num_bytes: 12262815 num_examples: 34308 - name: validation num_bytes: 1672795 num_examples: 4384 download_size: 6120469 dataset_size: 13935610 ---

HydraLM/partitioned_v3_standardized_026

--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: dataset_id dtype: string - name: unique_id dtype: string splits: - name: train num_bytes: 34048776.63602931 num_examples: 63321 download_size: 5555939 dataset_size: 34048776.63602931 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "partitioned_v3_standardized_026" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Naveengo/sql-create-context-5000rows

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: context dtype: string splits: - name: train num_bytes: 1104644.8706364457 num_examples: 5000 download_size: 548687 dataset_size: 1104644.8706364457 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "sql-create-context-5000rows" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

KDAI-NLP/traffy-fondue-type-only

--- license: mit dataset_info: features: - name: ticket_id dtype: string - name: type dtype: string - name: comment dtype: string - name: timestamp dtype: timestamp[ns] - name: subdistrict dtype: string - name: district dtype: string - name: province dtype: string - name: is_ไม่ระบุ dtype: int64 - name: is_ความสะอาด dtype: int64 - name: is_สายไฟ dtype: int64 - name: is_สะพาน dtype: int64 - name: is_ถนน dtype: int64 - name: is_น้ำท่วม dtype: int64 - name: is_ร้องเรียน dtype: int64 - name: is_ท่อระบายน้ำ dtype: int64 - name: is_ความปลอดภัย dtype: int64 - name: is_คลอง dtype: int64 - name: is_แสงสว่าง dtype: int64 - name: is_ทางเท้า dtype: int64 - name: is_จราจร dtype: int64 - name: is_กีดขวาง dtype: int64 - name: is_การเดินทาง dtype: int64 - name: is_เสียงรบกวน dtype: int64 - name: is_ต้นไม้ dtype: int64 - name: is_สัตว์จรจัด dtype: int64 - name: is_เสนอแนะ dtype: int64 - name: is_คนจรจัด dtype: int64 - name: is_ห้องน้ำ dtype: int64 - name: is_ป้ายจราจร dtype: int64 - name: is_สอบถาม dtype: int64 - name: is_ป้าย dtype: int64 - name: is_PM2.5 dtype: int64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 326026940 num_examples: 406266 download_size: 0 dataset_size: 326026940 configs: - config_name: default data_files: - split: train path: data/train-* ---

bashmanxx/llama45train

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 17198108 num_examples: 13649 download_size: 2106426 dataset_size: 17198108 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3

--- pretty_name: Evaluation run of nlpguy/ColorShadow-7B-v3 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [nlpguy/ColorShadow-7B-v3](https://huggingface.co/nlpguy/ColorShadow-7B-v3) on\ \ the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-04T12:00:00.400283](https://huggingface.co/datasets/open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3/blob/main/results_2024-01-04T12-00-00.400283.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6077756404899893,\n\ \ \"acc_stderr\": 0.0331406868415802,\n \"acc_norm\": 0.6110717172741464,\n\ \ \"acc_norm_stderr\": 0.03381281098512482,\n \"mc1\": 0.45532435740514077,\n\ \ \"mc1_stderr\": 0.017433490102538765,\n \"mc2\": 0.6287894376799671,\n\ \ \"mc2_stderr\": 0.015043355245179869\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6313993174061433,\n \"acc_stderr\": 0.014097810678042196,\n\ \ \"acc_norm\": 0.6757679180887372,\n \"acc_norm_stderr\": 0.013678810399518822\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6394144592710616,\n\ \ \"acc_stderr\": 0.004791890625834189,\n \"acc_norm\": 0.8504282015534754,\n\ \ \"acc_norm_stderr\": 0.0035592230156104953\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5555555555555556,\n\ \ \"acc_stderr\": 0.04292596718256981,\n \"acc_norm\": 0.5555555555555556,\n\ \ \"acc_norm_stderr\": 0.04292596718256981\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.0373852067611967,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.0373852067611967\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.54,\n\ \ \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.54,\n \ \ \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6867924528301886,\n \"acc_stderr\": 0.028544793319055326,\n\ \ \"acc_norm\": 0.6867924528301886,\n \"acc_norm_stderr\": 0.028544793319055326\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.46,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107223,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107223\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768079,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768079\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5404255319148936,\n \"acc_stderr\": 0.03257901482099835,\n\ \ \"acc_norm\": 0.5404255319148936,\n \"acc_norm_stderr\": 0.03257901482099835\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4298245614035088,\n\ \ \"acc_stderr\": 0.04657047260594963,\n \"acc_norm\": 0.4298245614035088,\n\ \ \"acc_norm_stderr\": 0.04657047260594963\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5793103448275863,\n \"acc_stderr\": 0.0411391498118926,\n\ \ \"acc_norm\": 0.5793103448275863,\n \"acc_norm_stderr\": 0.0411391498118926\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3968253968253968,\n \"acc_stderr\": 0.02519710107424648,\n \"\ acc_norm\": 0.3968253968253968,\n \"acc_norm_stderr\": 0.02519710107424648\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3888888888888889,\n\ \ \"acc_stderr\": 0.04360314860077459,\n \"acc_norm\": 0.3888888888888889,\n\ \ \"acc_norm_stderr\": 0.04360314860077459\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.6838709677419355,\n\ \ \"acc_stderr\": 0.026450874489042764,\n \"acc_norm\": 0.6838709677419355,\n\ \ \"acc_norm_stderr\": 0.026450874489042764\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4876847290640394,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.4876847290640394,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.703030303030303,\n \"acc_stderr\": 0.03567969772268049,\n\ \ \"acc_norm\": 0.703030303030303,\n \"acc_norm_stderr\": 0.03567969772268049\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7474747474747475,\n \"acc_stderr\": 0.030954055470365907,\n \"\ acc_norm\": 0.7474747474747475,\n \"acc_norm_stderr\": 0.030954055470365907\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8497409326424871,\n \"acc_stderr\": 0.025787723180723886,\n\ \ \"acc_norm\": 0.8497409326424871,\n \"acc_norm_stderr\": 0.025787723180723886\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6256410256410256,\n \"acc_stderr\": 0.024537591572830506,\n\ \ \"acc_norm\": 0.6256410256410256,\n \"acc_norm_stderr\": 0.024537591572830506\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3296296296296296,\n \"acc_stderr\": 0.028661201116524575,\n \ \ \"acc_norm\": 0.3296296296296296,\n \"acc_norm_stderr\": 0.028661201116524575\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6470588235294118,\n \"acc_stderr\": 0.031041941304059285,\n\ \ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.031041941304059285\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3509933774834437,\n \"acc_stderr\": 0.03896981964257375,\n \"\ acc_norm\": 0.3509933774834437,\n \"acc_norm_stderr\": 0.03896981964257375\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8091743119266055,\n \"acc_stderr\": 0.016847676400091095,\n \"\ acc_norm\": 0.8091743119266055,\n \"acc_norm_stderr\": 0.016847676400091095\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.44907407407407407,\n \"acc_stderr\": 0.03392238405321616,\n \"\ acc_norm\": 0.44907407407407407,\n \"acc_norm_stderr\": 0.03392238405321616\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7254901960784313,\n \"acc_stderr\": 0.03132179803083289,\n \"\ acc_norm\": 0.7254901960784313,\n \"acc_norm_stderr\": 0.03132179803083289\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7721518987341772,\n \"acc_stderr\": 0.027303484599069422,\n \ \ \"acc_norm\": 0.7721518987341772,\n \"acc_norm_stderr\": 0.027303484599069422\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7175572519083969,\n \"acc_stderr\": 0.03948406125768361,\n\ \ \"acc_norm\": 0.7175572519083969,\n \"acc_norm_stderr\": 0.03948406125768361\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7933884297520661,\n \"acc_stderr\": 0.03695980128098825,\n \"\ acc_norm\": 0.7933884297520661,\n \"acc_norm_stderr\": 0.03695980128098825\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.04236511258094633,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.04236511258094633\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7116564417177914,\n \"acc_stderr\": 0.03559039531617342,\n\ \ \"acc_norm\": 0.7116564417177914,\n \"acc_norm_stderr\": 0.03559039531617342\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.44642857142857145,\n\ \ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\ \ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7184466019417476,\n \"acc_stderr\": 0.044532548363264673,\n\ \ \"acc_norm\": 0.7184466019417476,\n \"acc_norm_stderr\": 0.044532548363264673\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406978,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406978\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7816091954022989,\n\ \ \"acc_stderr\": 0.014774358319934495,\n \"acc_norm\": 0.7816091954022989,\n\ \ \"acc_norm_stderr\": 0.014774358319934495\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7052023121387283,\n \"acc_stderr\": 0.024547617794803828,\n\ \ \"acc_norm\": 0.7052023121387283,\n \"acc_norm_stderr\": 0.024547617794803828\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.36089385474860336,\n\ \ \"acc_stderr\": 0.01606229067111047,\n \"acc_norm\": 0.36089385474860336,\n\ \ \"acc_norm_stderr\": 0.01606229067111047\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6633986928104575,\n \"acc_stderr\": 0.02705797462449438,\n\ \ \"acc_norm\": 0.6633986928104575,\n \"acc_norm_stderr\": 0.02705797462449438\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.684887459807074,\n\ \ \"acc_stderr\": 0.026385273703464496,\n \"acc_norm\": 0.684887459807074,\n\ \ \"acc_norm_stderr\": 0.026385273703464496\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6635802469135802,\n \"acc_stderr\": 0.02628973494595293,\n\ \ \"acc_norm\": 0.6635802469135802,\n \"acc_norm_stderr\": 0.02628973494595293\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \ \ \"acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.43089960886571055,\n\ \ \"acc_stderr\": 0.012647695889547228,\n \"acc_norm\": 0.43089960886571055,\n\ \ \"acc_norm_stderr\": 0.012647695889547228\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5661764705882353,\n \"acc_stderr\": 0.030105636570016633,\n\ \ \"acc_norm\": 0.5661764705882353,\n \"acc_norm_stderr\": 0.030105636570016633\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6405228758169934,\n \"acc_stderr\": 0.019412539242032168,\n \ \ \"acc_norm\": 0.6405228758169934,\n \"acc_norm_stderr\": 0.019412539242032168\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6938775510204082,\n \"acc_stderr\": 0.029504896454595957,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.029504896454595957\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6766169154228856,\n\ \ \"acc_stderr\": 0.03307615947979033,\n \"acc_norm\": 0.6766169154228856,\n\ \ \"acc_norm_stderr\": 0.03307615947979033\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.82,\n \"acc_stderr\": 0.03861229196653693,\n \ \ \"acc_norm\": 0.82,\n \"acc_norm_stderr\": 0.03861229196653693\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5,\n \ \ \"acc_stderr\": 0.03892494720807614,\n \"acc_norm\": 0.5,\n \"\ acc_norm_stderr\": 0.03892494720807614\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.02954774168764004,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.02954774168764004\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.45532435740514077,\n\ \ \"mc1_stderr\": 0.017433490102538765,\n \"mc2\": 0.6287894376799671,\n\ \ \"mc2_stderr\": 0.015043355245179869\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8011049723756906,\n \"acc_stderr\": 0.011218629972515302\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.47536012130401817,\n \ \ \"acc_stderr\": 0.013755751352764918\n }\n}\n```" repo_url: https://huggingface.co/nlpguy/ColorShadow-7B-v3 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|arc:challenge|25_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-04T12-00-00.400283.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|gsm8k|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hellaswag|10_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-00-00.400283.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-management|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-00-00.400283.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|truthfulqa:mc|0_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-04T12-00-00.400283.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_04T12_00_00.400283 path: - '**/details_harness|winogrande|5_2024-01-04T12-00-00.400283.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-04T12-00-00.400283.parquet' - config_name: results data_files: - split: 2024_01_04T12_00_00.400283 path: - results_2024-01-04T12-00-00.400283.parquet - split: latest path: - results_2024-01-04T12-00-00.400283.parquet --- # Dataset Card for Evaluation run of nlpguy/ColorShadow-7B-v3  Dataset automatically created during the evaluation run of model [nlpguy/ColorShadow-7B-v3](https://huggingface.co/nlpguy/ColorShadow-7B-v3) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-04T12:00:00.400283](https://huggingface.co/datasets/open-llm-leaderboard/details_nlpguy__ColorShadow-7B-v3/blob/main/results_2024-01-04T12-00-00.400283.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6077756404899893, "acc_stderr": 0.0331406868415802, "acc_norm": 0.6110717172741464, "acc_norm_stderr": 0.03381281098512482, "mc1": 0.45532435740514077, "mc1_stderr": 0.017433490102538765, "mc2": 0.6287894376799671, "mc2_stderr": 0.015043355245179869 }, "harness|arc:challenge|25": { "acc": 0.6313993174061433, "acc_stderr": 0.014097810678042196, "acc_norm": 0.6757679180887372, "acc_norm_stderr": 0.013678810399518822 }, "harness|hellaswag|10": { "acc": 0.6394144592710616, "acc_stderr": 0.004791890625834189, "acc_norm": 0.8504282015534754, "acc_norm_stderr": 0.0035592230156104953 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5555555555555556, "acc_stderr": 0.04292596718256981, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.04292596718256981 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6973684210526315, "acc_stderr": 0.0373852067611967, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.0373852067611967 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6867924528301886, "acc_stderr": 0.028544793319055326, "acc_norm": 0.6867924528301886, "acc_norm_stderr": 0.028544793319055326 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7222222222222222, "acc_stderr": 0.037455547914624555, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.037455547914624555 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5404255319148936, "acc_stderr": 0.03257901482099835, "acc_norm": 0.5404255319148936, "acc_norm_stderr": 0.03257901482099835 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4298245614035088, "acc_stderr": 0.04657047260594963, "acc_norm": 0.4298245614035088, "acc_norm_stderr": 0.04657047260594963 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5793103448275863, "acc_stderr": 0.0411391498118926, "acc_norm": 0.5793103448275863, "acc_norm_stderr": 0.0411391498118926 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3968253968253968, "acc_stderr": 0.02519710107424648, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.02519710107424648 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3888888888888889, "acc_stderr": 0.04360314860077459, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.04360314860077459 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6838709677419355, "acc_stderr": 0.026450874489042764, "acc_norm": 0.6838709677419355, "acc_norm_stderr": 0.026450874489042764 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4876847290640394, "acc_stderr": 0.035169204442208966, "acc_norm": 0.4876847290640394, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.703030303030303, "acc_stderr": 0.03567969772268049, "acc_norm": 0.703030303030303, "acc_norm_stderr": 0.03567969772268049 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7474747474747475, "acc_stderr": 0.030954055470365907, "acc_norm": 0.7474747474747475, "acc_norm_stderr": 0.030954055470365907 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8497409326424871, "acc_stderr": 0.025787723180723886, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.025787723180723886 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6256410256410256, "acc_stderr": 0.024537591572830506, "acc_norm": 0.6256410256410256, "acc_norm_stderr": 0.024537591572830506 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3296296296296296, "acc_stderr": 0.028661201116524575, "acc_norm": 0.3296296296296296, "acc_norm_stderr": 0.028661201116524575 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6470588235294118, "acc_stderr": 0.031041941304059285, "acc_norm": 0.6470588235294118, "acc_norm_stderr": 0.031041941304059285 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3509933774834437, "acc_stderr": 0.03896981964257375, "acc_norm": 0.3509933774834437, "acc_norm_stderr": 0.03896981964257375 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8091743119266055, "acc_stderr": 0.016847676400091095, "acc_norm": 0.8091743119266055, "acc_norm_stderr": 0.016847676400091095 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.44907407407407407, "acc_stderr": 0.03392238405321616, "acc_norm": 0.44907407407407407, "acc_norm_stderr": 0.03392238405321616 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7254901960784313, "acc_stderr": 0.03132179803083289, "acc_norm": 0.7254901960784313, "acc_norm_stderr": 0.03132179803083289 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7721518987341772, "acc_stderr": 0.027303484599069422, "acc_norm": 0.7721518987341772, "acc_norm_stderr": 0.027303484599069422 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7175572519083969, "acc_stderr": 0.03948406125768361, "acc_norm": 0.7175572519083969, "acc_norm_stderr": 0.03948406125768361 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7933884297520661, "acc_stderr": 0.03695980128098825, "acc_norm": 0.7933884297520661, "acc_norm_stderr": 0.03695980128098825 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7407407407407407, "acc_stderr": 0.04236511258094633, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.04236511258094633 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7116564417177914, "acc_stderr": 0.03559039531617342, "acc_norm": 0.7116564417177914, "acc_norm_stderr": 0.03559039531617342 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.44642857142857145, "acc_stderr": 0.04718471485219588, "acc_norm": 0.44642857142857145, "acc_norm_stderr": 0.04718471485219588 }, "harness|hendrycksTest-management|5": { "acc": 0.7184466019417476, "acc_stderr": 0.044532548363264673, "acc_norm": 0.7184466019417476, "acc_norm_stderr": 0.044532548363264673 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406978, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406978 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7816091954022989, "acc_stderr": 0.014774358319934495, "acc_norm": 0.7816091954022989, "acc_norm_stderr": 0.014774358319934495 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7052023121387283, "acc_stderr": 0.024547617794803828, "acc_norm": 0.7052023121387283, "acc_norm_stderr": 0.024547617794803828 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.36089385474860336, "acc_stderr": 0.01606229067111047, "acc_norm": 0.36089385474860336, "acc_norm_stderr": 0.01606229067111047 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6633986928104575, "acc_stderr": 0.02705797462449438, "acc_norm": 0.6633986928104575, "acc_norm_stderr": 0.02705797462449438 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.684887459807074, "acc_stderr": 0.026385273703464496, "acc_norm": 0.684887459807074, "acc_norm_stderr": 0.026385273703464496 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6635802469135802, "acc_stderr": 0.02628973494595293, "acc_norm": 0.6635802469135802, "acc_norm_stderr": 0.02628973494595293 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4787234042553192, "acc_stderr": 0.029800481645628693, "acc_norm": 0.4787234042553192, "acc_norm_stderr": 0.029800481645628693 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.43089960886571055, "acc_stderr": 0.012647695889547228, "acc_norm": 0.43089960886571055, "acc_norm_stderr": 0.012647695889547228 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5661764705882353, "acc_stderr": 0.030105636570016633, "acc_norm": 0.5661764705882353, "acc_norm_stderr": 0.030105636570016633 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6405228758169934, "acc_stderr": 0.019412539242032168, "acc_norm": 0.6405228758169934, "acc_norm_stderr": 0.019412539242032168 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6938775510204082, "acc_stderr": 0.029504896454595957, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.029504896454595957 }, "harness|hendrycksTest-sociology|5": { "acc": 0.6766169154228856, "acc_stderr": 0.03307615947979033, "acc_norm": 0.6766169154228856, "acc_norm_stderr": 0.03307615947979033 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.82, "acc_stderr": 0.03861229196653693, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653693 }, "harness|hendrycksTest-virology|5": { "acc": 0.5, "acc_stderr": 0.03892494720807614, "acc_norm": 0.5, "acc_norm_stderr": 0.03892494720807614 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8187134502923976, "acc_stderr": 0.02954774168764004, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.02954774168764004 }, "harness|truthfulqa:mc|0": { "mc1": 0.45532435740514077, "mc1_stderr": 0.017433490102538765, "mc2": 0.6287894376799671, "mc2_stderr": 0.015043355245179869 }, "harness|winogrande|5": { "acc": 0.8011049723756906, "acc_stderr": 0.011218629972515302 }, "harness|gsm8k|5": { "acc": 0.47536012130401817, "acc_stderr": 0.013755751352764918 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

open-llm-leaderboard/details_ChavyvAkvar__habib-DPO

--- pretty_name: Evaluation run of ChavyvAkvar/habib-DPO dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [ChavyvAkvar/habib-DPO](https://huggingface.co/ChavyvAkvar/habib-DPO) on the [Open\ \ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_ChavyvAkvar__habib-DPO\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-08T14:15:05.108726](https://huggingface.co/datasets/open-llm-leaderboard/details_ChavyvAkvar__habib-DPO/blob/main/results_2024-04-08T14-15-05.108726.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6463086057955821,\n\ \ \"acc_stderr\": 0.03219641610397338,\n \"acc_norm\": 0.6470499429849053,\n\ \ \"acc_norm_stderr\": 0.0328482314699445,\n \"mc1\": 0.4847001223990208,\n\ \ \"mc1_stderr\": 0.017495304473187902,\n \"mc2\": 0.6519725385425954,\n\ \ \"mc2_stderr\": 0.015460535740302407\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6569965870307167,\n \"acc_stderr\": 0.013872423223718166,\n\ \ \"acc_norm\": 0.6868600682593856,\n \"acc_norm_stderr\": 0.01355267154362349\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6899024098785103,\n\ \ \"acc_stderr\": 0.004615880352799734,\n \"acc_norm\": 0.8670583549093805,\n\ \ \"acc_norm_stderr\": 0.003388177893268278\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6444444444444445,\n\ \ \"acc_stderr\": 0.04135176749720386,\n \"acc_norm\": 0.6444444444444445,\n\ \ \"acc_norm_stderr\": 0.04135176749720386\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6842105263157895,\n \"acc_stderr\": 0.0378272898086547,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.0378272898086547\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7245283018867924,\n \"acc_stderr\": 0.027495663683724064,\n\ \ \"acc_norm\": 0.7245283018867924,\n \"acc_norm_stderr\": 0.027495663683724064\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7430555555555556,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.7430555555555556,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-college_computer_science|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness|hendrycksTest-college_mathematics|5\": {\n \"acc\": 0.31,\n\ \ \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.31,\n \ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-college_medicine|5\"\ : {\n \"acc\": 0.6705202312138728,\n \"acc_stderr\": 0.03583901754736412,\n\ \ \"acc_norm\": 0.6705202312138728,\n \"acc_norm_stderr\": 0.03583901754736412\n\ \ },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.04690650298201942,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.04690650298201942\n },\n \"harness|hendrycksTest-computer_security|5\"\ : {\n \"acc\": 0.76,\n \"acc_stderr\": 0.042923469599092816,\n \ \ \"acc_norm\": 0.76,\n \"acc_norm_stderr\": 0.042923469599092816\n \ \ },\n \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\":\ \ 0.5957446808510638,\n \"acc_stderr\": 0.03208115750788684,\n \"\ acc_norm\": 0.5957446808510638,\n \"acc_norm_stderr\": 0.03208115750788684\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5175438596491229,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.5175438596491229,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5793103448275863,\n \"acc_stderr\": 0.0411391498118926,\n\ \ \"acc_norm\": 0.5793103448275863,\n \"acc_norm_stderr\": 0.0411391498118926\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.42592592592592593,\n \"acc_stderr\": 0.02546714904546955,\n \"\ acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.02546714904546955\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.48412698412698413,\n\ \ \"acc_stderr\": 0.04469881854072606,\n \"acc_norm\": 0.48412698412698413,\n\ \ \"acc_norm_stderr\": 0.04469881854072606\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7741935483870968,\n\ \ \"acc_stderr\": 0.023785577884181012,\n \"acc_norm\": 0.7741935483870968,\n\ \ \"acc_norm_stderr\": 0.023785577884181012\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.49261083743842365,\n \"acc_stderr\": 0.03517603540361008,\n\ \ \"acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.03517603540361008\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7575757575757576,\n \"acc_stderr\": 0.03346409881055953,\n\ \ \"acc_norm\": 0.7575757575757576,\n \"acc_norm_stderr\": 0.03346409881055953\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.029620227874790486,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.029620227874790486\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8860103626943006,\n \"acc_stderr\": 0.022935144053919443,\n\ \ \"acc_norm\": 0.8860103626943006,\n \"acc_norm_stderr\": 0.022935144053919443\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6564102564102564,\n \"acc_stderr\": 0.024078696580635477,\n\ \ \"acc_norm\": 0.6564102564102564,\n \"acc_norm_stderr\": 0.024078696580635477\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3296296296296296,\n \"acc_stderr\": 0.028661201116524565,\n \ \ \"acc_norm\": 0.3296296296296296,\n \"acc_norm_stderr\": 0.028661201116524565\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.030388353551886793,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.030388353551886793\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8550458715596331,\n \"acc_stderr\": 0.015094215699700476,\n \"\ acc_norm\": 0.8550458715596331,\n \"acc_norm_stderr\": 0.015094215699700476\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5046296296296297,\n \"acc_stderr\": 0.03409825519163572,\n \"\ acc_norm\": 0.5046296296296297,\n \"acc_norm_stderr\": 0.03409825519163572\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8382352941176471,\n \"acc_stderr\": 0.025845017986926913,\n \"\ acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.025845017986926913\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8143459915611815,\n \"acc_stderr\": 0.025310495376944856,\n \ \ \"acc_norm\": 0.8143459915611815,\n \"acc_norm_stderr\": 0.025310495376944856\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6995515695067265,\n\ \ \"acc_stderr\": 0.030769352008229143,\n \"acc_norm\": 0.6995515695067265,\n\ \ \"acc_norm_stderr\": 0.030769352008229143\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.03641297081313729,\n\ \ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.03641297081313729\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7851239669421488,\n \"acc_stderr\": 0.037494924487096966,\n \"\ acc_norm\": 0.7851239669421488,\n \"acc_norm_stderr\": 0.037494924487096966\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7607361963190185,\n \"acc_stderr\": 0.033519538795212696,\n\ \ \"acc_norm\": 0.7607361963190185,\n \"acc_norm_stderr\": 0.033519538795212696\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\ \ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8547008547008547,\n\ \ \"acc_stderr\": 0.023086635086841403,\n \"acc_norm\": 0.8547008547008547,\n\ \ \"acc_norm_stderr\": 0.023086635086841403\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.73,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8186462324393359,\n\ \ \"acc_stderr\": 0.013778693778464074,\n \"acc_norm\": 0.8186462324393359,\n\ \ \"acc_norm_stderr\": 0.013778693778464074\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7398843930635838,\n \"acc_stderr\": 0.023618678310069356,\n\ \ \"acc_norm\": 0.7398843930635838,\n \"acc_norm_stderr\": 0.023618678310069356\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4480446927374302,\n\ \ \"acc_stderr\": 0.016631976628930595,\n \"acc_norm\": 0.4480446927374302,\n\ \ \"acc_norm_stderr\": 0.016631976628930595\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7026143790849673,\n \"acc_stderr\": 0.02617390850671858,\n\ \ \"acc_norm\": 0.7026143790849673,\n \"acc_norm_stderr\": 0.02617390850671858\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.729903536977492,\n\ \ \"acc_stderr\": 0.02521804037341063,\n \"acc_norm\": 0.729903536977492,\n\ \ \"acc_norm_stderr\": 0.02521804037341063\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7160493827160493,\n \"acc_stderr\": 0.025089478523765137,\n\ \ \"acc_norm\": 0.7160493827160493,\n \"acc_norm_stderr\": 0.025089478523765137\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4716312056737589,\n \"acc_stderr\": 0.029779450957303062,\n \ \ \"acc_norm\": 0.4716312056737589,\n \"acc_norm_stderr\": 0.029779450957303062\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46153846153846156,\n\ \ \"acc_stderr\": 0.01273239828619044,\n \"acc_norm\": 0.46153846153846156,\n\ \ \"acc_norm_stderr\": 0.01273239828619044\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6948529411764706,\n \"acc_stderr\": 0.027971541370170598,\n\ \ \"acc_norm\": 0.6948529411764706,\n \"acc_norm_stderr\": 0.027971541370170598\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6454248366013072,\n \"acc_stderr\": 0.0193533605475537,\n \ \ \"acc_norm\": 0.6454248366013072,\n \"acc_norm_stderr\": 0.0193533605475537\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784593,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784593\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.835820895522388,\n\ \ \"acc_stderr\": 0.026193923544454115,\n \"acc_norm\": 0.835820895522388,\n\ \ \"acc_norm_stderr\": 0.026193923544454115\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5180722891566265,\n\ \ \"acc_stderr\": 0.03889951252827216,\n \"acc_norm\": 0.5180722891566265,\n\ \ \"acc_norm_stderr\": 0.03889951252827216\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8304093567251462,\n \"acc_stderr\": 0.02878210810540171,\n\ \ \"acc_norm\": 0.8304093567251462,\n \"acc_norm_stderr\": 0.02878210810540171\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4847001223990208,\n\ \ \"mc1_stderr\": 0.017495304473187902,\n \"mc2\": 0.6519725385425954,\n\ \ \"mc2_stderr\": 0.015460535740302407\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7947908445146015,\n \"acc_stderr\": 0.011350315707462068\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6611068991660348,\n \ \ \"acc_stderr\": 0.013037955768562507\n }\n}\n```" repo_url: https://huggingface.co/ChavyvAkvar/habib-DPO leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|arc:challenge|25_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-04-08T14-15-05.108726.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|gsm8k|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hellaswag|10_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-08T14-15-05.108726.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-management|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-virology|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-08T14-15-05.108726.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|truthfulqa:mc|0_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-04-08T14-15-05.108726.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_08T14_15_05.108726 path: - '**/details_harness|winogrande|5_2024-04-08T14-15-05.108726.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-04-08T14-15-05.108726.parquet' - config_name: results data_files: - split: 2024_04_08T14_15_05.108726 path: - results_2024-04-08T14-15-05.108726.parquet - split: latest path: - results_2024-04-08T14-15-05.108726.parquet --- # Dataset Card for Evaluation run of ChavyvAkvar/habib-DPO  Dataset automatically created during the evaluation run of model [ChavyvAkvar/habib-DPO](https://huggingface.co/ChavyvAkvar/habib-DPO) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_ChavyvAkvar__habib-DPO", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-08T14:15:05.108726](https://huggingface.co/datasets/open-llm-leaderboard/details_ChavyvAkvar__habib-DPO/blob/main/results_2024-04-08T14-15-05.108726.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6463086057955821, "acc_stderr": 0.03219641610397338, "acc_norm": 0.6470499429849053, "acc_norm_stderr": 0.0328482314699445, "mc1": 0.4847001223990208, "mc1_stderr": 0.017495304473187902, "mc2": 0.6519725385425954, "mc2_stderr": 0.015460535740302407 }, "harness|arc:challenge|25": { "acc": 0.6569965870307167, "acc_stderr": 0.013872423223718166, "acc_norm": 0.6868600682593856, "acc_norm_stderr": 0.01355267154362349 }, "harness|hellaswag|10": { "acc": 0.6899024098785103, "acc_stderr": 0.004615880352799734, "acc_norm": 0.8670583549093805, "acc_norm_stderr": 0.003388177893268278 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6444444444444445, "acc_stderr": 0.04135176749720386, "acc_norm": 0.6444444444444445, "acc_norm_stderr": 0.04135176749720386 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6842105263157895, "acc_stderr": 0.0378272898086547, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.0378272898086547 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7245283018867924, "acc_stderr": 0.027495663683724064, "acc_norm": 0.7245283018867924, "acc_norm_stderr": 0.027495663683724064 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7430555555555556, "acc_stderr": 0.03653946969442099, "acc_norm": 0.7430555555555556, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201942, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201942 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5957446808510638, "acc_stderr": 0.03208115750788684, "acc_norm": 0.5957446808510638, "acc_norm_stderr": 0.03208115750788684 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5793103448275863, "acc_stderr": 0.0411391498118926, "acc_norm": 0.5793103448275863, "acc_norm_stderr": 0.0411391498118926 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42592592592592593, "acc_stderr": 0.02546714904546955, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.02546714904546955 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.48412698412698413, "acc_stderr": 0.04469881854072606, "acc_norm": 0.48412698412698413, "acc_norm_stderr": 0.04469881854072606 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7741935483870968, "acc_stderr": 0.023785577884181012, "acc_norm": 0.7741935483870968, "acc_norm_stderr": 0.023785577884181012 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.49261083743842365, "acc_stderr": 0.03517603540361008, "acc_norm": 0.49261083743842365, "acc_norm_stderr": 0.03517603540361008 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7575757575757576, "acc_stderr": 0.03346409881055953, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.03346409881055953 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7777777777777778, "acc_stderr": 0.029620227874790486, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.029620227874790486 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8860103626943006, "acc_stderr": 0.022935144053919443, "acc_norm": 0.8860103626943006, "acc_norm_stderr": 0.022935144053919443 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6564102564102564, "acc_stderr": 0.024078696580635477, "acc_norm": 0.6564102564102564, "acc_norm_stderr": 0.024078696580635477 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3296296296296296, "acc_stderr": 0.028661201116524565, "acc_norm": 0.3296296296296296, "acc_norm_stderr": 0.028661201116524565 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6764705882352942, "acc_stderr": 0.030388353551886793, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.030388353551886793 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8550458715596331, "acc_stderr": 0.015094215699700476, "acc_norm": 0.8550458715596331, "acc_norm_stderr": 0.015094215699700476 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5046296296296297, "acc_stderr": 0.03409825519163572, "acc_norm": 0.5046296296296297, "acc_norm_stderr": 0.03409825519163572 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8382352941176471, "acc_stderr": 0.025845017986926913, "acc_norm": 0.8382352941176471, "acc_norm_stderr": 0.025845017986926913 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8143459915611815, "acc_stderr": 0.025310495376944856, "acc_norm": 0.8143459915611815, "acc_norm_stderr": 0.025310495376944856 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6995515695067265, "acc_stderr": 0.030769352008229143, "acc_norm": 0.6995515695067265, "acc_norm_stderr": 0.030769352008229143 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7786259541984732, "acc_stderr": 0.03641297081313729, "acc_norm": 0.7786259541984732, "acc_norm_stderr": 0.03641297081313729 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7851239669421488, "acc_stderr": 0.037494924487096966, "acc_norm": 0.7851239669421488, "acc_norm_stderr": 0.037494924487096966 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7607361963190185, "acc_stderr": 0.033519538795212696, "acc_norm": 0.7607361963190185, "acc_norm_stderr": 0.033519538795212696 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness|hendrycksTest-management|5": { "acc": 0.7864077669902912, "acc_stderr": 0.040580420156460344, "acc_norm": 0.7864077669902912, "acc_norm_stderr": 0.040580420156460344 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8547008547008547, "acc_stderr": 0.023086635086841403, "acc_norm": 0.8547008547008547, "acc_norm_stderr": 0.023086635086841403 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.73, "acc_stderr": 0.0446196043338474, "acc_norm": 0.73, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8186462324393359, "acc_stderr": 0.013778693778464074, "acc_norm": 0.8186462324393359, "acc_norm_stderr": 0.013778693778464074 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7398843930635838, "acc_stderr": 0.023618678310069356, "acc_norm": 0.7398843930635838, "acc_norm_stderr": 0.023618678310069356 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.4480446927374302, "acc_stderr": 0.016631976628930595, "acc_norm": 0.4480446927374302, "acc_norm_stderr": 0.016631976628930595 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7026143790849673, "acc_stderr": 0.02617390850671858, "acc_norm": 0.7026143790849673, "acc_norm_stderr": 0.02617390850671858 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.729903536977492, "acc_stderr": 0.02521804037341063, "acc_norm": 0.729903536977492, "acc_norm_stderr": 0.02521804037341063 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7160493827160493, "acc_stderr": 0.025089478523765137, "acc_norm": 0.7160493827160493, "acc_norm_stderr": 0.025089478523765137 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4716312056737589, "acc_stderr": 0.029779450957303062, "acc_norm": 0.4716312056737589, "acc_norm_stderr": 0.029779450957303062 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.46153846153846156, "acc_stderr": 0.01273239828619044, "acc_norm": 0.46153846153846156, "acc_norm_stderr": 0.01273239828619044 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6948529411764706, "acc_stderr": 0.027971541370170598, "acc_norm": 0.6948529411764706, "acc_norm_stderr": 0.027971541370170598 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6454248366013072, "acc_stderr": 0.0193533605475537, "acc_norm": 0.6454248366013072, "acc_norm_stderr": 0.0193533605475537 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6636363636363637, "acc_stderr": 0.04525393596302506, "acc_norm": 0.6636363636363637, "acc_norm_stderr": 0.04525393596302506 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784593, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784593 }, "harness|hendrycksTest-sociology|5": { "acc": 0.835820895522388, "acc_stderr": 0.026193923544454115, "acc_norm": 0.835820895522388, "acc_norm_stderr": 0.026193923544454115 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness|hendrycksTest-virology|5": { "acc": 0.5180722891566265, "acc_stderr": 0.03889951252827216, "acc_norm": 0.5180722891566265, "acc_norm_stderr": 0.03889951252827216 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8304093567251462, "acc_stderr": 0.02878210810540171, "acc_norm": 0.8304093567251462, "acc_norm_stderr": 0.02878210810540171 }, "harness|truthfulqa:mc|0": { "mc1": 0.4847001223990208, "mc1_stderr": 0.017495304473187902, "mc2": 0.6519725385425954, "mc2_stderr": 0.015460535740302407 }, "harness|winogrande|5": { "acc": 0.7947908445146015, "acc_stderr": 0.011350315707462068 }, "harness|gsm8k|5": { "acc": 0.6611068991660348, "acc_stderr": 0.013037955768562507 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

Ismagopo/TradingZoo

--- license: openrail ---

JoshVictor/platypus-Jo-data

--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 2253597 num_examples: 1000 download_size: 1118629 dataset_size: 2253597 configs: - config_name: default data_files: - split: train path: data/train-* ---

pccl-org/formal-logic-simple-order-multi-token-dynamic-objects-paired-relationship-0-100

--- dataset_info: features: - name: greater_than sequence: int64 - name: less_than sequence: int64 - name: paired_example sequence: sequence: sequence: int64 - name: correct_example sequence: sequence: int64 - name: incorrect_example sequence: sequence: int64 - name: distance dtype: int64 - name: index dtype: int64 - name: index_in_distance dtype: int64 splits: - name: train num_bytes: 1397336 num_examples: 4950 download_size: 159651 dataset_size: 1397336 configs: - config_name: default data_files: - split: train path: data/train-* ---

Deojoandco/dialogturns_not_generated_val

--- dataset_info: features: - name: url dtype: string - name: id dtype: string - name: num_comments dtype: int64 - name: name dtype: string - name: title dtype: string - name: body dtype: string - name: score dtype: int64 - name: upvote_ratio dtype: float64 - name: distinguished dtype: 'null' - name: over_18 dtype: bool - name: created_utc dtype: int64 - name: comments list: - name: body dtype: string - name: created_utc dtype: float64 - name: distinguished dtype: string - name: id dtype: string - name: permalink dtype: string - name: score dtype: int64 - name: best_num_comments dtype: int64 - name: query dtype: string - name: dialog dtype: string - name: annotation_success dtype: bool - name: annotation_text dtype: string - name: turns_generated dtype: bool - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 493996 num_examples: 25 download_size: 304777 dataset_size: 493996 --- # Dataset Card for "dialogturns_not_generated_val" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

dolo650/lamini_docs_processed

--- license: apache-2.0 --- License/Credit goes to the original creators of the dataset. This is a sample dataset used for instruction fine tuning of LLMs

danielz01/BigEarthNet-S2-v1.0

--- configs: - config_name: s2-rgb data_files: - split: test path: s2-rgb/test-* - split: val path: s2-rgb/val-* - split: train path: s2-rgb/train-* dataset_info: config_name: s2-rgb features: - name: img dtype: image - name: labels sequence: string - name: coordinates struct: - name: lrx dtype: int64 - name: lry dtype: int64 - name: ulx dtype: int64 - name: uly dtype: int64 - name: projection dtype: string - name: tile_source dtype: string - name: acquisition_date dtype: string splits: - name: test num_bytes: 3453114936.75 num_examples: 125866 - name: val num_bytes: 3393628600.625 num_examples: 123723 - name: train num_bytes: 7391482704.125 num_examples: 269695 download_size: 13839792533 dataset_size: 14238226241.5 --- # Dataset Card for "BigEarthNet-S2-v1.0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

mateusartur/mateusartur

--- license: openrail ---

316usman/thematic1d

--- license: bsd dataset_info: features: - name: text dtype: string - name: thematic dtype: string - name: sub-thematic dtype: string - name: country dtype: string - name: document_url dtype: string - name: source_url dtype: string splits: - name: train num_bytes: 109014361 num_examples: 147302 download_size: 32599891 dataset_size: 109014361 configs: - config_name: default data_files: - split: train path: data/train-* ---

PL-MTEB/polemo2_in

--- license: cc-by-nc-sa-4.0 ---

lishuyang/recipepairs

--- annotations_creators: no-annotation language_creators: found language: en license: gpl-3.0 multilinguality: monolingual size_categories: - 1M<n<10M source_datasets: original task_categories: - text-generation pretty_name: RecipePairs dataset_info: - config_name: 1.5.0 splits: - name: pairs num_examples: 6908697 --- RecipePairs dataset, originally from the 2022 EMNLP paper: ["SHARE: a System for Hierarchical Assistive Recipe Editing"](https://aclanthology.org/2022.emnlp-main.761/) by Shuyang Li, Yufei Li, Jianmo Ni, and Julian McAuley. This version (1.5.0) has been updated with 6.9M pairs of `base -> target` recipes, alongside their name overlap, IOU (longest common subsequence / union), and target dietary categories. These cover the 459K recipes from the original GeniusKitcen/Food.com dataset. If you would like to use this data or found it useful in your work/research, please cite the following papers: ``` @inproceedings{li-etal-2022-share, title = "{SHARE}: a System for Hierarchical Assistive Recipe Editing", author = "Li, Shuyang and Li, Yufei and Ni, Jianmo and McAuley, Julian", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, United Arab Emirates", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.emnlp-main.761", pages = "11077--11090", abstract = "The large population of home cooks with dietary restrictions is under-served by existing cooking resources and recipe generation models. To help them, we propose the task of controllable recipe editing: adapt a base recipe to satisfy a user-specified dietary constraint. This task is challenging, and cannot be adequately solved with human-written ingredient substitution rules or existing end-to-end recipe generation models. We tackle this problem with SHARE: a System for Hierarchical Assistive Recipe Editing, which performs simultaneous ingredient substitution before generating natural-language steps using the edited ingredients. By decoupling ingredient and step editing, our step generator can explicitly integrate the available ingredients. Experiments on the novel RecipePairs dataset{---}83K pairs of similar recipes where each recipe satisfies one of seven dietary constraints{---}demonstrate that SHARE produces convincing, coherent recipes that are appropriate for a target dietary constraint. We further show through human evaluations and real-world cooking trials that recipes edited by SHARE can be easily followed by home cooks to create appealing dishes.", } @inproceedings{majumder-etal-2019-generating, title = "Generating Personalized Recipes from Historical User Preferences", author = "Majumder, Bodhisattwa Prasad and Li, Shuyang and Ni, Jianmo and McAuley, Julian", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)", month = nov, year = "2019", address = "Hong Kong, China", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/D19-1613", doi = "10.18653/v1/D19-1613", pages = "5976--5982", abstract = "Existing approaches to recipe generation are unable to create recipes for users with culinary preferences but incomplete knowledge of ingredients in specific dishes. We propose a new task of personalized recipe generation to help these users: expanding a name and incomplete ingredient details into complete natural-text instructions aligned with the user{'}s historical preferences. We attend on technique- and recipe-level representations of a user{'}s previously consumed recipes, fusing these {`}user-aware{'} representations in an attention fusion layer to control recipe text generation. Experiments on a new dataset of 180K recipes and 700K interactions show our model{'}s ability to generate plausible and personalized recipes compared to non-personalized baselines.", } ```

deepghs/bangumibase_full

--- license: mit task_categories: - image-classification - zero-shot-image-classification - text-to-image language: - en tags: - art - anime - not-for-all-audiences size_categories: - 1M<n<10M annotations_creators: - no-annotation source_datasets: - bangumibase --- # BangumiBase Full Dataset This is the full dataset of [BangumiBase](https://huggingface.co/BangumiBase). And all the original images are maintained here. # Information ## Images There are 1158841 images in total. The maximum ID of these images is 1650289. Last updated at `2024-04-16 10:11:31 CST`. These are the information of recent 50 images: | id | filename | width | height | type | rating | tags | repository | commit_id | chid | src_filename | created_at | has_face | face_width | face_height | face_min | face_max | resolution | face_max_ratio | face_min_ratio | face_width_ratio | face_height_ratio | face_area_ratio | |--------:|:------------|--------:|---------:|:----------|:----------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------|:-----------------------------------------|-------:|:---------------|-------------:|:-----------|-------------:|--------------:|-----------:|-----------:|-------------:|-----------------:|-----------------:|-------------------:|--------------------:|------------------:| | 1650289 | 1650289.png | 1498 | 1047 | image/png | sensitive | solo open_mouth short_hair blonde_hair 1boy upper_body male_focus outdoors nude sky muscular night barrel | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 48 | 3327.png | 1.71312e+09 | True | 223 | 220 | 220 | 223 | 1080 | 0.206481 | 0.203704 | 0.206481 | 0.203704 | 0.205088 | | 1650281 | 1650281.png | 1875 | 1078 | image/png | sensitive | solo short_hair blonde_hair 1boy upper_body male_focus muscular night muscular_male pectorals bara rope large_pectorals meme anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 48 | 3261.png | 1.71312e+09 | True | 375 | 368 | 368 | 375 | 1080 | 0.347222 | 0.340741 | 0.347222 | 0.340741 | 0.343966 | | 1650263 | 1650263.png | 1901 | 1079 | image/png | sensitive | solo open_mouth short_hair blonde_hair 1boy upper_body male_focus sky from_side muscular night anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 48 | 3193.png | 1.71312e+09 | True | 218 | 271 | 218 | 271 | 1080 | 0.250926 | 0.201852 | 0.201852 | 0.250926 | 0.225055 | | 1650242 | 1650242.png | 1792 | 1067 | image/png | general | solo brown_hair 1boy closed_mouth closed_eyes male_focus outdoors japanese_clothes blurry sweatdrop tree parody bandaid bandaid_on_face anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 47 | 3025.png | 1.71312e+09 | True | 496 | 531 | 496 | 531 | 1080 | 0.491667 | 0.459259 | 0.459259 | 0.491667 | 0.475187 | | 1650205 | 1650205.png | 330 | 609 | image/png | sensitive | solo 1boy holding male_focus weapon outdoors japanese_clothes sword tree muscular night grass katana nature forest dark | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 46 | 2679.png | 1.71312e+09 | True | 43 | 64 | 43 | 64 | 1080 | 0.0592593 | 0.0398148 | 0.0398148 | 0.0592593 | 0.0485736 | | 1650177 | 1650177.png | 1500 | 1073 | image/png | general | solo open_mouth short_hair black_hair 1boy upper_body male_focus indoors black_eyes bandages bandaged_head | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 46 | 1854.png | 1.71312e+09 | True | 247 | 272 | 247 | 272 | 1080 | 0.251852 | 0.228704 | 0.228704 | 0.251852 | 0.239999 | | 1650176 | 1650176.png | 1230 | 1078 | image/png | sensitive | long_hair open_mouth brown_hair 1boy gloves male_focus ponytail multiple_boys japanese_clothes black_gloves 2boys parody | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8778.png | 1.71312e+09 | True | 221 | 228 | 221 | 228 | 1080 | 0.211111 | 0.20463 | 0.20463 | 0.211111 | 0.207845 | | 1650175 | 1650175.png | 1021 | 1080 | image/png | sensitive | solo long_hair brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes black_gloves clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8777.png | 1.71312e+09 | True | 216 | 235 | 216 | 235 | 1080 | 0.217593 | 0.2 | 0.2 | 0.217593 | 0.208611 | | 1650174 | 1650174.png | 1016 | 1080 | image/png | sensitive | solo long_hair brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes scar clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8775.png | 1.71312e+09 | True | 190 | 205 | 190 | 205 | 1080 | 0.189815 | 0.175926 | 0.175926 | 0.189815 | 0.182738 | | 1650173 | 1650173.png | 1172 | 1073 | image/png | sensitive | solo long_hair smile brown_hair 1boy male_focus ponytail teeth japanese_clothes grin night | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8659.png | 1.71312e+09 | True | 225 | 235 | 225 | 235 | 1080 | 0.217593 | 0.208333 | 0.208333 | 0.217593 | 0.212913 | | 1650172 | 1650172.png | 971 | 1068 | image/png | sensitive | solo long_hair smile brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes night scar sharp_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8658.png | 1.71312e+09 | True | 177 | 199 | 177 | 199 | 1080 | 0.184259 | 0.163889 | 0.163889 | 0.184259 | 0.173776 | | 1650171 | 1650171.png | 901 | 1074 | image/png | sensitive | solo long_hair brown_hair 1boy gloves male_focus ponytail teeth japanese_clothes night clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8657.png | 1.71312e+09 | True | 173 | 188 | 173 | 188 | 1080 | 0.174074 | 0.160185 | 0.160185 | 0.174074 | 0.166985 | | 1650170 | 1650170.png | 827 | 1069 | image/png | sensitive | solo long_hair brown_hair 1boy male_focus ponytail teeth japanese_clothes night sharp_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8656.png | 1.71312e+09 | True | 162 | 189 | 162 | 189 | 1080 | 0.175 | 0.15 | 0.15 | 0.175 | 0.162019 | | 1650169 | 1650169.png | 730 | 1071 | image/png | sensitive | solo long_hair blue_eyes brown_hair 1boy male_focus ponytail teeth japanese_clothes clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8655.png | 1.71312e+09 | True | 146 | 189 | 146 | 189 | 1080 | 0.175 | 0.135185 | 0.135185 | 0.175 | 0.15381 | | 1650168 | 1650168.png | 683 | 1075 | image/png | sensitive | solo long_hair blue_eyes brown_hair 1boy male_focus ponytail teeth japanese_clothes clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8654.png | 1.71312e+09 | True | 149 | 190 | 149 | 190 | 1080 | 0.175926 | 0.137963 | 0.137963 | 0.175926 | 0.155792 | | 1650167 | 1650167.png | 620 | 1067 | image/png | sensitive | solo long_hair blue_eyes brown_hair 1boy male_focus ponytail teeth japanese_clothes scar sharp_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8653.png | 1.71312e+09 | True | 145 | 188 | 145 | 188 | 1080 | 0.174074 | 0.134259 | 0.134259 | 0.174074 | 0.152876 | | 1650166 | 1650166.png | 569 | 1069 | image/png | sensitive | solo long_hair brown_hair 1boy male_focus ponytail teeth japanese_clothes scar clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8652.png | 1.71312e+09 | True | 147 | 190 | 147 | 190 | 1080 | 0.175926 | 0.136111 | 0.136111 | 0.175926 | 0.154743 | | 1650165 | 1650165.png | 520 | 1066 | image/png | sensitive | solo long_hair blue_eyes blonde_hair brown_hair 1boy male_focus ponytail teeth japanese_clothes scar clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8651.png | 1.71312e+09 | True | 149 | 185 | 149 | 185 | 1080 | 0.171296 | 0.137963 | 0.137963 | 0.171296 | 0.153729 | | 1650164 | 1650164.png | 474 | 1064 | image/png | sensitive | solo long_hair open_mouth blonde_hair brown_hair 1boy male_focus ponytail japanese_clothes scar | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8650.png | 1.71312e+09 | True | 143 | 187 | 143 | 187 | 1080 | 0.173148 | 0.132407 | 0.132407 | 0.173148 | 0.151414 | | 1650163 | 1650163.png | 413 | 1064 | image/png | sensitive | solo long_hair open_mouth blue_eyes blonde_hair brown_hair 1boy male_focus ponytail japanese_clothes scar | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8649.png | 1.71312e+09 | True | 142 | 184 | 142 | 184 | 1080 | 0.17037 | 0.131481 | 0.131481 | 0.17037 | 0.149668 | | 1650137 | 1650137.png | 1910 | 1080 | image/png | general | solo long_hair blonde_hair 1boy male_focus outdoors sweat teeth parody grass portrait clenched_teeth anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8263.png | 1.71312e+09 | True | 868 | 696 | 696 | 868 | 1080 | 0.803704 | 0.644444 | 0.803704 | 0.644444 | 0.719682 | | 1650130 | 1650130.png | 1916 | 1079 | image/png | general | solo long_hair looking_at_viewer smile brown_hair 1boy male_focus ponytail outdoors teeth japanese_clothes grin scar chain parody | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8252.png | 1.71312e+09 | True | 799 | 739 | 739 | 799 | 1080 | 0.739815 | 0.684259 | 0.739815 | 0.684259 | 0.711495 | | 1650124 | 1650124.png | 1916 | 1080 | image/png | general | solo open_mouth brown_hair 1boy male_focus ponytail teeth makeup parody eyeshadow | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 8219.png | 1.71312e+09 | True | 778 | 729 | 729 | 778 | 1080 | 0.72037 | 0.675 | 0.72037 | 0.675 | 0.697316 | | 1650119 | 1650119.png | 1528 | 1080 | image/png | general | solo 1boy red_eyes grey_hair male_focus indoors scarf profile headband portrait candle ninja purple_scarf anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 2451.png | 1.71312e+09 | True | 449 | 648 | 449 | 648 | 1080 | 0.6 | 0.415741 | 0.415741 | 0.6 | 0.499444 | | 1650118 | 1650118.png | 1915 | 1078 | image/png | sensitive | solo looking_at_viewer smile blonde_hair 1boy red_eyes hat male_focus teeth sky cloud grin facial_mark portrait evil_smile evil_grin | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 2363.png | 1.71312e+09 | True | 663 | 599 | 599 | 663 | 1080 | 0.613889 | 0.55463 | 0.613889 | 0.55463 | 0.583507 | | 1650117 | 1650117.png | 1916 | 1079 | image/png | sensitive | solo looking_at_viewer smile blonde_hair 1boy red_eyes hat male_focus teeth sky cloud grin evil_smile evil_grin | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 45 | 2362.png | 1.71312e+09 | True | 660 | 575 | 575 | 660 | 1080 | 0.611111 | 0.532407 | 0.611111 | 0.532407 | 0.570403 | | 1650115 | 1650115.png | 1915 | 1079 | image/png | general | solo looking_at_viewer short_hair 1boy closed_mouth male_focus indoors facial_hair parody portrait bookshelf monocle | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 7699.png | 1.71312e+09 | True | 836 | 1011 | 836 | 1011 | 1080 | 0.936111 | 0.774074 | 0.774074 | 0.936111 | 0.851246 | | 1650114 | 1650114.png | 1039 | 1080 | image/png | general | short_hair brown_hair black_hair male_focus outdoors multiple_boys sky japanese_clothes 2boys kimono from_behind night bandaid night_sky bandaid_on_face green_kimono anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 7001.png | 1.71312e+09 | True | 139 | 205 | 139 | 205 | 1080 | 0.189815 | 0.128704 | 0.128704 | 0.189815 | 0.156301 | | 1650113 | 1650113.png | 1877 | 1080 | image/png | general | solo open_mouth brown_hair 1boy upper_body male_focus weapon teeth sky japanese_clothes glasses cloud sword kimono parody katana head_out_of_frame haori opaque_glasses | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6625.png | 1.71312e+09 | True | 356 | 304 | 304 | 356 | 1080 | 0.32963 | 0.281481 | 0.32963 | 0.281481 | 0.304606 | | 1650112 | 1650112.png | 1851 | 1080 | image/png | general | solo smile 1boy upper_body male_focus weapon sky japanese_clothes cloud sword kimono katana sheath head_out_of_frame black_kimono haori | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6624.png | 1.71312e+09 | True | 373 | 148 | 148 | 373 | 1080 | 0.34537 | 0.137037 | 0.34537 | 0.137037 | 0.217551 | | 1650111 | 1650111.png | 1912 | 1079 | image/png | general | solo long_hair black_hair 1boy male_focus outdoors teeth dark_skin from_behind night dark-skinned_male clenched_teeth nature forest head_out_of_frame anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6523.png | 1.71312e+09 | True | 588 | 410 | 410 | 588 | 1080 | 0.544444 | 0.37963 | 0.544444 | 0.37963 | 0.454629 | | 1650109 | 1650109.png | 1850 | 1076 | image/png | general | solo shirt black_hair 1boy holding upper_body grey_hair male_focus ponytail weapon teeth multiple_boys sword 2boys holding_weapon muscular holding_sword katana spiked_hair clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6436.png | 1.71312e+09 | True | 261 | 337 | 261 | 337 | 1080 | 0.312037 | 0.241667 | 0.241667 | 0.312037 | 0.274607 | | 1650108 | 1650108.png | 1897 | 1080 | image/png | sensitive | solo 1boy collarbone male_focus teeth japanese_clothes night clenched_teeth nature forest head_out_of_frame anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6423.png | 1.71312e+09 | True | 840 | 608 | 608 | 840 | 1080 | 0.777778 | 0.562963 | 0.777778 | 0.562963 | 0.66171 | | 1650107 | 1650107.png | 1185 | 1078 | image/png | general | solo brown_hair 1boy male_focus weapon outdoors japanese_clothes day sword kimono tree katana sheath haori brown_kimono samurai | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6019.png | 1.71312e+09 | True | 259 | 249 | 249 | 259 | 1080 | 0.239815 | 0.230556 | 0.239815 | 0.230556 | 0.23514 | | 1650106 | 1650106.png | 1345 | 1080 | image/png | general | solo brown_hair 1boy closed_mouth male_focus weapon outdoors japanese_clothes sword kimono tree katana sheath hakama haori samurai | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6018.png | 1.71312e+09 | True | 238 | 244 | 238 | 244 | 1080 | 0.225926 | 0.22037 | 0.22037 | 0.225926 | 0.223131 | | 1650105 | 1650105.png | 709 | 1032 | image/png | general | solo skirt brown_hair 1boy male_focus weapon outdoors sky japanese_clothes day cloud sword kimono katana hakama hakama_skirt haori | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6014.png | 1.71312e+09 | True | 134 | 172 | 134 | 172 | 1080 | 0.159259 | 0.124074 | 0.124074 | 0.159259 | 0.14057 | | 1650104 | 1650104.png | 1547 | 1079 | image/png | general | solo brown_hair 1boy closed_mouth brown_eyes male_focus outdoors sky day cloud tree thick_eyebrows parody portrait style_parody | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 6012.png | 1.71312e+09 | True | 914 | 945 | 914 | 945 | 1080 | 0.875 | 0.846296 | 0.846296 | 0.875 | 0.860528 | | 1650103 | 1650103.png | 1874 | 1079 | image/png | general | solo shirt blonde_hair 1boy yellow_eyes male_focus teeth coat fur_trim thick_eyebrows parody clenched_teeth | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5981.png | 1.71312e+09 | True | 861 | 887 | 861 | 887 | 1080 | 0.821296 | 0.797222 | 0.797222 | 0.821296 | 0.80917 | | 1650102 | 1650102.png | 1919 | 1080 | image/png | general | solo looking_at_viewer open_mouth brown_hair 1boy brown_eyes male_focus outdoors japanese_clothes thick_eyebrows parody portrait close-up style_parody official_style anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5968.png | 1.71312e+09 | True | 1136 | 1068 | 1068 | 1136 | 1080 | 1.05185 | 0.988889 | 1.05185 | 0.988889 | 1.01988 | | 1650101 | 1650101.png | 1909 | 1080 | image/png | general | solo blonde_hair 1boy yellow_eyes male_focus outdoors sky day cloud blurry blue_sky parody close-up sanpaku | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5951.png | 1.71312e+09 | True | 1172 | 1022 | 1022 | 1172 | 1080 | 1.08519 | 0.946296 | 1.08519 | 0.946296 | 1.01336 | | 1650100 | 1650100.png | 1709 | 1079 | image/png | general | solo looking_at_viewer open_mouth brown_hair 1boy brown_eyes male_focus outdoors teeth sky day cloud blue_sky thick_eyebrows parody portrait style_parody official_style anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5949.png | 1.71312e+09 | True | 931 | 1045 | 931 | 1045 | 1080 | 0.967593 | 0.862037 | 0.862037 | 0.967593 | 0.913291 | | 1650099 | 1650099.png | 1893 | 1080 | image/png | general | solo open_mouth short_hair blonde_hair 1boy brown_eyes upper_body male_focus weapon teeth sky japanese_clothes day cloud sword kimono blue_sky parody katana haori | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5947.png | 1.71312e+09 | True | 375 | 387 | 375 | 387 | 1080 | 0.358333 | 0.347222 | 0.347222 | 0.358333 | 0.352734 | | 1650098 | 1650098.png | 1857 | 1080 | image/png | general | solo open_mouth 1boy upper_body male_focus weapon teeth sky japanese_clothes day cloud sword kimono blue_sky parody katana sheath head_out_of_frame haori anime_coloring | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5946.png | 1.71312e+09 | True | 353 | 227 | 227 | 353 | 1080 | 0.326852 | 0.210185 | 0.326852 | 0.210185 | 0.262106 | | 1650097 | 1650097.png | 1913 | 903 | image/png | general | solo short_hair brown_hair 1boy hat brown_eyes male_focus teeth facial_hair thick_eyebrows portrait clenched_teeth close-up stubble straw_hat | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5835.png | 1.71312e+09 | True | 768 | 656 | 656 | 768 | 1080 | 0.711111 | 0.607407 | 0.711111 | 0.607407 | 0.657217 | | 1650095 | 1650095.png | 1915 | 1080 | image/png | general | solo short_hair brown_hair 1boy hat brown_eyes male_focus teeth facial_hair thick_eyebrows portrait clenched_teeth close-up mature_male stubble straw_hat | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5833.png | 1.71312e+09 | True | 765 | 656 | 656 | 765 | 1080 | 0.708333 | 0.607407 | 0.708333 | 0.607407 | 0.655932 | | 1650094 | 1650094.png | 1915 | 1080 | image/png | general | solo smile short_hair brown_hair 1boy hat brown_eyes male_focus teeth facial_hair scar clenched_teeth scar_on_face close-up stubble straw_hat | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5832.png | 1.71312e+09 | True | 824 | 472 | 472 | 824 | 1080 | 0.762963 | 0.437037 | 0.762963 | 0.437037 | 0.577445 | | 1650093 | 1650093.png | 1917 | 1078 | image/png | general | solo smile brown_hair 1boy hat collarbone male_focus teeth japanese_clothes facial_hair clenched_teeth close-up stubble straw_hat head_out_of_frame | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5831.png | 1.71312e+09 | True | 776 | 349 | 349 | 776 | 1080 | 0.718519 | 0.323148 | 0.718519 | 0.323148 | 0.481859 | | 1650092 | 1650092.png | 1357 | 1073 | image/png | sensitive | open_mouth blonde_hair grey_hair male_focus weapon multiple_boys indoors sword 2boys cape facial_hair beard mustache old old_man | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5719.png | 1.71312e+09 | True | 155 | 232 | 155 | 232 | 1080 | 0.214815 | 0.143519 | 0.143519 | 0.214815 | 0.175584 | | 1650091 | 1650091.png | 1769 | 1078 | image/png | general | solo looking_at_viewer short_hair brown_hair 1boy upper_body male_focus japanese_clothes indoors looking_back from_behind fur_trim facial_hair thick_eyebrows stubble | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5697.png | 1.71312e+09 | True | 314 | 387 | 314 | 387 | 1080 | 0.358333 | 0.290741 | 0.290741 | 0.358333 | 0.322773 | | 1650090 | 1650090.png | 791 | 900 | image/png | sensitive | short_hair blonde_hair 1boy male_focus multiple_boys solo_focus indoors looking_back from_behind fur_trim | BangumiBase/rurounikenshin2023 | 651168aec3cb7ba5aae9a3e718cccc12156a524c | 44 | 5659.png | 1.71312e+09 | True | 145 | 99 | 99 | 145 | 1080 | 0.134259 | 0.0916667 | 0.134259 | 0.0916667 | 0.110937 | ## Tags There are 8061 tags in total. These are the top 30 tags (1235 tags in total) of type `character`: | tag | type | count | |:---------------------------------|:----------|--------:| | oumae_kumiko | character | 6518 | | misaka_mikoto | character | 5199 | | kinomoto_sakura | character | 4578 | | hirasawa_yui | character | 4321 | | sakata_gintoki | character | 4094 | | kirito | character | 3975 | | kamijou_touma | character | 3708 | | midoriya_izuku | character | 3589 | | natsuki_subaru | character | 3512 | | tainaka_ritsu | character | 3484 | | akiyama_mio | character | 3418 | | kurosaki_ichigo | character | 3350 | | nakano_azusa | character | 3245 | | lucy_heartfilia | character | 3019 | | monkey_d._luffy | character | 2980 | | kotobuki_tsumugi | character | 2956 | | shirai_kuroko | character | 2825 | | uzumaki_naruto | character | 2755 | | satou_kazuma | character | 2686 | | yoshida_yuuko_(machikado_mazoku) | character | 2426 | | kousaka_reina | character | 2291 | | araragi_koyomi | character | 2235 | | kamado_tanjirou | character | 2203 | | emiya_shirou | character | 2075 | | takagi-san | character | 2056 | | kazanari_tsubasa | character | 2017 | | gon_freecss | character | 1990 | | sora_harewataru | character | 1951 | | kafuu_chino | character | 1861 | | asirpa | character | 1835 | These are the top 30 tags (6826 tags in total) of type `general`: | tag | type | count | |:------------------|:--------|--------:| | solo | general | 866519 | | 1girl | general | 617253 | | 1boy | general | 533345 | | male_focus | general | 488199 | | short_hair | general | 472448 | | long_hair | general | 388260 | | black_hair | general | 383584 | | shirt | general | 363654 | | brown_hair | general | 340743 | | upper_body | general | 308224 | | closed_mouth | general | 288325 | | open_mouth | general | 271939 | | looking_at_viewer | general | 267001 | | smile | general | 252195 | | school_uniform | general | 215854 | | brown_eyes | general | 212886 | | blonde_hair | general | 184176 | | parody | general | 173041 | | jacket | general | 172627 | | outdoors | general | 172395 | | indoors | general | 169257 | | white_shirt | general | 164958 | | blush | general | 154054 | | long_sleeves | general | 152847 | | anime_coloring | general | 152375 | | blue_eyes | general | 145734 | | solo_focus | general | 143894 | | closed_eyes | general | 130706 | | holding | general | 127717 | | portrait | general | 127575 |

aditijha/instruct_v1_2k

--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 1475295.9366042826 num_examples: 2000 download_size: 788725 dataset_size: 1475295.9366042826 --- # Dataset Card for "instruct_v1_2k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

phamtungthuy/cafedanluat2

--- dataset_info: features: - name: content dtype: string - name: question dtype: string - name: relevant_laws list: - name: law_id dtype: string - name: text dtype: string - name: split dtype: string - name: id dtype: string splits: - name: train num_bytes: 27357307 num_examples: 6616 download_size: 12227490 dataset_size: 27357307 configs: - config_name: default data_files: - split: train path: data/train-* ---

AdapterOcean/med_alpaca_standardized_cluster_7

--- dataset_info: features: - name: text dtype: string - name: conversation_id dtype: int64 - name: embedding sequence: float64 - name: cluster dtype: int64 splits: - name: train num_bytes: 73841362 num_examples: 7528 download_size: 21771105 dataset_size: 73841362 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_7" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Ssunbell/SROIE_layoutlmv2_sequence

--- dataset_info: features: - name: guid sequence: string - name: words sequence: string - name: labels sequence: int64 - name: boxes sequence: sequence: int64 - name: actual_bboxes sequence: sequence: int64 - name: file_name dtype: string - name: image sequence: sequence: sequence: uint8 splits: - name: train num_bytes: 98185080 num_examples: 594 - name: val num_bytes: 5264337 num_examples: 32 - name: test num_bytes: 57252300 num_examples: 347 download_size: 67438968 dataset_size: 160701717 --- # Dataset Card for "SROIE_layoutlmv2_sequence" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Mike0307/MNIST-M

--- license: mit dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': '0' '1': '1' '2': '2' '3': '3' '4': '4' '5': '5' '6': '6' '7': '7' '8': '8' '9': '9' splits: - name: train num_bytes: 119131988.027 num_examples: 59001 - name: test num_bytes: 18049625.166 num_examples: 9001 download_size: 143468539 dataset_size: 137181613.193 --- ## Train Example 👉[Domain-Adversarial-Neural-Network](https://github.com/yeyuting0307/Domain-Adversarial-Neural-Network)

version-control/the-stack-ds-lib-50k

--- dataset_info: features: - name: repo_name dtype: string - name: hexsha sequence: string - name: file_path sequence: string - name: code sequence: string - name: apis sequence: sequence: string splits: - name: train num_bytes: 616797241 num_examples: 40990 download_size: 221909836 dataset_size: 616797241 configs: - config_name: default data_files: - split: train path: data/train-* ---

CyberHarem/asagumo_kantaicollection

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of asagumo/朝雲 (Kantai Collection) This is the dataset of asagumo/朝雲 (Kantai Collection), containing 404 images and their tags. The core tags of this character are `brown_hair, long_hair, twintails, hair_ribbon, ribbon, grey_eyes`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 404 | 314.31 MiB | [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 404 | 215.37 MiB | [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 856 | 433.91 MiB | [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 404 | 293.49 MiB | [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 856 | 553.79 MiB | [Download](https://huggingface.co/datasets/CyberHarem/asagumo_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/asagumo_kantaicollection', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 7 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, solo, white_shirt, grey_jacket, white_headband, buttons, grey_skirt, long_sleeves, pleated_skirt, simple_background, blue_necktie, closed_mouth, ponytail, white_background, collared_shirt, cowboy_shot, looking_at_viewer, official_alternate_costume, school_uniform | | 1 | 17 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, grey_skirt, pleated_skirt, solo, white_shirt, blue_ascot, short_sleeves, suspender_skirt, arm_warmers, looking_at_viewer, simple_background, white_background, cowboy_shot, twitter_username, collared_shirt, black_thighhighs, school_uniform, smile | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, arm_warmers, ascot, black_thighhighs, looking_at_viewer, pleated_skirt, school_uniform, solo, suspenders, blush, grey_skirt, white_shirt, sitting, smile | | 3 | 11 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | 1girl, looking_at_viewer, solo, cowboy_shot, blue_bikini, small_breasts, white_background, flat_chest, simple_background, blue_sky, blush, cloud, day, outdoors, side-tie_bikini_bottom, standing, twitter_username | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | white_shirt | grey_jacket | white_headband | buttons | grey_skirt | long_sleeves | pleated_skirt | simple_background | blue_necktie | closed_mouth | ponytail | white_background | collared_shirt | cowboy_shot | looking_at_viewer | official_alternate_costume | school_uniform | blue_ascot | short_sleeves | suspender_skirt | arm_warmers | twitter_username | black_thighhighs | smile | ascot | suspenders | blush | sitting | blue_bikini | small_breasts | flat_chest | blue_sky | cloud | day | outdoors | side-tie_bikini_bottom | standing | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------------|:--------------|:-----------------|:----------|:-------------|:---------------|:----------------|:--------------------|:---------------|:---------------|:-----------|:-------------------|:-----------------|:--------------|:--------------------|:-----------------------------|:-----------------|:-------------|:----------------|:------------------|:--------------|:-------------------|:-------------------|:--------|:--------|:-------------|:--------|:----------|:--------------|:----------------|:-------------|:-----------|:--------|:------|:-----------|:-------------------------|:-----------| | 0 | 7 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | 1 | 17 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | X | X | X | | | | X | | X | X | | | | X | X | X | X | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | X | X | | | | X | | X | | | | | | | | X | | X | | | | X | | X | X | X | X | X | X | | | | | | | | | | | 3 | 11 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | X | X | | | | | | | | X | | | | X | | X | X | | | | | | | X | | | | | X | | X | X | X | X | X | X | X | X | X |

kkucheria/kkquickdataset

--- license: llama2 ---

ddtraveller/wisdom

--- license: mit task_categories: - table-question-answering language: - en size_categories: - 1K<n<10K ---

b583x2/test

--- license: apache-2.0 ---

Ninatacataca/dataset

--- license: openrail ---

Javtor/rock-paper-scissors

--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: 0: paper 1: rock 2: scissors splits: - name: test num_bytes: 29457688.0 num_examples: 372 - name: train num_bytes: 196585089.6 num_examples: 2520 download_size: 229783612 dataset_size: 226042777.6 --- # Dataset Card for "rock-paper-scissors" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

minoruskore/wlkjokj3454sd45sc45

--- license: other dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: user_id dtype: int64 - name: name dtype: string - name: anime_id dtype: int64 - name: anime dtype: string - name: rating dtype: int64 splits: - name: train num_bytes: 1386784355 num_examples: 19460153 - name: test num_bytes: 354541207 num_examples: 4865038 - name: train100k num_bytes: 5716739 num_examples: 80000 - name: test100k num_bytes: 1453191 num_examples: 20000 - name: train500k num_bytes: 28547903 num_examples: 400000 - name: test500k num_bytes: 7235060 num_examples: 100000 - name: train1kk num_bytes: 57023319 num_examples: 800000 - name: test1kk num_bytes: 14562005 num_examples: 200000 download_size: 832651093 dataset_size: 1855863779 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: train100k path: data/train100k-* - split: test100k path: data/test100k-* - split: train500k path: data/train500k-* - split: test500k path: data/test500k-* - split: train1kk path: data/train1kk-* - split: test1kk path: data/test1kk-* ---