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automated-research-group/llama2_7b_chat-boolq-results

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Hugging Face2023-12-02 更新2024-03-04 收录
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--- dataset_info: - config_name: '{''do_sample''=False, ''beams''=10}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 217480 num_examples: 3270 download_size: 105062 dataset_size: 217480 - config_name: '{''do_sample''=False, ''beams''=1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 503592 num_examples: 3270 download_size: 265378 dataset_size: 503592 - config_name: '{''do_sample''=False, ''beams''=5}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 217480 num_examples: 3270 download_size: 105062 dataset_size: 217480 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218096 num_examples: 3270 download_size: 105150 dataset_size: 218096 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218191 num_examples: 3270 download_size: 105558 dataset_size: 218191 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217965 num_examples: 3270 download_size: 105096 dataset_size: 217965 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218285 num_examples: 3270 download_size: 105322 dataset_size: 218285 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218025 num_examples: 3270 download_size: 105120 dataset_size: 218025 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218336 num_examples: 3270 download_size: 105622 dataset_size: 218336 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 216642 num_examples: 3270 download_size: 105050 dataset_size: 216642 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 216562 num_examples: 3270 download_size: 105487 dataset_size: 216562 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217182 num_examples: 3270 download_size: 104940 dataset_size: 217182 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217123 num_examples: 3270 download_size: 105570 dataset_size: 217123 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217545 num_examples: 3270 download_size: 105061 dataset_size: 217545 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 219782 num_examples: 3270 download_size: 107601 dataset_size: 219782 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105165 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218152 num_examples: 3270 download_size: 105161 dataset_size: 218152 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218137 num_examples: 3270 download_size: 105142 dataset_size: 218137 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218156 num_examples: 3270 download_size: 105161 dataset_size: 218156 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218150 num_examples: 3270 download_size: 105158 dataset_size: 218150 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 214912 num_examples: 3270 download_size: 104059 dataset_size: 214912 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 229014 num_examples: 3270 download_size: 115914 dataset_size: 229014 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217453 num_examples: 3270 download_size: 105699 dataset_size: 217453 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 233550 num_examples: 3270 download_size: 120956 dataset_size: 233550 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217074 num_examples: 3270 download_size: 105063 dataset_size: 217074 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 228714 num_examples: 3270 download_size: 117246 dataset_size: 228714 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218151 num_examples: 3270 download_size: 105142 dataset_size: 218151 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218152 num_examples: 3270 download_size: 105165 dataset_size: 218152 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218147 num_examples: 3270 download_size: 105150 dataset_size: 218147 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218173 num_examples: 3270 download_size: 105449 dataset_size: 218173 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217974 num_examples: 3270 download_size: 105119 dataset_size: 217974 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 216615 num_examples: 3270 download_size: 104953 dataset_size: 216615 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218087 num_examples: 3270 download_size: 105124 dataset_size: 218087 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217401 num_examples: 3270 download_size: 105177 dataset_size: 217401 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218037 num_examples: 3270 download_size: 105301 dataset_size: 218037 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 220330 num_examples: 3270 download_size: 107206 dataset_size: 220330 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217500 num_examples: 3270 download_size: 105181 dataset_size: 217500 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 219606 num_examples: 3270 download_size: 106880 dataset_size: 219606 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 216996 num_examples: 3270 download_size: 104798 dataset_size: 216996 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 216260 num_examples: 3270 download_size: 105790 dataset_size: 216260 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218142 num_examples: 3270 download_size: 105142 dataset_size: 218142 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218142 num_examples: 3270 download_size: 105142 dataset_size: 218142 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218142 num_examples: 3270 download_size: 105142 dataset_size: 218142 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218151 num_examples: 3270 download_size: 105142 dataset_size: 218151 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218137 num_examples: 3270 download_size: 105142 dataset_size: 218137 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105165 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218148 num_examples: 3270 download_size: 105148 dataset_size: 218148 - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}' features: - name: id dtype: string - name: prediction dtype: string - name: bool_accuracy dtype: bool splits: - name: train num_bytes: 218146 num_examples: 3270 download_size: 105142 dataset_size: 218146 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 217979 num_examples: 3270 download_size: 105610 dataset_size: 217979 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 216783 num_examples: 3270 download_size: 105217 dataset_size: 216783 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 235031 num_examples: 3270 download_size: 122186 dataset_size: 235031 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 218161 num_examples: 3270 download_size: 106034 dataset_size: 218161 - 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: bool_accuracy dtype: bool splits: - name: train num_bytes: 231418 num_examples: 3270 download_size: 118724 dataset_size: 231418 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''=0.9, ''top_k''=100, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=1, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}/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''=1.0, ''top_k''=100, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=10, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}/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''=0.9, ''top_k''=100, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=100, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=1000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.9, ''top_k''=10000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=100, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=1000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=0.95, ''top_k''=10000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=100, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=1000, ''top_p''=0.2}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.05}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.1}/train-*' - config_name: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}' data_files: - split: train path: '{''do_sample''=True, ''beams''=5, ''temperature''=1.0, ''top_k''=10000, ''top_p''=0.2}/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''=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-*' --- # Dataset Card for "llama2_7b_chat-boolq-results" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
提供机构：
automated-research-group
原始信息汇总

数据集概述

数据集配置

配置1

  • 配置名称: {do_sample=False, beams=10}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 217480，样本数为 3270
  • 下载大小: 105062
  • 数据集大小: 217480

配置2

  • 配置名称: {do_sample=False, beams=1}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 503592，样本数为 3270
  • 下载大小: 265378
  • 数据集大小: 503592

配置3

  • 配置名称: {do_sample=False, beams=5}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 217480，样本数为 3270
  • 下载大小: 105062
  • 数据集大小: 217480

配置4

  • 配置名称: {do_sample=True, beams=1, temperature=0.05, top_k=100, top_p=0.5}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218096，样本数为 3270
  • 下载大小: 105150
  • 数据集大小: 218096

配置5

  • 配置名称: {do_sample=True, beams=1, temperature=0.05, top_k=100, top_p=1.0}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218191，样本数为 3270
  • 下载大小: 105558
  • 数据集大小: 218191

配置6

  • 配置名称: {do_sample=True, beams=1, temperature=0.05, top_k=1000, top_p=0.5}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 217965，样本数为 3270
  • 下载大小: 105096
  • 数据集大小: 217965

配置7

  • 配置名称: {do_sample=True, beams=1, temperature=0.05, top_k=1000, top_p=1.0}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218285，样本数为 3270
  • 下载大小: 105322
  • 数据集大小: 218285

配置8

  • 配置名称: {do_sample=True, beams=1, temperature=0.05, top_k=10000, top_p=0.5}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218025，样本数为 3270
  • 下载大小: 105120
  • 数据集大小: 218025

配置9

  • 配置名称: {do_sample=True, beams=1, temperature=0.05, top_k=10000, top_p=1.0}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218336，样本数为 3270
  • 下载大小: 105622
  • 数据集大小: 218336

配置10

  • 配置名称: {do_sample=True, beams=1, temperature=0.55, top_k=100, top_p=0.5}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 216642，样本数为 3270
  • 下载大小: 105050
  • 数据集大小: 216642

配置11

  • 配置名称: {do_sample=True, beams=1, temperature=0.55, top_k=100, top_p=1.0}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 216562，样本数为 3270
  • 下载大小: 105487
  • 数据集大小: 216562

配置12

  • 配置名称: {do_sample=True, beams=1, temperature=0.55, top_k=1000, top_p=0.5}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 217182，样本数为 3270
  • 下载大小: 104940
  • 数据集大小: 217182

配置13

  • 配置名称: {do_sample=True, beams=1, temperature=0.55, top_k=1000, top_p=1.0}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 217123，样本数为 3270
  • 下载大小: 105570
  • 数据集大小: 217123

配置14

  • 配置名称: {do_sample=True, beams=1, temperature=0.55, top_k=10000, top_p=0.5}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 217545，样本数为 3270
  • 下载大小: 105061
  • 数据集大小: 217545

配置15

  • 配置名称: {do_sample=True, beams=1, temperature=0.55, top_k=10000, top_p=1.0}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 219782，样本数为 3270
  • 下载大小: 107601
  • 数据集大小: 219782

配置16

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=100, top_p=0.05}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置17

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=100, top_p=0.1}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置18

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=100, top_p=0.2}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置19

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=1000, top_p=0.05}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置20

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=1000, top_p=0.1}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置21

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=1000, top_p=0.2}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置22

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=10000, top_p=0.05}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置23

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=10000, top_p=0.1}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置24

  • 配置名称: {do_sample=True, beams=1, temperature=0.9, top_k=10000, top_p=0.2}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置25

  • 配置名称: {do_sample=True, beams=1, temperature=0.95, top_k=100, top_p=0.05}
  • 特征:
    • id: 类型为 string
    • prediction: 类型为 string
    • bool_accuracy: 类型为 bool
  • 分割:
    • train: 字节数为 218148，样本数为 3270
  • 下载大小: 105148
  • 数据集大小: 218148

配置26

  • 配置名称: {do_sample=True, beams=1, temperature=0.95, top_k=100, top_p=0.1}
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