automated-research-group/llama2_7b_chat-boolq-results
收藏资源简介:
--- 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)
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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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stringprediction: 类型为stringbool_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}



