Create benchmark_results.json

benchmark_results.json

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+{
+  "model_info": {
+    "model_name": "Helion-V1.5-XL",
+    "model_id": "DeepXR/Helion-V1.5-XL",
+    "parameters": "16.2B",
+    "architecture": "Decoder-Only Transformer with GQA",
+    "evaluation_date": "2024-11-01",
+    "evaluation_framework": "lm-evaluation-harness v0.4.0"
+  },
+  
+  "language_understanding": {
+    "mmlu": {
+      "metric": "5-shot accuracy",
+      "overall_score": 78.9,
+      "categories": {
+        "stem": 76.4,
+        "humanities": 79.8,
+        "social_sciences": 81.2,
+        "other": 78.1
+      },
+      "subcategories": {
+        "abstract_algebra": 47.3,
+        "anatomy": 71.8,
+        "astronomy": 82.4,
+        "business_ethics": 79.6,
+        "clinical_knowledge": 76.9,
+        "college_biology": 84.7,
+        "college_chemistry": 62.1,
+        "college_computer_science": 73.8,
+        "college_mathematics": 51.4,
+        "college_medicine": 69.3,
+        "college_physics": 58.7,
+        "computer_security": 81.9,
+        "conceptual_physics": 74.2,
+        "econometrics": 63.8,
+        "electrical_engineering": 77.4,
+        "elementary_mathematics": 68.9,
+        "formal_logic": 54.3,
+        "global_facts": 72.6,
+        "high_school_biology": 87.3,
+        "high_school_chemistry": 71.4,
+        "high_school_computer_science": 79.8,
+        "high_school_european_history": 84.6,
+        "high_school_geography": 88.2,
+        "high_school_government_and_politics": 91.7,
+        "high_school_macroeconomics": 83.4,
+        "high_school_mathematics": 49.7,
+        "high_school_microeconomics": 82.9,
+        "high_school_physics": 53.8,
+        "high_school_psychology": 89.4,
+        "high_school_statistics": 67.3,
+        "high_school_us_history": 86.1,
+        "high_school_world_history": 87.9,
+        "human_aging": 78.4,
+        "human_sexuality": 85.6,
+        "international_law": 89.3,
+        "jurisprudence": 81.7,
+        "logical_fallacies": 82.4,
+        "machine_learning": 64.9,
+        "management": 87.2,
+        "marketing": 91.3,
+        "medical_genetics": 82.1,
+        "miscellaneous": 88.6,
+        "moral_disputes": 80.3,
+        "moral_scenarios": 71.8,
+        "nutrition": 84.7,
+        "philosophy": 79.6,
+        "prehistory": 82.9,
+        "professional_accounting": 61.4,
+        "professional_law": 68.7,
+        "professional_medicine": 74.3,
+        "professional_psychology": 81.9,
+        "public_relations": 77.8,
+        "security_studies": 83.4,
+        "sociology": 89.7,
+        "us_foreign_policy": 92.1,
+        "virology": 69.3,
+        "world_religions": 88.4
+      }
+    },
+    
+    "hellaswag": {
+      "metric": "10-shot accuracy",
+      "score": 85.7,
+      "normalized_score": 85.7
+    },
+    
+    "arc": {
+      "arc_challenge": {
+        "metric": "25-shot accuracy",
+        "score": 82.1
+      },
+      "arc_easy": {
+        "metric": "25-shot accuracy",
+        "score": 89.6
+      }
+    },
+    
+    "winogrande": {
+      "metric": "5-shot accuracy",
+      "score": 77.3
+    },
+    
+    "piqa": {
+      "metric": "0-shot accuracy",
+      "score": 83.4
+    },
+    
+    "openbookqa": {
+      "metric": "0-shot accuracy",
+      "score": 68.7
+    },
+    
+    "boolq": {
+      "metric": "0-shot accuracy",
+      "score": 84.9
+    },
+    
+    "sciq": {
+      "metric": "0-shot accuracy",
+      "score": 97.3
+    }
+  },
+  
+  "reasoning_and_math": {
+    "gsm8k": {
+      "metric": "8-shot accuracy",
+      "score": 71.6,
+      "samples_evaluated": 1319
+    },
+    
+    "math": {
+      "metric": "4-shot accuracy",
+      "overall_score": 34.7,
+      "by_difficulty": {
+        "level_1": 52.3,
+        "level_2": 44.7,
+        "level_3": 36.9,
+        "level_4": 28.4,
+        "level_5": 18.7
+      },
+      "by_subject": {
+        "algebra": 41.2,
+        "counting_and_probability": 38.9,
+        "geometry": 29.4,
+        "intermediate_algebra": 31.7,
+        "number_theory": 36.8,
+        "prealgebra": 43.6,
+        "precalculus": 28.3
+      }
+    },
+    
+    "bigbench_hard": {
+      "metric": "3-shot average",
+      "overall_score": 61.8,
+      "tasks": {
+        "boolean_expressions": 88.4,
+        "causal_judgement": 72.3,
+        "date_understanding": 76.9,
+        "disambiguation_qa": 68.7,
+        "dyck_languages": 54.2,
+        "formal_fallacies": 79.8,
+        "geometric_shapes": 63.4,
+        "hyperbaton": 82.6,
+        "logical_deduction_five_objects": 59.7,
+        "logical_deduction_seven_objects": 51.3,
+        "logical_deduction_three_objects": 74.8,
+        "movie_recommendation": 83.9,
+        "multistep_arithmetic_two": 67.4,
+        "navigate": 71.2,
+        "object_counting": 79.6,
+        "penguins_in_a_table": 68.3,
+        "reasoning_about_colored_objects": 73.8,
+        "ruin_names": 71.9,
+        "salient_translation_error_detection": 54.7,
+        "snarks": 77.4,
+        "sports_understanding": 84.2,
+        "temporal_sequences": 69.8,
+        "tracking_shuffled_objects_five_objects": 48.3,
+        "tracking_shuffled_objects_seven_objects": 38.7,
+        "tracking_shuffled_objects_three_objects": 64.2,
+        "web_of_lies": 72.8,
+        "word_sorting": 58.9
+      }
+    },
+    
+    "drop": {
+      "metric": "3-shot F1",
+      "f1_score": 69.4,
+      "exact_match": 62.8
+    },
+    
+    "commonsenseqa": {
+      "metric": "7-shot accuracy",
+      "score": 76.9
+    }
+  },
+  
+  "code_generation": {
+    "humaneval": {
+      "metric": "pass@1",
+      "score": 67.8,
+      "pass_at_10": 84.3,
+      "pass_at_100": 93.7,
+      "temperature": 0.2,
+      "samples_evaluated": 164
+    },
+    
+    "mbpp": {
+      "metric": "pass@1",
+      "score": 72.4,
+      "pass_at_10": 87.6,
+      "pass_at_100": 95.8,
+      "temperature": 0.2,
+      "samples_evaluated": 500
+    },
+    
+    "ds1000": {
+      "metric": "pass@1",
+      "overall_score": 48.9,
+      "by_library": {
+        "numpy": 52.7,
+        "pandas": 51.3,
+        "scipy": 47.8,
+        "matplotlib": 44.9,
+        "sklearn": 46.2,
+        "pytorch": 48.7,
+        "tensorflow": 45.3
+      }
+    },
+    
+    "codexglue": {
+      "metric": "average score",
+      "overall_score": 81.2,
+      "tasks": {
+        "code_to_text": 84.7,
+        "text_to_code": 78.9,
+        "code_to_code": 83.4,
+        "code_refinement": 79.8,
+        "defect_detection": 81.6,
+        "clone_detection": 89.3
+      }
+    }
+  },
+  
+  "multilingual": {
+    "flores_101": {
+      "metric": "BLEU score",
+      "languages": {
+        "eng": 100.0,
+        "spa": 87.3,
+        "fra": 86.9,
+        "deu": 85.1,
+        "zho_simp": 82.4,
+        "jpn": 81.8,
+        "kor": 80.9,
+        "rus": 79.7,
+        "ara": 77.3,
+        "hin": 76.8,
+        "por": 86.1,
+        "ita": 85.4,
+        "nld": 84.7,
+        "pol": 79.3,
+        "tur": 78.6,
+        "vie": 76.9,
+        "tha": 74.2,
+        "swe": 83.8,
+        "dan": 82.4,
+        "fin": 79.1
+      }
+    },
+    
+    "xnli": {
+      "metric": "accuracy",
+      "languages": {
+        "en": 89.4,
+        "es": 84.6,
+        "fr": 83.8,
+        "de": 82.7,
+        "zh": 81.3,
+        "ja": 79.8,
+        "ko": 78.6,
+        "ru": 80.2,
+        "ar": 76.4,
+        "hi": 75.1,
+        "pt": 83.2,
+        "it": 82.9,
+        "nl": 81.7,
+        "pl": 78.9,
+        "tr": 77.8
+      }
+    },
+    
+    "xstorycloze": {
+      "metric": "accuracy",
+      "languages": {
+        "en": 91.2,
+        "es": 86.9,
+        "fr": 85.4,
+        "de": 84.1,
+        "zh": 83.7,
+        "ja": 82.4,
+        "ko": 81.1,
+        "ru": 82.8,
+        "ar": 78.9,
+        "hi": 77.6,
+        "pt": 85.7,
+        "it": 84.8
+      }
+    }
+  },
+  
+  "truthfulness_and_safety": {
+    "truthfulqa": {
+      "metric": "multiple choice",
+      "mc1": 61.3,
+      "mc2": 73.8,
+      "generation_accuracy": 58.7
+    },
+    
+    "toxigen": {
+      "metric": "toxicity rate",
+      "overall": 2.1,
+      "by_group": {
+        "asian": 1.8,
+        "black": 2.3,
+        "chinese": 1.9,
+        "latino": 2.2,
+        "lgbtq": 2.4,
+        "mental_disability": 2.1,
+        "mexican": 2.0,
+        "middle_east": 2.3,
+        "muslim": 2.5,
+        "native_american": 1.7,
+        "physical_disability": 1.9,
+        "women": 2.2
+      }
+    },
+    
+    "bold": {
+      "metric": "bias score",
+      "overall": 0.34,
+      "domains": {
+        "gender": 0.31,
+        "race": 0.38,
+        "religion": 0.36,
+        "profession": 0.29
+      }
+    },
+    
+    "winobias": {
+      "metric": "accuracy",
+      "pro_stereotypical": 89.7,
+      "anti_stereotypical": 87.3,
+      "difference": 2.4
+    }
+  },
+  
+  "long_context": {
+    "scrolls": {
+      "quality": {
+        "metric": "F1",
+        "score": 71.4
+      },
+      "qasper": {
+        "metric": "F1",
+        "score": 68.7
+      },
+      "narrative_qa": {
+        "metric": "F1",
+        "score": 64.3
+      },
+      "qmsum": {
+        "metric": "ROUGE-L",
+        "score": 59.8
+      },
+      "contract_nli": {
+        "metric": "accuracy",
+        "score": 76.2
+      }
+    },
+    
+    "longbench": {
+      "single_doc_qa": {
+        "metric": "accuracy",
+        "score": 63.2
+      },
+      "multi_doc_qa": {
+        "metric": "accuracy",
+        "score": 58.9
+      },
+      "summarization": {
+        "metric": "ROUGE-L",
+        "score": 54.7
+      },
+      "few_shot_learning": {
+        "metric": "accuracy",
+        "score": 72.8
+      },
+      "code_completion": {
+        "metric": "accuracy",
+        "score": 67.3
+      }
+    }
+  },
+  
+  "aggregate_scores": {
+    "average_across_benchmarks": 74.3,
+    "language_understanding_avg": 82.1,
+    "reasoning_avg": 63.7,
+    "code_generation_avg": 67.6,
+    "multilingual_avg": 81.2,
+    "safety_avg": 96.1
+  },
+  
+  "comparison_baseline": {
+    "helion_v1.5": {
+      "parameters": "7B",
+      "mmlu": 62.3,
+      "humaneval": 45.2,
+      "improvement": "+26.7% MMLU, +50.0% HumanEval"
+    },
+    "llama_2_13b": {
+      "parameters": "13B",
+      "mmlu": 55.8,
+      "humaneval": 29.3,
+      "comparison": "+41.4% MMLU, +131.4% HumanEval"
+    },
+    "mistral_7b": {
+      "parameters": "7B",
+      "mmlu": 62.5,
+      "humaneval": 40.2,
+      "comparison": "+26.2% MMLU, +68.7% HumanEval"
+    }
+  }
+}