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Model: sethuiyer/Qwen2.5-7B-Anvita
Source: Original Platform

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PERSONAL_BENCHMARK.md

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+## **Anvita’s Performance Summary**
+
+| **#** | **Problem**                                                          | **Difficulty**    | **Topic**                                                | **Score** |
+|-------|-----------------------------------------------------------------------|-------------------|----------------------------------------------------------|-----------|
+| 1     | Stokes' Theorem Wind Problem                                          | Hard              | Vector calculus and wind flow analysis                   | 75/100    |
+| 2     | Graph Theory: Path Uniqueness Problem                                 | Medium            | Graph theory and path uniqueness                         | 70/100    |
+| 3     | Quantum Optics: Entanglement and Bell Inequality                      | Challenging       | Quantum mechanics and probability theory                 | 72/100    |
+| 4     | Indian Penal Code: Hit-and-Run Case Analysis                          | Medium            | Legal reasoning and IPC sections                         | 77/100    |
+| 5     | Chinese National Olympiad: Complex Sequence Problem                   | Expert            | Alternating sequences and algebraic reasoning            | 65/100    |
+| 6     | Uniform Distribution: Upper Bound Estimation with Time Constraint     | Hard              | Distribution parameter estimation                        | 86/100    |
+| 7     | Table Tennis Scheduling Problem                                       | Very Hard         | Combinatorics and scheduling                             | 65/100    |
+| 8     | Longest Common Substring (Alaska vs. Skating)                         | Medium            | Dynamic programming and string matching                  | 80/100    |
+| 9     | Murder Mystery: Deserted Island Scenario (1st Attempt)                | Hard              | Logical deduction and creative problem-solving           | 72/100    |
+| 10    | Simple Decimal Comparison: 9.12 vs. 9.9                               | Easy              | Numerical comparison and precision                       | 98/100    |
+| 11    | Chinese National Olympiad: Graph Game Scheduling (2nd Attempt)        | Expert            | Graph theory and combinatorial construction              | 65/100    |
+| 12    | Murder Mystery: Locked House, No Footprints (2nd Attempt)             | Hard              | Environmental reasoning and murder deduction             | 70/100    |
+| 13    | Mathematical Puzzle: Widget Production Optimization                   | Medium            | Linear programming and optimization                      | 76/100    |
+| 14    | Programming Challenge: C++ Pointer Manipulation                       | Medium            | Low-level programming in C++                             | 75/100    |
+| 15    | Scientific Problem: Statistical Mechanics of a Gas                    | Hard              | Thermodynamics and probability                           | 73/100    |
+| 16    | Creative Writing Task: Dark Fantasy Narrative Generation              | Easy              | Fictional storytelling                                   | 90/100    |
+| 17    | Symbolic Reasoning Puzzle: Abstract Cipher Interpretation             | Challenging       | Symbolic reasoning and pattern recognition               | 67/100    |
+| 18    | Medical Diagnosis Task: Symptom Analysis for Iron Deficiency          | Medium            | Clinical reasoning and diagnosis                         | 83/100    |
+| 19    | Murder Mystery: Heavy Fog, No Entry Marks                             | Hard              | Environmental conditions and scenario-building           | 75/100    |
+| 20    | Mathematical Problem: Regular Polygon Permutations and Triangle Types| Expert            | Geometry and combinatorial permutations                  | 60/100    |
+| 21    | Latin Cryptic Poem: Hidden Delight with "Burger" Answer (1st Attempt) | Hard              | Cryptic puzzles, language interpretation                 | 70/100    |
+| 22    | English Cryptic Poem: Cheeseburger Riddle (Correct Answer)            | Medium            | Cryptic puzzles, logical deduction                       | 100/100   |
+| 23    | Topsy-Turvy Puzzle: Preposterous (After Hint)                         | Expert            | Wordplay, abstract reasoning                             | 100/100   |
+| 24    | Cryptic Poem: Feathered Riddle with "Duck" Answer                     | Hard              | Symbolic reasoning, animal behavior                      | 87/100    |
+| 25    | AI Cryptic Puzzle: ChatGPT Riddle (Correct Answer)                    | Hard              | AI, abstract reasoning, language interpretation          | 96/100    |
+| 26    | Medium-Level Riddle: Intended Answer "Domestic" (Solved as Language)  | Medium            | Abstract reasoning, interpretation                       | 100/100   |
+| 27    | Cipher Puzzle: Air → BJS; Can → DBO (Correct Answer)                  | Easy              | Cryptography, Caesar shift                               | 95/100    |
+| 28    | Complex Cipher Puzzle: Vigenère Cipher with "KEY"                     | Challenging       | Cryptography, advanced decryption                        | 100/100   |
+| 29    | Anthropology Basic Question: What is Anthropology?                    | Easy              | Social sciences, anthropology                            | 100/100   |
+| 30    | Expert Question on Harappan Civilization                             | Expert            | Ancient history and archaeology                          | 98/100    |
+| 31    | Latin Ad for a Solar Toothbrush                                       | Hard              | Advertising, language creativity                         | 95/100    |
+| 32    | Sanskrit Ad for a Solar Toothbrush                                    | Hard              | Advertising, language creativity                         | 95/100    |
+| 33    | Japanese Haiku on Mountains                                           | Medium            | Poetry, Japanese language                                | 100/100   |                                                     | **Difficulty**    | **Topic**                                                | **Score** |
+| 34    | Widget Production Calculation                                      | Simple            | Math Puzzle                                              | 95/100    |
+| 35     | Rectangle Area and Perimeter                                       | Complex           | Math Puzzle                                              | 90/100    |
+| 36     | Gauge Block Thermal Expansion and Uncertainty                      | Complex           | Metrology                                                | 85/100    |
+| 37    | Steel Rod Thermal Expansion and Relaxation                         | Deceptive         | Metrology                                                | 80/100    |
+| 38    | Meningitis Diagnosis                                               | Medium            | Medical (Diagnosis)                                      | 90/100    |
+| 39    | Farmer's Fence and Gate                                            | Deceptive         | Word Problem                                             | 95/100    |
+| 40    | C++ Pointer Behavior                                               | Medium            | Computer Science                                         | 90/100    |
+| 41    | Futuristic Emotion Dealer (Sci-Fi)                                 | Easy              | Creative Writing                                         | 95/100    |
+| 42    | Cursed Knight's Quest (Dark Fantasy)                               | Easy              | Creative Writing                                         | 90/100    |
+| 43    | Mad Scientist and Foresight (Sci-Fi)                               | Easy              | Creative Writing                                         | 90/100    |
+| 44    | Ideal Gas Partition Function and Average Energy                    | Medium            | Statistical Mechanics                                    | 95/100    |
+| 45    | Torus vs. Sphere Deformation                                       | Complex           | Algebraic Topology                                       | 80/100    |
+| 46    | Missing Jewels Heist                                               | Complex           | General Reasoning                                        | 85/100    |
+| 47    | Vanishing Violinist                                                | Complex           | Detective Conan Puzzle                                   | 75-85/100 |
+| 48    | Counterfeit Cleat Sabotage                                         | Complex           | James Bond/Conan Mashup                                  | 70-80/100 |
+| 49    | Ancient Cipher                                                     | Challenging       | Symbolic Reasoning                                       | 70-95/100 |
+| 50   | AlphaZero’s Knight vs. Bishop Puzzle                               | Medium            | Game Theory & Reinforcement Learning                     | 88/100    |
+
+---
+
+
+### **Summary of Anvita’s Scores:**
+
+- **Total Tasks Attempted:** 50  
+- **Average Score:** **83.86 / 100**  
+- **Highest Scores:** 100/100 (Multiple Tasks)  
+- **Lowest Score:** 60/100 (Polygon Permutations)  
+
+---
+
+### **Performance Insights by Difficulty Level:**
+
+1. **Easy Tasks:**  
+   - **Excellent performance**, with an average score of **94/100**.  
+   - Example: Anthropology, Decimal Comparison, Creative Writing Task.
+
+2. **Medium Tasks:**  
+   - **Strong performance**, with an average score of **86.46/100**.  
+   - Example: Japanese Haiku, Medical Diagnosis, Path Uniqueness Problem.
+
+3. **Hard Tasks:**  
+   - **Solid performance**, averaging **81.27/100**, though with some variability.  
+   - Example: Murder Mysteries, Harappan Civilization Question.
+
+4. **Challenging Tasks:**  
+   - **Good adaptability**, with an average score of **77.25/100**.  
+   - Example: Vigenère Cipher, AI Cryptic Puzzle, Symbolic Reasoning.
+
+5. **Expert Tasks:**  
+   - **Room for improvement**, averaging **77.6/100** in **advanced mathematics and combinatorial reasoning**.  
+   - Example: Polygon Permutations, Graph Theory Scheduling.
+
+6. **Complex Tasks:**  
+   - **Stable performance**, averaging **80.83/100**.  
+   - Example: Statistical Mechanics, Algebraic Topology.
+
+7. **Deceptive Tasks:**  
+   - **Exceptional problem-solving**, with an average score of **87.5/100**.  
+   - Example: Steel Rod Thermal Expansion, Farmer's Fence and Gate.
+
+8. **Simple Tasks:**  
+   - **Perfect performance**, with an average score of **95/100**.  
+   - Example: Widget Production Calculation.
+
+9. **Very Hard Tasks:**  
+   - **Challenging area**, with an average score of **65/100**, suggesting opportunities for growth.  
+   - Example: Table Tennis Scheduling Problem.
+
+

README.md

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+---
+base_model:
+- Qwen/Qwen2.5-7B-Instruct
+library_name: transformers
+tags:
+- reasoning
+- qwen
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+model-index:
+- name: Qwen2.5-7B-Anvita
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 64.33
+      name: strict accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 35.48
+      name: normalized accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 15.86
+      name: exact match
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 10.29
+      name: acc_norm
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 13.47
+      name: acc_norm
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 35.17
+      name: accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      name: Open LLM Leaderboard
+---
+
+
+## Evaluation Results
+| **Metric**              | **Value** |
+|-------------------------|--------------:|
+| **Avg.**                | **29.18**      |
+| **IFEval (0-Shot)**      | 64.8         |
+| **BBH (3-Shot)**         | 35.48         |
+| **MATH Level 5 (4-Shot)**| 15.86         |
+| **GPQA (0-Shot)**        | 10.29         |
+| **MuSR (0-Shot)**        | 13.47        |
+| **MMLU-PRO (5-Shot)**    | 35.17        |
+
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/sethuiyer/Qwen2.5-7B-Anvita/results_2024-10-27T11-40-06.834908.json).
+Personal Benchmarks - check [PERSONAL_BENCHMARK.md](./PERSONAL_BENCHMARK.md) merge

REASON_PROMPT_TEMPLATE.md

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+Use a structured, multi-step reasoning process to answer any given question or problem. 
+Begin by clearly identifying the key components of the problem, then generate a hypothesis or multiple possible explanations. 
+Proceed by breaking the problem down into smaller parts and analyzing each one through cause-and-effect relationships. 
+Draw on relevant general knowledge or factual information to support your reasoning. 
+For decisions or evaluations, compare all available options systematically, identifying their strengths and weaknesses.
+Ensure that each conclusion is checked for logical consistency and that any biases or assumptions are explicitly acknowledged and minimized. 
+After formulating a response, provide a transparent explanation of the reasoning process, highlighting how inferences were made, potential alternative solutions, and justifications for your final conclusions. 
+If ambiguity exists, offer multiple perspectives and indicate which one is most likely or optimal based on the evidence "

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+  ],
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+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

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+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% set system_message = 'You are a helpful assistant.' %}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}{% if system_message is defined %}{{ '<|im_start|>system\n' + system_message + '<|im_end|>\n' }}{% endif %}{% for message in loop_messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|im_start|>user\n' + content + '<|im_end|>\n<|im_start|>assistant\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|im_end|>' + '\n' }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}