README.md

---
license: apache-2.0
library_name: adapter-transformers
datasets:
- netcat420/MFANN
model-index:
- name: MFANN3b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 43.09
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=netcat420/MFANN3b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 72.33
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=netcat420/MFANN3b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 26.74
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=netcat420/MFANN3b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 40.22
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=netcat420/MFANN3b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 62.67
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=netcat420/MFANN3b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 3.34
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=netcat420/MFANN3b
      name: Open LLM Leaderboard
---

Fine-tuned on an expansive database comprising over 2.5 million tokens meticulously structured for chain of thought reasoning, MFANN emerges as a powerhouse in understanding and generating coherent, contextually rich text. Its robust architecture enables it to seamlessly navigate complex linguistic nuances, adeptly chaining together ideas to produce fluid, human-like discourse.

MFANN's exceptional capacity for reasoning shines through in its ability to grasp intricate concepts and synthesize information cohesively. Whether tackling intricate philosophical debates, crafting compelling narratives, or generating insightful analyses, MFANN consistently delivers results that are both insightful and compelling.

Empowered by its massive parameter count and rigorous fine-tuning process, MFANN excels in a myriad of applications, from natural language understanding and generation to content creation and dialogue systems. Its versatility and proficiency make it an invaluable tool across various domains, empowering researchers, developers, and innovators alike to push the boundaries of what's possible in artificial intelligence.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_netcat420__MFANN3b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |41.40|
|AI2 Reasoning Challenge (25-Shot)|43.09|
|HellaSwag (10-Shot)              |72.33|
|MMLU (5-Shot)                    |26.74|
|TruthfulQA (0-shot)              |40.22|
|Winogrande (5-shot)              |62.67|
|GSM8k (5-shot)                   | 3.34|