---
language:
- en
license: cc-by-2.0
tags:
- finance
- legal
- biology
- art
model-index:
- name: SatoshiNv5
  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: 60.49
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
      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: 82.94
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
      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: 63.42
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
      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: 41.8
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
      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: 78.69
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
      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: 34.72
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
      name: Open LLM Leaderboard
---

Behold, one of the first fine-tunes of Mistral's 7B 0.2 Base model. SatoshiN is trained on 4 epochs 2e-4 learning rate (cosine) of a diverse custom data-set, combined with a polishing round of that same data-set at a 1e-4 linear learning rate.
It's a nice assistant that isn't afraid to ask questions, and gather additional information before providing a response to user prompts.

SatoshiN | Base-Model

Wikitext Perplexity: 6.27 | 5.4

**Similar to SOTA, this model runs a bit hot, try using lower temperatures below .5 if experiencing any nonsense)

# [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_chrischain__SatoshiNv5)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |60.34|
|AI2 Reasoning Challenge (25-Shot)|60.49|
|HellaSwag (10-Shot)              |82.94|
|MMLU (5-Shot)                    |63.42|
|TruthfulQA (0-shot)              |41.80|
|Winogrande (5-shot)              |78.69|
|GSM8k (5-shot)                   |34.72|