---
language:
- en
license: apache-2.0
library_name: transformers
datasets:
- NeuralNovel/Neural-Story-v1
base_model: mistralai/Mistral-7B-Instruct-v0.2
inference: false
model-index:
- name: Mistral-7B-Instruct-v0.2-Neural-Story
  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: 64.08
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      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: 83.97
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      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: 60.67
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      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: 66.89
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      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: 75.85
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      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: 38.29
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      name: Open LLM Leaderboard
---

![Neural-Story](https://i.ibb.co/JFRYk6g/OIG-27.jpg)
# NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
[GGUF FILES HERE](https://huggingface.co/Kquant03/Mistral-7B-Instruct-v0.2-Neural-Story-GGUF)

The **Mistral-7B-Instruct-v0.2-Neural-Story** model, developed by NeuralNovel and funded by Techmind, is a language model finetuned from Mistral-7B-Instruct-v0.2.

Designed to generate instructive and narrative text, with a specific focus on storytelling.
This fine-tune has been tailored to provide detailed and creative responses in the context of narrative and optimised for short story telling.

Based on mistralAI, with apache-2.0 license, suitable for commercial or non-commercial use.

<a href='https://ko-fi.com/S6S2UH2TC' target='_blank'><img height='38' style='border:0px;height:36px;' src='https://storage.ko-fi.com/cdn/kofi1.png?v=3' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a>
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### Data-set
The model was finetuned using the Neural-Story-v1 dataset.

### Benchmark
| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | **64.96**   |
| ARC          | 64.08          |
| HellaSwag    | **66.89**   |
| MMLU         | 60.67         |
| TruthfulQA    | 66.89   |
| Winogrande    | **75.85**   |
| GSM8K         | 38.29        |

Evaluated on **HuggingFaceH4/open_llm_leaderboard**

### Summary

Fine-tuned with the intention of generating creative and narrative text, making it more suitable for creative writing prompts and storytelling.

#### Out-of-Scope Use

The model may not perform well in scenarios unrelated to instructive and narrative text generation. Misuse or applications outside its designed scope may result in suboptimal outcomes.

### Bias, Risks, and Limitations

The model may exhibit biases or limitations inherent in the training data. It is essential to consider these factors when deploying the model to avoid unintended consequences.

While the Neural-Story-v0.1 dataset serves as an excellent starting point for testing language models, users are advised to exercise caution, as there might be some inherent genre or writing bias.

### Hardware and Training


```

  n_epochs = 3,
  n_checkpoints = 3,
  batch_size = 12,
  learning_rate = 1e-5,



```

*Sincere appreciation to Techmind for their generous sponsorship.*