README.md

---
license: apache-2.0
library_name: transformers
datasets:
- Intel/orca_dpo_pairs
base_model: NeuralNovel/Gecko-7B-v0.1
inference: false
model-index:
- name: Gecko-7B-v0.1-DPO
  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: 56.74
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
      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: 82.38
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
      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: 60.42
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
      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: 57.42
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
      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: 77.35
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
      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: 45.03
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
      name: Open LLM Leaderboard
---

![Gecko](https://i.ibb.co/gtf92Nt/OIG-43.jpg)

# NeuralNovel/Gecko-7B-v0.1-DPO
Designed to generate instructive and narrative text, with a focus on mathematics & numeracy.

Full-parameter fine-tune (FFT) of Mistral-7B-Instruct-v0.2, with apache-2.0 license.

You may download and use this model for research, training and commercial purposes.

This model is suitable for commercial deployment.

[Join our Discord!](https://discord.gg/rJXGjmxqzS)

<a href='https://ko-fi.com/S6S2UH2TC' target='_blank'><img height='36' 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>

### Data-set

The model was finetuned using the orca_dpo_pairs dataset 


### Summary

Fine-tuned with the intention of following all prompt directions, making it more suitable for math questions and problem solving.

#### 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

This model may not work as intended. As such all users are encouraged to use this model with caution and respect.

This model is for testing and research purposes only, it has reduced levels of alignment and as a result may produce NSFW or harmful content.
The user is responsible for their output and must use this model responsibly.

### Hardware and Training

Trained on a single 80GB A100 for 2 hours trained using Axolotl

Thank you to **h2m** for the generous funding. 
# [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_NeuralNovel__Gecko-7B-v0.1-DPO)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |63.22|
|AI2 Reasoning Challenge (25-Shot)|56.74|
|HellaSwag (10-Shot)              |82.38|
|MMLU (5-Shot)                    |60.42|
|TruthfulQA (0-shot)              |57.42|
|Winogrande (5-shot)              |77.35|
|GSM8k (5-shot)                   |45.03|