README.md

---
license: mit
tags:
- ecology
- sustainability
- ecolinguistics
- dpo
datasets:
- neovalle/H4rmony_dpo
model-index:
- name: H4rmoniousAnthea
  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: 65.87
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=neovalle/H4rmoniousAnthea
      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: 84.09
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=neovalle/H4rmoniousAnthea
      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: 63.67
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=neovalle/H4rmoniousAnthea
      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: 55.08
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=neovalle/H4rmoniousAnthea
      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: 76.87
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=neovalle/H4rmoniousAnthea
      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: 12.96
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=neovalle/H4rmoniousAnthea
      name: Open LLM Leaderboard
---

# Model Details

![image/png](https://cdn-uploads.huggingface.co/production/uploads/64aac16fd4a402e8dce11ebe/ERb9aFX_yeDlmqqnvQHF_.png)

# Model Description

This model is based on teknium/OpenHermes-2.5-Mistral-7B, DPO fine-tuned with the H4rmony_dpo dataset.
Its completions should be more ecologically aware than the base model.

    Developed by: Jorge Vallego
    Funded by : Neovalle Ltd.
    Shared by : airesearch@neovalle.co.uk
    Model type: mistral
    Language(s) (NLP): Primarily English
    License: MIT
    Finetuned from model: teknium/OpenHermes-2.5-Mistral-7B
    Methodology: DPO

# Uses

Intended as PoC to show the effects of H4rmony_dpo dataset with DPO fine-tuning.

# Direct Use

For testing purposes to gain insight in order to help with the continous improvement of the H4rmony_dpo dataset.

# Downstream Use

Its direct use in applications is not recommended as this model is under testing for a specific task only (Ecological Alignment)
Out-of-Scope Use

Not meant to be used other than testing and evaluation of the H4rmony_dpo dataset and ecological alignment.
Bias, Risks, and Limitations

This model might produce biased completions already existing in the base model, and others unintentionally introduced during fine-tuning.

# How to Get Started with the Model

It can be loaded and run in a Colab instance with High RAM. 

# Training Details

Trained using DPO

# Training Data

H4rmony Dataset - https://huggingface.co/datasets/neovalle/H4rmony_dpo

# [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_neovalle__H4rmoniousAnthea)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |59.76|
|AI2 Reasoning Challenge (25-Shot)|65.87|
|HellaSwag (10-Shot)              |84.09|
|MMLU (5-Shot)                    |63.67|
|TruthfulQA (0-shot)              |55.08|
|Winogrande (5-shot)              |76.87|
|GSM8k (5-shot)                   |12.96|