README.md

---
language:
- en
license: cc-by-nc-4.0
library_name: transformers
tags:
- text-generation-inference
datasets:
- argilla/OpenHermesPreferences
pipeline_tag: text-generation
model-index:
- name: ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3
  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: 73.04
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3
      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: 89.11
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3
      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: 64.79
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3
      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: 77.48
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3
      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: 84.77
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3
      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: 69.22
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3
      name: Open LLM Leaderboard
---

Just dpo finetuned this model a bit more: https://huggingface.co/eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO on the https://huggingface.co/datasets/argilla/dpo-mix-7k dataset

As is described in the original model repo, not yet fully tested therefore potentially a bad match for using out-of-the-box, use with caution.




## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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## Uses

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## Training Details

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#### Training Hyperparameters

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## Evaluation

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#### Summary



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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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# [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_eren23__ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v3)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |76.40|
|AI2 Reasoning Challenge (25-Shot)|73.04|
|HellaSwag (10-Shot)              |89.11|
|MMLU (5-Shot)                    |64.79|
|TruthfulQA (0-shot)              |77.48|
|Winogrande (5-shot)              |84.77|
|GSM8k (5-shot)                   |69.22|