README.md

---

license: apache-2.0
library_name: transformers
base_model:
- nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2
datasets:
- flammenai/Date-DPO-NoAsterisks
- jondurbin/truthy-dpo-v0.1
model-index:
- name: Flammades-Mistral-Nemo-12B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 38.42
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Flammades-Mistral-Nemo-12B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 32.39
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Flammades-Mistral-Nemo-12B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 6.19
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Flammades-Mistral-Nemo-12B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 7.16
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Flammades-Mistral-Nemo-12B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 20.31
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Flammades-Mistral-Nemo-12B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 29.57
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Flammades-Mistral-Nemo-12B
      name: Open LLM Leaderboard

---

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# QuantFactory/Flammades-Mistral-Nemo-12B-GGUF
This is quantized version of [flammenai/Flammades-Mistral-Nemo-12B](https://huggingface.co./flammenai/Flammades-Mistral-Nemo-12B) created using llama.cpp

# Original Model Card


# Flammades-Mistral-Nemo-12B

[nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2](https://huggingface.co./nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2) finetuned on [flammenai/Date-DPO-NoAsterisks](https://huggingface.co./datasets/flammenai/Date-DPO-NoAsterisks) and [jondurbin/truthy-dpo-v0.1](https://huggingface.co./datasets/jondurbin/truthy-dpo-v0.1).

### Method

[ORPO tuned](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html) with 2x RTX 3090 for 3 epochs.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_nbeerbower__Flammades-Mistral-Nemo-12B)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |22.34|
|IFEval (0-Shot)    |38.42|
|BBH (3-Shot)       |32.39|
|MATH Lvl 5 (4-Shot)| 6.19|
|GPQA (0-shot)      | 7.16|
|MuSR (0-shot)      |20.31|
|MMLU-PRO (5-shot)  |29.57|