---
language:
- en
license: apache-2.0
library_name: transformers
datasets:
- Intel/orca_dpo_pairs
- mlabonne/chatml_dpo_pairs
model-index:
- name: neuronovo-9B-v0.4
  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: 72.44
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Neuronovo/neuronovo-9B-v0.4
      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: 88.33
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Neuronovo/neuronovo-9B-v0.4
      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: 65.24
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Neuronovo/neuronovo-9B-v0.4
      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: 71.07
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Neuronovo/neuronovo-9B-v0.4
      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: 80.66
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Neuronovo/neuronovo-9B-v0.4
      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: 62.77
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Neuronovo/neuronovo-9B-v0.4
      name: Open LLM Leaderboard
---
More information about previous [Neuronovo/neuronovo-9B-v0.2](https://huggingface.co/Neuronovo/neuronovo-9B-v0.2) version available here: 🔗[Don't stop DPOptimizing!](https://www.linkedin.com/pulse/dont-stop-dpoptimizing-jan-koco%2525C5%252584-mq4qf)

Author: Jan Kocoń     🔗[LinkedIn](https://www.linkedin.com/in/jankocon/)     🔗[Google Scholar](https://scholar.google.com/citations?user=pmQHb5IAAAAJ&hl=en&oi=ao)     🔗[ResearchGate](https://www.researchgate.net/profile/Jan-Kocon-2)

Changes concerning [Neuronovo/neuronovo-9B-v0.2](https://huggingface.co/Neuronovo/neuronovo-9B-v0.2):

1. **Training Dataset**: In addition to the [Intel/orca_dpo_pairs](Intel/orca_dpo_pairs) dataset, this version incorporates a [mlabonne/chatml_dpo_pairs](https://huggingface.co/datasets/mlabonne/chatml_dpo_pairs). The combined datasets enhance the model's capabilities in dialogues and interactive scenarios, further specializing it in natural language understanding and response generation.

2. **Tokenizer and Formatting**: The tokenizer now originates directly from the [Neuronovo/neuronovo-9B-v0.2](https://huggingface.co/Neuronovo/neuronovo-9B-v0.2) model.

3. **Training Configuration**: The training approach has shifted from using `max_steps=200` to `num_train_epochs=1`. This represents a change in the training strategy, focusing on epoch-based training rather than a fixed number of steps.

4. **Learning Rate**: The learning rate has been reduced to a smaller value of `5e-8`. This finer learning rate allows for more precise adjustments during the training process, potentially leading to better model performance.
# [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_Neuronovo__neuronovo-9B-v0.4)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |73.42|
|AI2 Reasoning Challenge (25-Shot)|72.44|
|HellaSwag (10-Shot)              |88.33|
|MMLU (5-Shot)                    |65.24|
|TruthfulQA (0-shot)              |71.07|
|Winogrande (5-shot)              |80.66|
|GSM8k (5-shot)                   |62.77|