README.md

---
license: unlicense
tags:
- mergekit
- merge
base_model:
- AI-B/UTENA-7B-NSFW
- AI-B/UTENA-7B-BAGEL
model-index:
- name: UTENA-7B-NSFW-V2
  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: 63.31
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AI-B/UTENA-7B-NSFW-V2
      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: 84.54
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AI-B/UTENA-7B-NSFW-V2
      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: 63.97
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AI-B/UTENA-7B-NSFW-V2
      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: 47.81
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AI-B/UTENA-7B-NSFW-V2
      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: 78.69
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AI-B/UTENA-7B-NSFW-V2
      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: 42.38
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AI-B/UTENA-7B-NSFW-V2
      name: Open LLM Leaderboard
---
# nsfw

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

### Models Merged

The following models were included in the merge:
* [AI-B/UTENA-7B-NSFW](https://huggingface.co/AI-B/UTENA-7B-NSFW)
* [AI-B/UTENA-7B-BAGEL](https://huggingface.co/AI-B/UTENA-7B-BAGEL)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
      - model: AI-B/UTENA-7B-NSFW
        layer_range: [0, 32]
      - model: AI-B/UTENA-7B-BAGEL
        layer_range: [0, 32]
merge_method: slerp
base_model: AI-B/UTENA-7B-NSFW
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

```
 
## Quanitized Models

[UTENA-7B-NSFW-V2-GGUF](https://huggingface.co/s3nh/UTENA-7B-NSFW-V2-GGUF)
# [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_AI-B__UTENA-7B-NSFW-V2)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |63.45|
|AI2 Reasoning Challenge (25-Shot)|63.31|
|HellaSwag (10-Shot)              |84.54|
|MMLU (5-Shot)                    |63.97|
|TruthfulQA (0-shot)              |47.81|
|Winogrande (5-shot)              |78.69|
|GSM8k (5-shot)                   |42.38|