---
language:
- en
- de
license: mit
model-index:
- name: LexGPT-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: 66.47
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/LexGPT-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: 85.91
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/LexGPT-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: 64.48
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/LexGPT-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: 59.98
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/LexGPT-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: 78.53
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/LexGPT-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: 61.56
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/LexGPT-V3
      name: Open LLM Leaderboard
---
This Model was just an Test Train to see how our new Training Algorithm and Data does like.

Model is based on Mistral v0.1

As this was an test run, we just tested it and heres the Data, the model hasnt Improved any better.

| Model | Turn 1 Score | Turn 2 Score | Average Score |
|-------|-------------|-------------|---------------|
| gpt-4 | 8.95625      | 9.025000     | 8.990625       |
| gpt-3.5-turbo | 8.075000     | 7.943750     | 7.943750       |
| claude-v1  | 8.150000     | 7.900000     | 8.025000       |
| **LexGPT-V3** | **8.14375**      | 7.719355     | 7.926667       |
| vicuna-13b-v1.3 | 6.812500    | 5.962500     | 6.387500       |

Open-LLM Leaderboard Results:
[Results](https://huggingface.co/datasets/open-llm-leaderboard/details_lex-hue__LexGPT-V3)
# [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_lex-hue__LexGPT-V3)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.49|
|AI2 Reasoning Challenge (25-Shot)|66.47|
|HellaSwag (10-Shot)              |85.91|
|MMLU (5-Shot)                    |64.48|
|TruthfulQA (0-shot)              |59.98|
|Winogrande (5-shot)              |78.53|
|GSM8k (5-shot)                   |61.56|